diff --git a/.circleci/config.yml b/.circleci/config.yml index b0a369a35..b996dc312 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -625,6 +625,48 @@ jobs: paths: - llm_translation_coverage.xml - llm_translation_coverage + pass_through_unit_testing: + docker: + - image: cimg/python:3.11 + auth: + username: ${DOCKERHUB_USERNAME} + password: ${DOCKERHUB_PASSWORD} + working_directory: ~/project + + steps: + - checkout + - run: + name: Install Dependencies + command: | + python -m pip install --upgrade pip + python -m pip install -r requirements.txt + pip install "pytest==7.3.1" + pip install "pytest-retry==1.6.3" + pip install "pytest-cov==5.0.0" + pip install "pytest-asyncio==0.21.1" + pip install "respx==0.21.1" + # Run pytest and generate JUnit XML report + - run: + name: Run tests + command: | + pwd + ls + python -m pytest -vv tests/pass_through_unit_tests --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5 + no_output_timeout: 120m + - run: + name: Rename the coverage files + command: | + mv coverage.xml pass_through_unit_tests_coverage.xml + mv .coverage pass_through_unit_tests_coverage + + # Store test results + - store_test_results: + path: test-results + - persist_to_workspace: + root: . + paths: + - pass_through_unit_tests_coverage.xml + - pass_through_unit_tests_coverage image_gen_testing: docker: - image: cimg/python:3.11 @@ -765,12 +807,14 @@ jobs: curl https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash - run: python -c "from litellm import *" || (echo '🚨 import failed, this means you introduced unprotected imports! 🚨'; exit 1) - run: ruff check ./litellm - - run: python ./tests/documentation_tests/test_general_setting_keys.py + # - run: python ./tests/documentation_tests/test_general_setting_keys.py - run: python ./tests/code_coverage_tests/router_code_coverage.py - run: python ./tests/code_coverage_tests/test_router_strategy_async.py - run: python ./tests/code_coverage_tests/litellm_logging_code_coverage.py - run: python ./tests/documentation_tests/test_env_keys.py + - run: python ./tests/documentation_tests/test_router_settings.py - run: python ./tests/documentation_tests/test_api_docs.py + - run: python ./tests/code_coverage_tests/ensure_async_clients_test.py - run: helm lint ./deploy/charts/litellm-helm db_migration_disable_update_check: @@ -922,7 +966,7 @@ jobs: command: | pwd ls - python -m pytest -s -vv tests/*.py -x --junitxml=test-results/junit.xml --durations=5 --ignore=tests/otel_tests --ignore=tests/pass_through_tests --ignore=tests/proxy_admin_ui_tests --ignore=tests/load_tests --ignore=tests/llm_translation --ignore=tests/image_gen_tests + python -m pytest -s -vv tests/*.py -x --junitxml=test-results/junit.xml --durations=5 --ignore=tests/otel_tests --ignore=tests/pass_through_tests --ignore=tests/proxy_admin_ui_tests --ignore=tests/load_tests --ignore=tests/llm_translation --ignore=tests/image_gen_tests --ignore=tests/pass_through_unit_tests no_output_timeout: 120m # Store test results @@ -1136,6 +1180,7 @@ jobs: pip install "PyGithub==1.59.1" pip install "google-cloud-aiplatform==1.59.0" pip install anthropic + # Run pytest and generate JUnit XML report - run: name: Build Docker image command: docker build -t my-app:latest -f ./docker/Dockerfile.database . @@ -1147,6 +1192,7 @@ jobs: -e DATABASE_URL=$PROXY_DATABASE_URL \ -e LITELLM_MASTER_KEY="sk-1234" \ -e OPENAI_API_KEY=$OPENAI_API_KEY \ + -e GEMINI_API_KEY=$GEMINI_API_KEY \ -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \ -e LITELLM_LICENSE=$LITELLM_LICENSE \ --name my-app \ @@ -1171,6 +1217,27 @@ jobs: - run: name: Wait for app to be ready command: dockerize -wait http://localhost:4000 -timeout 5m + # New steps to run Node.js test + - run: + name: Install Node.js + command: | + curl -fsSL https://deb.nodesource.com/setup_18.x | sudo -E bash - + sudo apt-get install -y nodejs + node --version + npm --version + + - run: + name: Install Node.js dependencies + command: | + npm install @google-cloud/vertexai + npm install @google/generative-ai + npm install --save-dev jest + + - run: + name: Run Vertex AI, Google AI Studio Node.js tests + command: | + npx jest tests/pass_through_tests --verbose + no_output_timeout: 30m - run: name: Run tests command: | @@ -1178,7 +1245,6 @@ jobs: ls python -m pytest -vv tests/pass_through_tests/ -x --junitxml=test-results/junit.xml --durations=5 no_output_timeout: 120m - # Store test results - store_test_results: path: test-results @@ -1204,7 +1270,7 @@ jobs: python -m venv venv . venv/bin/activate pip install coverage - coverage combine llm_translation_coverage logging_coverage litellm_router_coverage local_testing_coverage litellm_assistants_api_coverage auth_ui_unit_tests_coverage langfuse_coverage caching_coverage litellm_proxy_unit_tests_coverage image_gen_coverage + coverage combine llm_translation_coverage logging_coverage litellm_router_coverage local_testing_coverage litellm_assistants_api_coverage auth_ui_unit_tests_coverage langfuse_coverage caching_coverage litellm_proxy_unit_tests_coverage image_gen_coverage pass_through_unit_tests_coverage coverage xml - codecov/upload: file: ./coverage.xml @@ -1310,6 +1376,7 @@ jobs: name: Install Dependencies command: | npm install -D @playwright/test + npm install @google-cloud/vertexai pip install "pytest==7.3.1" pip install "pytest-retry==1.6.3" pip install "pytest-asyncio==0.21.1" @@ -1341,7 +1408,7 @@ jobs: command: | docker run -d \ -p 4000:4000 \ - -e DATABASE_URL=$PROXY_DATABASE_URL \ + -e DATABASE_URL=$PROXY_DATABASE_URL_2 \ -e LITELLM_MASTER_KEY="sk-1234" \ -e OPENAI_API_KEY=$OPENAI_API_KEY \ -e UI_USERNAME="admin" \ @@ -1371,7 +1438,7 @@ jobs: - run: name: Run Playwright Tests command: | - npx playwright test --reporter=html --output=test-results + npx playwright test e2e_ui_tests/ --reporter=html --output=test-results no_output_timeout: 120m - store_test_results: path: test-results @@ -1493,6 +1560,12 @@ workflows: only: - main - /litellm_.*/ + - pass_through_unit_testing: + filters: + branches: + only: + - main + - /litellm_.*/ - image_gen_testing: filters: branches: @@ -1508,6 +1581,7 @@ workflows: - upload-coverage: requires: - llm_translation_testing + - pass_through_unit_testing - image_gen_testing - logging_testing - litellm_router_testing @@ -1548,6 +1622,7 @@ workflows: - load_testing - test_bad_database_url - llm_translation_testing + - pass_through_unit_testing - image_gen_testing - logging_testing - litellm_router_testing diff --git a/docs/my-website/docs/completion/input.md b/docs/my-website/docs/completion/input.md index c563a5bf0..e55c160e0 100644 --- a/docs/my-website/docs/completion/input.md +++ b/docs/my-website/docs/completion/input.md @@ -41,7 +41,7 @@ Use `litellm.get_supported_openai_params()` for an updated list of params for ea | Provider | temperature | max_completion_tokens | max_tokens | top_p | stream | stream_options | stop | n | presence_penalty | frequency_penalty | functions | function_call | logit_bias | user | response_format | seed | tools | tool_choice | logprobs | top_logprobs | extra_headers | |---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---| -|Anthropic| ✅ | ✅ | ✅ |✅ | ✅ | ✅ | ✅ | | | | | | |✅ | ✅ | ✅ | ✅ | ✅ | | | ✅ | +|Anthropic| ✅ | ✅ | ✅ |✅ | ✅ | ✅ | ✅ | | | | | | |✅ | ✅ | | ✅ | ✅ | | | ✅ | |OpenAI| ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ | ✅ | ✅ |✅ | ✅ | ✅ | ✅ | ✅ | |Azure OpenAI| ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |✅ | ✅ | ✅ | ✅ |✅ | ✅ | | | ✅ | |Replicate | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | | | | | diff --git a/docs/my-website/docs/guides/finetuned_models.md b/docs/my-website/docs/guides/finetuned_models.md new file mode 100644 index 000000000..cb0d49b44 --- /dev/null +++ b/docs/my-website/docs/guides/finetuned_models.md @@ -0,0 +1,74 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + + +# Calling Finetuned Models + +## OpenAI + + +| Model Name | Function Call | +|---------------------------|-----------------------------------------------------------------| +| fine tuned `gpt-4-0613` | `response = completion(model="ft:gpt-4-0613", messages=messages)` | +| fine tuned `gpt-4o-2024-05-13` | `response = completion(model="ft:gpt-4o-2024-05-13", messages=messages)` | +| fine tuned `gpt-3.5-turbo-0125` | `response = completion(model="ft:gpt-3.5-turbo-0125", messages=messages)` | +| fine tuned `gpt-3.5-turbo-1106` | `response = completion(model="ft:gpt-3.5-turbo-1106", messages=messages)` | +| fine tuned `gpt-3.5-turbo-0613` | `response = completion(model="ft:gpt-3.5-turbo-0613", messages=messages)` | + + +## Vertex AI + +Fine tuned models on vertex have a numerical model/endpoint id. + + + + +```python +from litellm import completion +import os + +## set ENV variables +os.environ["VERTEXAI_PROJECT"] = "hardy-device-38811" +os.environ["VERTEXAI_LOCATION"] = "us-central1" + +response = completion( + model="vertex_ai/", # e.g. vertex_ai/4965075652664360960 + messages=[{ "content": "Hello, how are you?","role": "user"}], + base_model="vertex_ai/gemini-1.5-pro" # the base model - used for routing +) +``` + + + + +1. Add Vertex Credentials to your env + +```bash +!gcloud auth application-default login +``` + +2. Setup config.yaml + +```yaml +- model_name: finetuned-gemini + litellm_params: + model: vertex_ai/ + vertex_project: + vertex_location: + model_info: + base_model: vertex_ai/gemini-1.5-pro # IMPORTANT +``` + +3. Test it! + +```bash +curl --location 'https://0.0.0.0:4000/v1/chat/completions' \ +--header 'Content-Type: application/json' \ +--header 'Authorization: ' \ +--data '{"model": "finetuned-gemini" ,"messages":[{"role": "user", "content":[{"type": "text", "text": "hi"}]}]}' +``` + + + + + diff --git a/docs/my-website/docs/moderation.md b/docs/my-website/docs/moderation.md new file mode 100644 index 000000000..6dd092fb5 --- /dev/null +++ b/docs/my-website/docs/moderation.md @@ -0,0 +1,135 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Moderation + + +### Usage + + + +```python +from litellm import moderation + +response = moderation( + input="hello from litellm", + model="text-moderation-stable" +) +``` + + + + +For `/moderations` endpoint, there is **no need to specify `model` in the request or on the litellm config.yaml** + +Start litellm proxy server + +``` +litellm +``` + + + + + +```python +from openai import OpenAI + +# set base_url to your proxy server +# set api_key to send to proxy server +client = OpenAI(api_key="", base_url="http://0.0.0.0:4000") + +response = client.moderations.create( + input="hello from litellm", + model="text-moderation-stable" # optional, defaults to `omni-moderation-latest` +) + +print(response) +``` + + + + +```shell +curl --location 'http://0.0.0.0:4000/moderations' \ + --header 'Content-Type: application/json' \ + --header 'Authorization: Bearer sk-1234' \ + --data '{"input": "Sample text goes here", "model": "text-moderation-stable"}' +``` + + + + + + +## Input Params +LiteLLM accepts and translates the [OpenAI Moderation params](https://platform.openai.com/docs/api-reference/moderations) across all supported providers. + +### Required Fields + +- `input`: *string or array* - Input (or inputs) to classify. Can be a single string, an array of strings, or an array of multi-modal input objects similar to other models. + - If string: A string of text to classify for moderation + - If array of strings: An array of strings to classify for moderation + - If array of objects: An array of multi-modal inputs to the moderation model, where each object can be: + - An object describing an image to classify with: + - `type`: *string, required* - Always `image_url` + - `image_url`: *object, required* - Contains either an image URL or a data URL for a base64 encoded image + - An object describing text to classify with: + - `type`: *string, required* - Always `text` + - `text`: *string, required* - A string of text to classify + +### Optional Fields + +- `model`: *string (optional)* - The moderation model to use. Defaults to `omni-moderation-latest`. + +## Output Format +Here's the exact json output and type you can expect from all moderation calls: + +[**LiteLLM follows OpenAI's output format**](https://platform.openai.com/docs/api-reference/moderations/object) + + +```python +{ + "id": "modr-AB8CjOTu2jiq12hp1AQPfeqFWaORR", + "model": "text-moderation-007", + "results": [ + { + "flagged": true, + "categories": { + "sexual": false, + "hate": false, + "harassment": true, + "self-harm": false, + "sexual/minors": false, + "hate/threatening": false, + "violence/graphic": false, + "self-harm/intent": false, + "self-harm/instructions": false, + "harassment/threatening": true, + "violence": true + }, + "category_scores": { + "sexual": 0.000011726012417057063, + "hate": 0.22706663608551025, + "harassment": 0.5215635299682617, + "self-harm": 2.227119921371923e-6, + "sexual/minors": 7.107352217872176e-8, + "hate/threatening": 0.023547329008579254, + "violence/graphic": 0.00003391829886822961, + "self-harm/intent": 1.646940972932498e-6, + "self-harm/instructions": 1.1198755256458526e-9, + "harassment/threatening": 0.5694745779037476, + "violence": 0.9971134662628174 + } + } + ] +} + +``` + + +## **Supported Providers** + +| Provider | +|-------------| +| OpenAI | diff --git a/docs/my-website/docs/observability/argilla.md b/docs/my-website/docs/observability/argilla.md index 8d20b9daa..dad28ce90 100644 --- a/docs/my-website/docs/observability/argilla.md +++ b/docs/my-website/docs/observability/argilla.md @@ -4,24 +4,63 @@ import TabItem from '@theme/TabItem'; # Argilla -Argilla is a tool for annotating datasets. +Argilla is a collaborative annotation tool for AI engineers and domain experts who need to build high-quality datasets for their projects. +## Getting Started -## Usage +To log the data to Argilla, first you need to deploy the Argilla server. If you have not deployed the Argilla server, please follow the instructions [here](https://docs.argilla.io/latest/getting_started/quickstart/). + +Next, you will need to configure and create the Argilla dataset. + +```python +import argilla as rg + +client = rg.Argilla(api_url="", api_key="") + +settings = rg.Settings( + guidelines="These are some guidelines.", + fields=[ + rg.ChatField( + name="user_input", + ), + rg.TextField( + name="llm_output", + ), + ], + questions=[ + rg.RatingQuestion( + name="rating", + values=[1, 2, 3, 4, 5, 6, 7], + ), + ], +) + +dataset = rg.Dataset( + name="my_first_dataset", + settings=settings, +) + +dataset.create() +``` + +For further configuration, please refer to the [Argilla documentation](https://docs.argilla.io/latest/how_to_guides/dataset/). + + +## Usage ```python -from litellm import completion +import os import litellm -import os +from litellm import completion # add env vars os.environ["ARGILLA_API_KEY"]="argilla.apikey" os.environ["ARGILLA_BASE_URL"]="http://localhost:6900" -os.environ["ARGILLA_DATASET_NAME"]="my_second_dataset" +os.environ["ARGILLA_DATASET_NAME"]="my_first_dataset" os.environ["OPENAI_API_KEY"]="sk-proj-..." litellm.callbacks = ["argilla"] diff --git a/docs/my-website/docs/pass_through/anthropic_completion.md b/docs/my-website/docs/pass_through/anthropic_completion.md index 0c6a5f1b6..2e052f7cd 100644 --- a/docs/my-website/docs/pass_through/anthropic_completion.md +++ b/docs/my-website/docs/pass_through/anthropic_completion.md @@ -1,10 +1,18 @@ -# Anthropic `/v1/messages` +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Anthropic SDK Pass-through endpoints for Anthropic - call provider-specific endpoint, in native format (no translation). -Just replace `https://api.anthropic.com` with `LITELLM_PROXY_BASE_URL/anthropic` 🚀 +Just replace `https://api.anthropic.com` with `LITELLM_PROXY_BASE_URL/anthropic` #### **Example Usage** + + + + + ```bash curl --request POST \ --url http://0.0.0.0:4000/anthropic/v1/messages \ @@ -20,6 +28,33 @@ curl --request POST \ }' ``` + + + +```python +from anthropic import Anthropic + +# Initialize client with proxy base URL +client = Anthropic( + base_url="http://0.0.0.0:4000/anthropic", # /anthropic + api_key="sk-anything" # proxy virtual key +) + +# Make a completion request +response = client.messages.create( + model="claude-3-5-sonnet-20241022", + max_tokens=1024, + messages=[ + {"role": "user", "content": "Hello, world"} + ] +) + +print(response) +``` + + + + Supports **ALL** Anthropic Endpoints (including streaming). [**See All Anthropic Endpoints**](https://docs.anthropic.com/en/api/messages) @@ -222,14 +257,14 @@ curl https://api.anthropic.com/v1/messages/batches \ ``` -## Advanced - Use with Virtual Keys +## Advanced Pre-requisites - [Setup proxy with DB](../proxy/virtual_keys.md#setup) Use this, to avoid giving developers the raw Anthropic API key, but still letting them use Anthropic endpoints. -### Usage +### Use with Virtual Keys 1. Setup environment @@ -279,4 +314,58 @@ curl --request POST \ {"role": "user", "content": "Hello, world"} ] }' -``` \ No newline at end of file +``` + + +### Send `litellm_metadata` (tags) + + + + +```bash +curl --request POST \ + --url http://0.0.0.0:4000/anthropic/v1/messages \ + --header 'accept: application/json' \ + --header 'content-type: application/json' \ + --header "Authorization: bearer sk-anything" \ + --data '{ + "model": "claude-3-5-sonnet-20241022", + "max_tokens": 1024, + "messages": [ + {"role": "user", "content": "Hello, world"} + ], + "litellm_metadata": { + "tags": ["test-tag-1", "test-tag-2"] + } + }' +``` + + + + +```python +from anthropic import Anthropic + +client = Anthropic( + base_url="http://0.0.0.0:4000/anthropic", + api_key="sk-anything" +) + +response = client.messages.create( + model="claude-3-5-sonnet-20241022", + max_tokens=1024, + messages=[ + {"role": "user", "content": "Hello, world"} + ], + extra_body={ + "litellm_metadata": { + "tags": ["test-tag-1", "test-tag-2"] + } + } +) + +print(response) +``` + + + \ No newline at end of file diff --git a/docs/my-website/docs/pass_through/google_ai_studio.md b/docs/my-website/docs/pass_through/google_ai_studio.md index cc7f9ce71..ee5eecc19 100644 --- a/docs/my-website/docs/pass_through/google_ai_studio.md +++ b/docs/my-website/docs/pass_through/google_ai_studio.md @@ -1,12 +1,21 @@ +import Image from '@theme/IdealImage'; +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + + # Google AI Studio SDK Pass-through endpoints for Google AI Studio - call provider-specific endpoint, in native format (no translation). -Just replace `https://generativelanguage.googleapis.com` with `LITELLM_PROXY_BASE_URL/gemini` 🚀 +Just replace `https://generativelanguage.googleapis.com` with `LITELLM_PROXY_BASE_URL/gemini` #### **Example Usage** + + + + ```bash -http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-anything' \ +curl 'http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-anything' \ -H 'Content-Type: application/json' \ -d '{ "contents": [{ @@ -17,6 +26,53 @@ http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-any }' ``` + + + +```javascript +const { GoogleGenerativeAI } = require("@google/generative-ai"); + +const modelParams = { + model: 'gemini-pro', +}; + +const requestOptions = { + baseUrl: 'http://localhost:4000/gemini', // http:///gemini +}; + +const genAI = new GoogleGenerativeAI("sk-1234"); // litellm proxy API key +const model = genAI.getGenerativeModel(modelParams, requestOptions); + +async function main() { + try { + const result = await model.generateContent("Explain how AI works"); + console.log(result.response.text()); + } catch (error) { + console.error('Error:', error); + } +} + +// For streaming responses +async function main_streaming() { + try { + const streamingResult = await model.generateContentStream("Explain how AI works"); + for await (const chunk of streamingResult.stream) { + console.log('Stream chunk:', JSON.stringify(chunk)); + } + const aggregatedResponse = await streamingResult.response; + console.log('Aggregated response:', JSON.stringify(aggregatedResponse)); + } catch (error) { + console.error('Error:', error); + } +} + +main(); +// main_streaming(); +``` + + + + Supports **ALL** Google AI Studio Endpoints (including streaming). [**See All Google AI Studio Endpoints**](https://ai.google.dev/api) @@ -166,14 +222,14 @@ curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5 ``` -## Advanced - Use with Virtual Keys +## Advanced Pre-requisites - [Setup proxy with DB](../proxy/virtual_keys.md#setup) Use this, to avoid giving developers the raw Google AI Studio key, but still letting them use Google AI Studio endpoints. -### Usage +### Use with Virtual Keys 1. Setup environment @@ -220,4 +276,66 @@ http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-123 }] }] }' -``` \ No newline at end of file +``` + + +### Send `tags` in request headers + +Use this if you want `tags` to be tracked in the LiteLLM DB and on logging callbacks. + +Pass tags in request headers as a comma separated list. In the example below the following tags will be tracked + +``` +tags: ["gemini-js-sdk", "pass-through-endpoint"] +``` + + + + +```bash +curl 'http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:generateContent?key=sk-anything' \ +-H 'Content-Type: application/json' \ +-H 'tags: gemini-js-sdk,pass-through-endpoint' \ +-d '{ + "contents": [{ + "parts":[{ + "text": "The quick brown fox jumps over the lazy dog." + }] + }] +}' +``` + + + + +```javascript +const { GoogleGenerativeAI } = require("@google/generative-ai"); + +const modelParams = { + model: 'gemini-pro', +}; + +const requestOptions = { + baseUrl: 'http://localhost:4000/gemini', // http:///gemini + customHeaders: { + "tags": "gemini-js-sdk,pass-through-endpoint" + } +}; + +const genAI = new GoogleGenerativeAI("sk-1234"); +const model = genAI.getGenerativeModel(modelParams, requestOptions); + +async function main() { + try { + const result = await model.generateContent("Explain how AI works"); + console.log(result.response.text()); + } catch (error) { + console.error('Error:', error); + } +} + +main(); +``` + + + diff --git a/docs/my-website/docs/pass_through/vertex_ai.md b/docs/my-website/docs/pass_through/vertex_ai.md index 07b0beb75..601f89f4b 100644 --- a/docs/my-website/docs/pass_through/vertex_ai.md +++ b/docs/my-website/docs/pass_through/vertex_ai.md @@ -4,13 +4,108 @@ import TabItem from '@theme/TabItem'; # Vertex AI SDK -Use VertexAI SDK to call endpoints on LiteLLM Gateway (native provider format) +Pass-through endpoints for Vertex AI - call provider-specific endpoint, in native format (no translation). -:::tip +Just replace `https://REGION-aiplatform.googleapis.com` with `LITELLM_PROXY_BASE_URL/vertex_ai` + + +#### **Example Usage** + + + + +```bash +curl http://localhost:4000/vertex_ai/publishers/google/models/gemini-1.0-pro:generateContent \ + -H "Content-Type: application/json" \ + -H "x-litellm-api-key: Bearer sk-1234" \ + -d '{ + "contents":[{ + "role": "user", + "parts":[{"text": "How are you doing today?"}] + }] + }' +``` + + + + +```javascript +const { VertexAI } = require('@google-cloud/vertexai'); + +const vertexAI = new VertexAI({ + project: 'your-project-id', // enter your vertex project id + location: 'us-central1', // enter your vertex region + apiEndpoint: "localhost:4000/vertex_ai" // /vertex_ai # note, do not include 'https://' in the url +}); + +const model = vertexAI.getGenerativeModel({ + model: 'gemini-1.0-pro' +}, { + customHeaders: { + "x-litellm-api-key": "sk-1234" // Your litellm Virtual Key + } +}); + +async function generateContent() { + try { + const prompt = { + contents: [{ + role: 'user', + parts: [{ text: 'How are you doing today?' }] + }] + }; + + const response = await model.generateContent(prompt); + console.log('Response:', response); + } catch (error) { + console.error('Error:', error); + } +} + +generateContent(); +``` + + + + + +## Quick Start + +Let's call the Vertex AI [`/generateContent` endpoint](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference) + +1. Add Vertex AI Credentials to your environment + +```bash +export DEFAULT_VERTEXAI_PROJECT="" # "adroit-crow-413218" +export DEFAULT_VERTEXAI_LOCATION="" # "us-central1" +export DEFAULT_GOOGLE_APPLICATION_CREDENTIALS="" # "/Users/Downloads/adroit-crow-413218-a956eef1a2a8.json" +``` + +2. Start LiteLLM Proxy + +```bash +litellm + +# RUNNING on http://0.0.0.0:4000 +``` + +3. Test it! + +Let's call the Google AI Studio token counting endpoint + +```bash +curl http://localhost:4000/vertex-ai/publishers/google/models/gemini-1.0-pro:generateContent \ + -H "Content-Type: application/json" \ + -H "Authorization: Bearer sk-1234" \ + -d '{ + "contents":[{ + "role": "user", + "parts":[{"text": "How are you doing today?"}] + }] + }' +``` -Looking for the Unified API (OpenAI format) for VertexAI ? [Go here - using vertexAI with LiteLLM SDK or LiteLLM Proxy Server](../providers/vertex.md) -::: ## Supported API Endpoints @@ -22,7 +117,7 @@ Looking for the Unified API (OpenAI format) for VertexAI ? [Go here - using vert - Tuning API - CountTokens API -## Authentication to Vertex AI +#### Authentication to Vertex AI LiteLLM Proxy Server supports two methods of authentication to Vertex AI: @@ -30,715 +125,60 @@ LiteLLM Proxy Server supports two methods of authentication to Vertex AI: 2. Set Vertex AI credentials on proxy server -## Quick Start Usage - - - - - -#### 1. Start litellm proxy - -```shell -litellm --config /path/to/config.yaml -``` - -#### 2. Test it - -```python -import vertexai -from vertexai.preview.generative_models import GenerativeModel - -LITE_LLM_ENDPOINT = "http://localhost:4000" - -vertexai.init( - project="", # enter your project id - location="", # enter your region - api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex-ai", # route on litellm - api_transport="rest", -) - -model = GenerativeModel(model_name="gemini-1.0-pro") -model.generate_content("hi") - -``` - - - - - - -#### 1. Set `default_vertex_config` on your `config.yaml` - - -Add the following credentials to your litellm config.yaml to use the Vertex AI endpoints. - -```yaml -default_vertex_config: - vertex_project: "adroit-crow-413218" - vertex_location: "us-central1" - vertex_credentials: "/Users/ishaanjaffer/Downloads/adroit-crow-413218-a956eef1a2a8.json" # Add path to service account.json -``` - -#### 2. Start litellm proxy - -```shell -litellm --config /path/to/config.yaml -``` - -#### 3. Test it - -```python -import vertexai -from google.auth.credentials import Credentials -from vertexai.generative_models import GenerativeModel - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - - -class CredentialsWrapper(Credentials): - def __init__(self, token=None): - super().__init__() - self.token = token - self.expiry = None # or set to a future date if needed - - def refresh(self, request): - pass - - def apply(self, headers, token=None): - headers["Authorization"] = f"Bearer {self.token}" - - @property - def expired(self): - return False # Always consider the token as non-expired - - @property - def valid(self): - return True # Always consider the credentials as valid - - -credentials = CredentialsWrapper(token=LITELLM_PROXY_API_KEY) - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - credentials=credentials, - api_transport="rest", -) - -model = GenerativeModel("gemini-1.5-flash-001") - -response = model.generate_content( - "What's a good name for a flower shop that specializes in selling bouquets of dried flowers?" -) - -print(response.text) -``` - - - - ## Usage Examples ### Gemini API (Generate Content) - - -```python -import vertexai -from vertexai.generative_models import GenerativeModel - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - api_transport="rest", - -) - -model = GenerativeModel("gemini-1.5-flash-001") - -response = model.generate_content( - "What's a good name for a flower shop that specializes in selling bouquets of dried flowers?" -) - -print(response.text) -``` - - - - -```python -import vertexai -from google.auth.credentials import Credentials -from vertexai.generative_models import GenerativeModel - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - - -class CredentialsWrapper(Credentials): - def __init__(self, token=None): - super().__init__() - self.token = token - self.expiry = None # or set to a future date if needed - - def refresh(self, request): - pass - - def apply(self, headers, token=None): - headers["Authorization"] = f"Bearer {self.token}" - - @property - def expired(self): - return False # Always consider the token as non-expired - - @property - def valid(self): - return True # Always consider the credentials as valid - - -credentials = CredentialsWrapper(token=LITELLM_PROXY_API_KEY) - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - credentials=credentials, - api_transport="rest", - -) - -model = GenerativeModel("gemini-1.5-flash-001") - -response = model.generate_content( - "What's a good name for a flower shop that specializes in selling bouquets of dried flowers?" -) - -print(response.text) -``` - - - ```shell -curl http://localhost:4000/vertex-ai/publishers/google/models/gemini-1.5-flash-001:generateContent \ +curl http://localhost:4000/vertex_ai/publishers/google/models/gemini-1.5-flash-001:generateContent \ -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ + -H "x-litellm-api-key: Bearer sk-1234" \ -d '{"contents":[{"role": "user", "parts":[{"text": "hi"}]}]}' ``` - - ### Embeddings API - - - - -```python -from typing import List, Optional -from vertexai.language_models import TextEmbeddingInput, TextEmbeddingModel -import vertexai -from vertexai.generative_models import GenerativeModel - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - api_transport="rest", -) - - -def embed_text( - texts: List[str] = ["banana muffins? ", "banana bread? banana muffins?"], - task: str = "RETRIEVAL_DOCUMENT", - model_name: str = "text-embedding-004", - dimensionality: Optional[int] = 256, -) -> List[List[float]]: - """Embeds texts with a pre-trained, foundational model.""" - model = TextEmbeddingModel.from_pretrained(model_name) - inputs = [TextEmbeddingInput(text, task) for text in texts] - kwargs = dict(output_dimensionality=dimensionality) if dimensionality else {} - embeddings = model.get_embeddings(inputs, **kwargs) - return [embedding.values for embedding in embeddings] -``` - - - - - -```python -from typing import List, Optional -from vertexai.language_models import TextEmbeddingInput, TextEmbeddingModel -import vertexai -from google.auth.credentials import Credentials -from vertexai.generative_models import GenerativeModel - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - - -class CredentialsWrapper(Credentials): - def __init__(self, token=None): - super().__init__() - self.token = token - self.expiry = None # or set to a future date if needed - - def refresh(self, request): - pass - - def apply(self, headers, token=None): - headers["Authorization"] = f"Bearer {self.token}" - - @property - def expired(self): - return False # Always consider the token as non-expired - - @property - def valid(self): - return True # Always consider the credentials as valid - - -credentials = CredentialsWrapper(token=LITELLM_PROXY_API_KEY) - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - credentials=credentials, - api_transport="rest", -) - - -def embed_text( - texts: List[str] = ["banana muffins? ", "banana bread? banana muffins?"], - task: str = "RETRIEVAL_DOCUMENT", - model_name: str = "text-embedding-004", - dimensionality: Optional[int] = 256, -) -> List[List[float]]: - """Embeds texts with a pre-trained, foundational model.""" - model = TextEmbeddingModel.from_pretrained(model_name) - inputs = [TextEmbeddingInput(text, task) for text in texts] - kwargs = dict(output_dimensionality=dimensionality) if dimensionality else {} - embeddings = model.get_embeddings(inputs, **kwargs) - return [embedding.values for embedding in embeddings] -``` - - - ```shell -curl http://localhost:4000/vertex-ai/publishers/google/models/textembedding-gecko@001:predict \ +curl http://localhost:4000/vertex_ai/publishers/google/models/textembedding-gecko@001:predict \ -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ + -H "x-litellm-api-key: Bearer sk-1234" \ -d '{"instances":[{"content": "gm"}]}' ``` - - - ### Imagen API - - - - - -```python -from typing import List, Optional -from vertexai.preview.vision_models import ImageGenerationModel -import vertexai -from google.auth.credentials import Credentials - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - api_transport="rest", -) - -model = ImageGenerationModel.from_pretrained("imagen-3.0-generate-001") - -images = model.generate_images( - prompt=prompt, - # Optional parameters - number_of_images=1, - language="en", - # You can't use a seed value and watermark at the same time. - # add_watermark=False, - # seed=100, - aspect_ratio="1:1", - safety_filter_level="block_some", - person_generation="allow_adult", -) - -images[0].save(location=output_file, include_generation_parameters=False) - -# Optional. View the generated image in a notebook. -# images[0].show() - -print(f"Created output image using {len(images[0]._image_bytes)} bytes") - -``` - - - - -```python -from typing import List, Optional -from vertexai.preview.vision_models import ImageGenerationModel -import vertexai -from google.auth.credentials import Credentials - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - - -class CredentialsWrapper(Credentials): - def __init__(self, token=None): - super().__init__() - self.token = token - self.expiry = None # or set to a future date if needed - - def refresh(self, request): - pass - - def apply(self, headers, token=None): - headers["Authorization"] = f"Bearer {self.token}" - - @property - def expired(self): - return False # Always consider the token as non-expired - - @property - def valid(self): - return True # Always consider the credentials as valid - - -credentials = CredentialsWrapper(token=LITELLM_PROXY_API_KEY) - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - credentials=credentials, - api_transport="rest", -) - -model = ImageGenerationModel.from_pretrained("imagen-3.0-generate-001") - -images = model.generate_images( - prompt=prompt, - # Optional parameters - number_of_images=1, - language="en", - # You can't use a seed value and watermark at the same time. - # add_watermark=False, - # seed=100, - aspect_ratio="1:1", - safety_filter_level="block_some", - person_generation="allow_adult", -) - -images[0].save(location=output_file, include_generation_parameters=False) - -# Optional. View the generated image in a notebook. -# images[0].show() - -print(f"Created output image using {len(images[0]._image_bytes)} bytes") - -``` - - - - - ```shell -curl http://localhost:4000/vertex-ai/publishers/google/models/imagen-3.0-generate-001:predict \ +curl http://localhost:4000/vertex_ai/publishers/google/models/imagen-3.0-generate-001:predict \ -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ + -H "x-litellm-api-key: Bearer sk-1234" \ -d '{"instances":[{"prompt": "make an otter"}], "parameters": {"sampleCount": 1}}' ``` - - - ### Count Tokens API - - - - - - -```python -from typing import List, Optional -from vertexai.generative_models import GenerativeModel -import vertexai - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - api_transport="rest", -) - - -model = GenerativeModel("gemini-1.5-flash-001") - -prompt = "Why is the sky blue?" - -# Prompt tokens count -response = model.count_tokens(prompt) -print(f"Prompt Token Count: {response.total_tokens}") -print(f"Prompt Character Count: {response.total_billable_characters}") - -# Send text to Gemini -response = model.generate_content(prompt) - -# Response tokens count -usage_metadata = response.usage_metadata -print(f"Prompt Token Count: {usage_metadata.prompt_token_count}") -print(f"Candidates Token Count: {usage_metadata.candidates_token_count}") -print(f"Total Token Count: {usage_metadata.total_token_count}") -``` - - - - - - -```python -from typing import List, Optional -from vertexai.generative_models import GenerativeModel -import vertexai -from google.auth.credentials import Credentials - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - - -class CredentialsWrapper(Credentials): - def __init__(self, token=None): - super().__init__() - self.token = token - self.expiry = None # or set to a future date if needed - - def refresh(self, request): - pass - - def apply(self, headers, token=None): - headers["Authorization"] = f"Bearer {self.token}" - - @property - def expired(self): - return False # Always consider the token as non-expired - - @property - def valid(self): - return True # Always consider the credentials as valid - - -credentials = CredentialsWrapper(token=LITELLM_PROXY_API_KEY) - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - credentials=credentials, - api_transport="rest", -) - - -model = GenerativeModel("gemini-1.5-flash-001") - -prompt = "Why is the sky blue?" - -# Prompt tokens count -response = model.count_tokens(prompt) -print(f"Prompt Token Count: {response.total_tokens}") -print(f"Prompt Character Count: {response.total_billable_characters}") - -# Send text to Gemini -response = model.generate_content(prompt) - -# Response tokens count -usage_metadata = response.usage_metadata -print(f"Prompt Token Count: {usage_metadata.prompt_token_count}") -print(f"Candidates Token Count: {usage_metadata.candidates_token_count}") -print(f"Total Token Count: {usage_metadata.total_token_count}") -``` - - - - - - - ```shell -curl http://localhost:4000/vertex-ai/publishers/google/models/gemini-1.5-flash-001:countTokens \ +curl http://localhost:4000/vertex_ai/publishers/google/models/gemini-1.5-flash-001:countTokens \ -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ + -H "x-litellm-api-key: Bearer sk-1234" \ -d '{"contents":[{"role": "user", "parts":[{"text": "hi"}]}]}' ``` - - - - ### Tuning API Create Fine Tuning Job - - - - -```python -from typing import List, Optional -from vertexai.preview.tuning import sft -import vertexai - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - api_transport="rest", -) - - -# TODO(developer): Update project -vertexai.init(project=PROJECT_ID, location="us-central1") - -sft_tuning_job = sft.train( - source_model="gemini-1.0-pro-002", - train_dataset="gs://cloud-samples-data/ai-platform/generative_ai/sft_train_data.jsonl", -) - -# Polling for job completion -while not sft_tuning_job.has_ended: - time.sleep(60) - sft_tuning_job.refresh() - -print(sft_tuning_job.tuned_model_name) -print(sft_tuning_job.tuned_model_endpoint_name) -print(sft_tuning_job.experiment) - -``` - - - - - -```python -from typing import List, Optional -from vertexai.preview.tuning import sft -import vertexai -from google.auth.credentials import Credentials - -LITELLM_PROXY_API_KEY = "sk-1234" -LITELLM_PROXY_BASE = "http://0.0.0.0:4000/vertex-ai" - -import datetime - - -class CredentialsWrapper(Credentials): - def __init__(self, token=None): - super().__init__() - self.token = token - self.expiry = None # or set to a future date if needed - - def refresh(self, request): - pass - - def apply(self, headers, token=None): - headers["Authorization"] = f"Bearer {self.token}" - - @property - def expired(self): - return False # Always consider the token as non-expired - - @property - def valid(self): - return True # Always consider the credentials as valid - - -credentials = CredentialsWrapper(token=LITELLM_PROXY_API_KEY) - -vertexai.init( - project="adroit-crow-413218", - location="us-central1", - api_endpoint=LITELLM_PROXY_BASE, - credentials=credentials, - api_transport="rest", -) - - -# TODO(developer): Update project -vertexai.init(project=PROJECT_ID, location="us-central1") - -sft_tuning_job = sft.train( - source_model="gemini-1.0-pro-002", - train_dataset="gs://cloud-samples-data/ai-platform/generative_ai/sft_train_data.jsonl", -) - -# Polling for job completion -while not sft_tuning_job.has_ended: - time.sleep(60) - sft_tuning_job.refresh() - -print(sft_tuning_job.tuned_model_name) -print(sft_tuning_job.tuned_model_endpoint_name) -print(sft_tuning_job.experiment) -``` - - - - ```shell -curl http://localhost:4000/vertex-ai/tuningJobs \ +curl http://localhost:4000/vertex_ai/tuningJobs \ -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ + -H "x-litellm-api-key: Bearer sk-1234" \ -d '{ "baseModel": "gemini-1.0-pro-002", "supervisedTuningSpec" : { @@ -747,112 +187,130 @@ curl http://localhost:4000/vertex-ai/tuningJobs \ }' ``` - +## Advanced - +Pre-requisites +- [Setup proxy with DB](../proxy/virtual_keys.md#setup) + +Use this, to avoid giving developers the raw Anthropic API key, but still letting them use Anthropic endpoints. + +### Use with Virtual Keys + +1. Setup environment + +```bash +export DATABASE_URL="" +export LITELLM_MASTER_KEY="" + +# vertex ai credentials +export DEFAULT_VERTEXAI_PROJECT="" # "adroit-crow-413218" +export DEFAULT_VERTEXAI_LOCATION="" # "us-central1" +export DEFAULT_GOOGLE_APPLICATION_CREDENTIALS="" # "/Users/Downloads/adroit-crow-413218-a956eef1a2a8.json" +``` + +```bash +litellm + +# RUNNING on http://0.0.0.0:4000 +``` + +2. Generate virtual key + +```bash +curl -X POST 'http://0.0.0.0:4000/key/generate' \ +-H 'x-litellm-api-key: Bearer sk-1234' \ +-H 'Content-Type: application/json' \ +-d '{}' +``` + +Expected Response + +```bash +{ + ... + "key": "sk-1234ewknldferwedojwojw" +} +``` + +3. Test it! -### Context Caching +```bash +curl http://localhost:4000/vertex_ai/publishers/google/models/gemini-1.0-pro:generateContent \ + -H "Content-Type: application/json" \ + -H "x-litellm-api-key: Bearer sk-1234" \ + -d '{ + "contents":[{ + "role": "user", + "parts":[{"text": "How are you doing today?"}] + }] + }' +``` -Use Vertex AI Context Caching +### Send `tags` in request headers -[**Relevant VertexAI Docs**](https://cloud.google.com/vertex-ai/generative-ai/docs/context-cache/context-cache-overview) +Use this if you wants `tags` to be tracked in the LiteLLM DB and on logging callbacks + +Pass `tags` in request headers as a comma separated list. In the example below the following tags will be tracked + +``` +tags: ["vertex-js-sdk", "pass-through-endpoint"] +``` + - - -1. Add model to config.yaml -```yaml -model_list: - # used for /chat/completions, /completions, /embeddings endpoints - - model_name: gemini-1.5-pro-001 - litellm_params: - model: vertex_ai/gemini-1.5-pro-001 - vertex_project: "project-id" - vertex_location: "us-central1" - vertex_credentials: "adroit-crow-413218-a956eef1a2a8.json" # Add path to service account.json - -# used for the /cachedContent and vertexAI native endpoints -default_vertex_config: - vertex_project: "adroit-crow-413218" - vertex_location: "us-central1" - vertex_credentials: "adroit-crow-413218-a956eef1a2a8.json" # Add path to service account.json - +```bash +curl http://localhost:4000/vertex-ai/publishers/google/models/gemini-1.0-pro:generateContent \ + -H "Content-Type: application/json" \ + -H "x-litellm-api-key: Bearer sk-1234" \ + -H "tags: vertex-js-sdk,pass-through-endpoint" \ + -d '{ + "contents":[{ + "role": "user", + "parts":[{"text": "How are you doing today?"}] + }] + }' ``` -2. Start Proxy + + -``` -$ litellm --config /path/to/config.yaml -``` +```javascript +const { VertexAI } = require('@google-cloud/vertexai'); -3. Make Request! -We make the request in two steps: -- Create a cachedContents object -- Use the cachedContents object in your /chat/completions +const vertexAI = new VertexAI({ + project: 'your-project-id', // enter your vertex project id + location: 'us-central1', // enter your vertex region + apiEndpoint: "localhost:4000/vertex_ai" // /vertex_ai # note, do not include 'https://' in the url +}); -**Create a cachedContents object** - -First, create a cachedContents object by calling the Vertex `cachedContents` endpoint. The LiteLLM proxy forwards the `/cachedContents` request to the VertexAI API. - -```python -import httpx - -# Set Litellm proxy variables -LITELLM_BASE_URL = "http://0.0.0.0:4000" -LITELLM_PROXY_API_KEY = "sk-1234" - -httpx_client = httpx.Client(timeout=30) - -print("Creating cached content") -create_cache = httpx_client.post( - url=f"{LITELLM_BASE_URL}/vertex-ai/cachedContents", - headers={"Authorization": f"Bearer {LITELLM_PROXY_API_KEY}"}, - json={ - "model": "gemini-1.5-pro-001", - "contents": [ - { - "role": "user", - "parts": [{ - "text": "This is sample text to demonstrate explicit caching." * 4000 - }] - } - ], +const model = vertexAI.getGenerativeModel({ + model: 'gemini-1.0-pro' +}, { + customHeaders: { + "x-litellm-api-key": "sk-1234", // Your litellm Virtual Key + "tags": "vertex-js-sdk,pass-through-endpoint" } -) +}); -print("Response from create_cache:", create_cache) -create_cache_response = create_cache.json() -print("JSON from create_cache:", create_cache_response) -cached_content_name = create_cache_response["name"] -``` +async function generateContent() { + try { + const prompt = { + contents: [{ + role: 'user', + parts: [{ text: 'How are you doing today?' }] + }] + }; -**Use the cachedContents object in your /chat/completions request to VertexAI** + const response = await model.generateContent(prompt); + console.log('Response:', response); + } catch (error) { + console.error('Error:', error); + } +} -```python -import openai - -# Set Litellm proxy variables -LITELLM_BASE_URL = "http://0.0.0.0:4000" -LITELLM_PROXY_API_KEY = "sk-1234" - -client = openai.OpenAI(api_key=LITELLM_PROXY_API_KEY, base_url=LITELLM_BASE_URL) - -response = client.chat.completions.create( - model="gemini-1.5-pro-001", - max_tokens=8192, - messages=[ - { - "role": "user", - "content": "What is the sample text about?", - }, - ], - temperature=0.7, - extra_body={"cached_content": cached_content_name}, # Use the cached content -) - -print("Response from proxy:", response) +generateContent(); ``` diff --git a/docs/my-website/docs/proxy/config_management.md b/docs/my-website/docs/proxy/config_management.md new file mode 100644 index 000000000..4f7c5775b --- /dev/null +++ b/docs/my-website/docs/proxy/config_management.md @@ -0,0 +1,59 @@ +# File Management + +## `include` external YAML files in a config.yaml + +You can use `include` to include external YAML files in a config.yaml. + +**Quick Start Usage:** + +To include a config file, use `include` with either a single file or a list of files. + +Contents of `parent_config.yaml`: +```yaml +include: + - model_config.yaml # 👈 Key change, will include the contents of model_config.yaml + +litellm_settings: + callbacks: ["prometheus"] +``` + + +Contents of `model_config.yaml`: +```yaml +model_list: + - model_name: gpt-4o + litellm_params: + model: openai/gpt-4o + api_base: https://exampleopenaiendpoint-production.up.railway.app/ + - model_name: fake-anthropic-endpoint + litellm_params: + model: anthropic/fake + api_base: https://exampleanthropicendpoint-production.up.railway.app/ + +``` + +Start proxy server + +This will start the proxy server with config `parent_config.yaml`. Since the `include` directive is used, the server will also include the contents of `model_config.yaml`. +``` +litellm --config parent_config.yaml --detailed_debug +``` + + + + + +## Examples using `include` + +Include a single file: +```yaml +include: + - model_config.yaml +``` + +Include multiple files: +```yaml +include: + - model_config.yaml + - another_config.yaml +``` \ No newline at end of file diff --git a/docs/my-website/docs/proxy/config_settings.md b/docs/my-website/docs/proxy/config_settings.md new file mode 100644 index 000000000..c762a0716 --- /dev/null +++ b/docs/my-website/docs/proxy/config_settings.md @@ -0,0 +1,507 @@ +# All settings + + +```yaml +environment_variables: {} + +model_list: + - model_name: string + litellm_params: {} + model_info: + id: string + mode: embedding + input_cost_per_token: 0 + output_cost_per_token: 0 + max_tokens: 2048 + base_model: gpt-4-1106-preview + additionalProp1: {} + +litellm_settings: + # Logging/Callback settings + success_callback: ["langfuse"] # list of success callbacks + failure_callback: ["sentry"] # list of failure callbacks + callbacks: ["otel"] # list of callbacks - runs on success and failure + service_callbacks: ["datadog", "prometheus"] # logs redis, postgres failures on datadog, prometheus + turn_off_message_logging: boolean # prevent the messages and responses from being logged to on your callbacks, but request metadata will still be logged. + redact_user_api_key_info: boolean # Redact information about the user api key (hashed token, user_id, team id, etc.), from logs. Currently supported for Langfuse, OpenTelemetry, Logfire, ArizeAI logging. + langfuse_default_tags: ["cache_hit", "cache_key", "proxy_base_url", "user_api_key_alias", "user_api_key_user_id", "user_api_key_user_email", "user_api_key_team_alias", "semantic-similarity", "proxy_base_url"] # default tags for Langfuse Logging + + # Networking settings + request_timeout: 10 # (int) llm requesttimeout in seconds. Raise Timeout error if call takes longer than 10s. Sets litellm.request_timeout + force_ipv4: boolean # If true, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6 + Anthropic API + + set_verbose: boolean # sets litellm.set_verbose=True to view verbose debug logs. DO NOT LEAVE THIS ON IN PRODUCTION + json_logs: boolean # if true, logs will be in json format + + # Fallbacks, reliability + default_fallbacks: ["claude-opus"] # set default_fallbacks, in case a specific model group is misconfigured / bad. + content_policy_fallbacks: [{"gpt-3.5-turbo-small": ["claude-opus"]}] # fallbacks for ContentPolicyErrors + context_window_fallbacks: [{"gpt-3.5-turbo-small": ["gpt-3.5-turbo-large", "claude-opus"]}] # fallbacks for ContextWindowExceededErrors + + + + # Caching settings + cache: true + cache_params: # set cache params for redis + type: redis # type of cache to initialize + + # Optional - Redis Settings + host: "localhost" # The host address for the Redis cache. Required if type is "redis". + port: 6379 # The port number for the Redis cache. Required if type is "redis". + password: "your_password" # The password for the Redis cache. Required if type is "redis". + namespace: "litellm.caching.caching" # namespace for redis cache + + # Optional - Redis Cluster Settings + redis_startup_nodes: [{"host": "127.0.0.1", "port": "7001"}] + + # Optional - Redis Sentinel Settings + service_name: "mymaster" + sentinel_nodes: [["localhost", 26379]] + + # Optional - Qdrant Semantic Cache Settings + qdrant_semantic_cache_embedding_model: openai-embedding # the model should be defined on the model_list + qdrant_collection_name: test_collection + qdrant_quantization_config: binary + similarity_threshold: 0.8 # similarity threshold for semantic cache + + # Optional - S3 Cache Settings + s3_bucket_name: cache-bucket-litellm # AWS Bucket Name for S3 + s3_region_name: us-west-2 # AWS Region Name for S3 + s3_aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID # us os.environ/ to pass environment variables. This is AWS Access Key ID for S3 + s3_aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY # AWS Secret Access Key for S3 + s3_endpoint_url: https://s3.amazonaws.com # [OPTIONAL] S3 endpoint URL, if you want to use Backblaze/cloudflare s3 bucket + + # Common Cache settings + # Optional - Supported call types for caching + supported_call_types: ["acompletion", "atext_completion", "aembedding", "atranscription"] + # /chat/completions, /completions, /embeddings, /audio/transcriptions + mode: default_off # if default_off, you need to opt in to caching on a per call basis + ttl: 600 # ttl for caching + + +callback_settings: + otel: + message_logging: boolean # OTEL logging callback specific settings + +general_settings: + completion_model: string + disable_spend_logs: boolean # turn off writing each transaction to the db + disable_master_key_return: boolean # turn off returning master key on UI (checked on '/user/info' endpoint) + disable_retry_on_max_parallel_request_limit_error: boolean # turn off retries when max parallel request limit is reached + disable_reset_budget: boolean # turn off reset budget scheduled task + disable_adding_master_key_hash_to_db: boolean # turn off storing master key hash in db, for spend tracking + enable_jwt_auth: boolean # allow proxy admin to auth in via jwt tokens with 'litellm_proxy_admin' in claims + enforce_user_param: boolean # requires all openai endpoint requests to have a 'user' param + allowed_routes: ["route1", "route2"] # list of allowed proxy API routes - a user can access. (currently JWT-Auth only) + key_management_system: google_kms # either google_kms or azure_kms + master_key: string + + # Database Settings + database_url: string + database_connection_pool_limit: 0 # default 100 + database_connection_timeout: 0 # default 60s + allow_requests_on_db_unavailable: boolean # if true, will allow requests that can not connect to the DB to verify Virtual Key to still work + + custom_auth: string + max_parallel_requests: 0 # the max parallel requests allowed per deployment + global_max_parallel_requests: 0 # the max parallel requests allowed on the proxy all up + infer_model_from_keys: true + background_health_checks: true + health_check_interval: 300 + alerting: ["slack", "email"] + alerting_threshold: 0 + use_client_credentials_pass_through_routes: boolean # use client credentials for all pass through routes like "/vertex-ai", /bedrock/. When this is True Virtual Key auth will not be applied on these endpoints +``` + +### litellm_settings - Reference + +| Name | Type | Description | +|------|------|-------------| +| success_callback | array of strings | List of success callbacks. [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | +| failure_callback | array of strings | List of failure callbacks [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | +| callbacks | array of strings | List of callbacks - runs on success and failure [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | +| service_callbacks | array of strings | System health monitoring - Logs redis, postgres failures on specified services (e.g. datadog, prometheus) [Doc Metrics](prometheus) | +| turn_off_message_logging | boolean | If true, prevents messages and responses from being logged to callbacks, but request metadata will still be logged [Proxy Logging](logging) | +| modify_params | boolean | If true, allows modifying the parameters of the request before it is sent to the LLM provider | +| enable_preview_features | boolean | If true, enables preview features - e.g. Azure O1 Models with streaming support.| +| redact_user_api_key_info | boolean | If true, redacts information about the user api key from logs [Proxy Logging](logging#redacting-userapikeyinfo) | +| langfuse_default_tags | array of strings | Default tags for Langfuse Logging. Use this if you want to control which LiteLLM-specific fields are logged as tags by the LiteLLM proxy. By default LiteLLM Proxy logs no LiteLLM-specific fields as tags. [Further docs](./logging#litellm-specific-tags-on-langfuse---cache_hit-cache_key) | +| set_verbose | boolean | If true, sets litellm.set_verbose=True to view verbose debug logs. DO NOT LEAVE THIS ON IN PRODUCTION | +| json_logs | boolean | If true, logs will be in json format. If you need to store the logs as JSON, just set the `litellm.json_logs = True`. We currently just log the raw POST request from litellm as a JSON [Further docs](./debugging) | +| default_fallbacks | array of strings | List of fallback models to use if a specific model group is misconfigured / bad. [Further docs](./reliability#default-fallbacks) | +| request_timeout | integer | The timeout for requests in seconds. If not set, the default value is `6000 seconds`. [For reference OpenAI Python SDK defaults to `600 seconds`.](https://github.com/openai/openai-python/blob/main/src/openai/_constants.py) | +| force_ipv4 | boolean | If true, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6 + Anthropic API | +| content_policy_fallbacks | array of objects | Fallbacks to use when a ContentPolicyViolationError is encountered. [Further docs](./reliability#content-policy-fallbacks) | +| context_window_fallbacks | array of objects | Fallbacks to use when a ContextWindowExceededError is encountered. [Further docs](./reliability#context-window-fallbacks) | +| cache | boolean | If true, enables caching. [Further docs](./caching) | +| cache_params | object | Parameters for the cache. [Further docs](./caching) | +| cache_params.type | string | The type of cache to initialize. Can be one of ["local", "redis", "redis-semantic", "s3", "disk", "qdrant-semantic"]. Defaults to "redis". [Furher docs](./caching) | +| cache_params.host | string | The host address for the Redis cache. Required if type is "redis". | +| cache_params.port | integer | The port number for the Redis cache. Required if type is "redis". | +| cache_params.password | string | The password for the Redis cache. Required if type is "redis". | +| cache_params.namespace | string | The namespace for the Redis cache. | +| cache_params.redis_startup_nodes | array of objects | Redis Cluster Settings. [Further docs](./caching) | +| cache_params.service_name | string | Redis Sentinel Settings. [Further docs](./caching) | +| cache_params.sentinel_nodes | array of arrays | Redis Sentinel Settings. [Further docs](./caching) | +| cache_params.ttl | integer | The time (in seconds) to store entries in cache. | +| cache_params.qdrant_semantic_cache_embedding_model | string | The embedding model to use for qdrant semantic cache. | +| cache_params.qdrant_collection_name | string | The name of the collection to use for qdrant semantic cache. | +| cache_params.qdrant_quantization_config | string | The quantization configuration for the qdrant semantic cache. | +| cache_params.similarity_threshold | float | The similarity threshold for the semantic cache. | +| cache_params.s3_bucket_name | string | The name of the S3 bucket to use for the semantic cache. | +| cache_params.s3_region_name | string | The region name for the S3 bucket. | +| cache_params.s3_aws_access_key_id | string | The AWS access key ID for the S3 bucket. | +| cache_params.s3_aws_secret_access_key | string | The AWS secret access key for the S3 bucket. | +| cache_params.s3_endpoint_url | string | Optional - The endpoint URL for the S3 bucket. | +| cache_params.supported_call_types | array of strings | The types of calls to cache. [Further docs](./caching) | +| cache_params.mode | string | The mode of the cache. [Further docs](./caching) | +| disable_end_user_cost_tracking | boolean | If true, turns off end user cost tracking on prometheus metrics + litellm spend logs table on proxy. | +| key_generation_settings | object | Restricts who can generate keys. [Further docs](./virtual_keys.md#restricting-key-generation) | + +### general_settings - Reference + +| Name | Type | Description | +|------|------|-------------| +| completion_model | string | The default model to use for completions when `model` is not specified in the request | +| disable_spend_logs | boolean | If true, turns off writing each transaction to the database | +| disable_master_key_return | boolean | If true, turns off returning master key on UI. (checked on '/user/info' endpoint) | +| disable_retry_on_max_parallel_request_limit_error | boolean | If true, turns off retries when max parallel request limit is reached | +| disable_reset_budget | boolean | If true, turns off reset budget scheduled task | +| disable_adding_master_key_hash_to_db | boolean | If true, turns off storing master key hash in db | +| enable_jwt_auth | boolean | allow proxy admin to auth in via jwt tokens with 'litellm_proxy_admin' in claims. [Doc on JWT Tokens](token_auth) | +| enforce_user_param | boolean | If true, requires all OpenAI endpoint requests to have a 'user' param. [Doc on call hooks](call_hooks)| +| allowed_routes | array of strings | List of allowed proxy API routes a user can access [Doc on controlling allowed routes](enterprise#control-available-public-private-routes)| +| key_management_system | string | Specifies the key management system. [Doc Secret Managers](../secret) | +| master_key | string | The master key for the proxy [Set up Virtual Keys](virtual_keys) | +| database_url | string | The URL for the database connection [Set up Virtual Keys](virtual_keys) | +| database_connection_pool_limit | integer | The limit for database connection pool [Setting DB Connection Pool limit](#configure-db-pool-limits--connection-timeouts) | +| database_connection_timeout | integer | The timeout for database connections in seconds [Setting DB Connection Pool limit, timeout](#configure-db-pool-limits--connection-timeouts) | +| allow_requests_on_db_unavailable | boolean | If true, allows requests to succeed even if DB is unreachable. **Only use this if running LiteLLM in your VPC** This will allow requests to work even when LiteLLM cannot connect to the DB to verify a Virtual Key | +| custom_auth | string | Write your own custom authentication logic [Doc Custom Auth](virtual_keys#custom-auth) | +| max_parallel_requests | integer | The max parallel requests allowed per deployment | +| global_max_parallel_requests | integer | The max parallel requests allowed on the proxy overall | +| infer_model_from_keys | boolean | If true, infers the model from the provided keys | +| background_health_checks | boolean | If true, enables background health checks. [Doc on health checks](health) | +| health_check_interval | integer | The interval for health checks in seconds [Doc on health checks](health) | +| alerting | array of strings | List of alerting methods [Doc on Slack Alerting](alerting) | +| alerting_threshold | integer | The threshold for triggering alerts [Doc on Slack Alerting](alerting) | +| use_client_credentials_pass_through_routes | boolean | If true, uses client credentials for all pass-through routes. [Doc on pass through routes](pass_through) | +| health_check_details | boolean | If false, hides health check details (e.g. remaining rate limit). [Doc on health checks](health) | +| public_routes | List[str] | (Enterprise Feature) Control list of public routes | +| alert_types | List[str] | Control list of alert types to send to slack (Doc on alert types)[./alerting.md] | +| enforced_params | List[str] | (Enterprise Feature) List of params that must be included in all requests to the proxy | +| enable_oauth2_auth | boolean | (Enterprise Feature) If true, enables oauth2.0 authentication | +| use_x_forwarded_for | str | If true, uses the X-Forwarded-For header to get the client IP address | +| service_account_settings | List[Dict[str, Any]] | Set `service_account_settings` if you want to create settings that only apply to service account keys (Doc on service accounts)[./service_accounts.md] | +| image_generation_model | str | The default model to use for image generation - ignores model set in request | +| store_model_in_db | boolean | If true, allows `/model/new` endpoint to store model information in db. Endpoint disabled by default. [Doc on `/model/new` endpoint](./model_management.md#create-a-new-model) | +| max_request_size_mb | int | The maximum size for requests in MB. Requests above this size will be rejected. | +| max_response_size_mb | int | The maximum size for responses in MB. LLM Responses above this size will not be sent. | +| proxy_budget_rescheduler_min_time | int | The minimum time (in seconds) to wait before checking db for budget resets. **Default is 597 seconds** | +| proxy_budget_rescheduler_max_time | int | The maximum time (in seconds) to wait before checking db for budget resets. **Default is 605 seconds** | +| proxy_batch_write_at | int | Time (in seconds) to wait before batch writing spend logs to the db. **Default is 10 seconds** | +| alerting_args | dict | Args for Slack Alerting [Doc on Slack Alerting](./alerting.md) | +| custom_key_generate | str | Custom function for key generation [Doc on custom key generation](./virtual_keys.md#custom--key-generate) | +| allowed_ips | List[str] | List of IPs allowed to access the proxy. If not set, all IPs are allowed. | +| embedding_model | str | The default model to use for embeddings - ignores model set in request | +| default_team_disabled | boolean | If true, users cannot create 'personal' keys (keys with no team_id). | +| alert_to_webhook_url | Dict[str] | [Specify a webhook url for each alert type.](./alerting.md#set-specific-slack-channels-per-alert-type) | +| key_management_settings | List[Dict[str, Any]] | Settings for key management system (e.g. AWS KMS, Azure Key Vault) [Doc on key management](../secret.md) | +| allow_user_auth | boolean | (Deprecated) old approach for user authentication. | +| user_api_key_cache_ttl | int | The time (in seconds) to cache user api keys in memory. | +| disable_prisma_schema_update | boolean | If true, turns off automatic schema updates to DB | +| litellm_key_header_name | str | If set, allows passing LiteLLM keys as a custom header. [Doc on custom headers](./virtual_keys.md#custom-headers) | +| moderation_model | str | The default model to use for moderation. | +| custom_sso | str | Path to a python file that implements custom SSO logic. [Doc on custom SSO](./custom_sso.md) | +| allow_client_side_credentials | boolean | If true, allows passing client side credentials to the proxy. (Useful when testing finetuning models) [Doc on client side credentials](./virtual_keys.md#client-side-credentials) | +| admin_only_routes | List[str] | (Enterprise Feature) List of routes that are only accessible to admin users. [Doc on admin only routes](./enterprise#control-available-public-private-routes) | +| use_azure_key_vault | boolean | If true, load keys from azure key vault | +| use_google_kms | boolean | If true, load keys from google kms | +| spend_report_frequency | str | Specify how often you want a Spend Report to be sent (e.g. "1d", "2d", "30d") [More on this](./alerting.md#spend-report-frequency) | +| ui_access_mode | Literal["admin_only"] | If set, restricts access to the UI to admin users only. [Docs](./ui.md#restrict-ui-access) | +| litellm_jwtauth | Dict[str, Any] | Settings for JWT authentication. [Docs](./token_auth.md) | +| litellm_license | str | The license key for the proxy. [Docs](../enterprise.md#how-does-deployment-with-enterprise-license-work) | +| oauth2_config_mappings | Dict[str, str] | Define the OAuth2 config mappings | +| pass_through_endpoints | List[Dict[str, Any]] | Define the pass through endpoints. [Docs](./pass_through) | +| enable_oauth2_proxy_auth | boolean | (Enterprise Feature) If true, enables oauth2.0 authentication | +| forward_openai_org_id | boolean | If true, forwards the OpenAI Organization ID to the backend LLM call (if it's OpenAI). | +| forward_client_headers_to_llm_api | boolean | If true, forwards the client headers (any `x-` headers) to the backend LLM call | + +### router_settings - Reference + +:::info + +Most values can also be set via `litellm_settings`. If you see overlapping values, settings on `router_settings` will override those on `litellm_settings`. +::: + +```yaml +router_settings: + routing_strategy: usage-based-routing-v2 # Literal["simple-shuffle", "least-busy", "usage-based-routing","latency-based-routing"], default="simple-shuffle" + redis_host: # string + redis_password: # string + redis_port: # string + enable_pre_call_check: true # bool - Before call is made check if a call is within model context window + allowed_fails: 3 # cooldown model if it fails > 1 call in a minute. + cooldown_time: 30 # (in seconds) how long to cooldown model if fails/min > allowed_fails + disable_cooldowns: True # bool - Disable cooldowns for all models + enable_tag_filtering: True # bool - Use tag based routing for requests + retry_policy: { # Dict[str, int]: retry policy for different types of exceptions + "AuthenticationErrorRetries": 3, + "TimeoutErrorRetries": 3, + "RateLimitErrorRetries": 3, + "ContentPolicyViolationErrorRetries": 4, + "InternalServerErrorRetries": 4 + } + allowed_fails_policy: { + "BadRequestErrorAllowedFails": 1000, # Allow 1000 BadRequestErrors before cooling down a deployment + "AuthenticationErrorAllowedFails": 10, # int + "TimeoutErrorAllowedFails": 12, # int + "RateLimitErrorAllowedFails": 10000, # int + "ContentPolicyViolationErrorAllowedFails": 15, # int + "InternalServerErrorAllowedFails": 20, # int + } + content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}] # List[Dict[str, List[str]]]: Fallback model for content policy violations + fallbacks=[{"claude-2": ["my-fallback-model"]}] # List[Dict[str, List[str]]]: Fallback model for all errors +``` + +| Name | Type | Description | +|------|------|-------------| +| routing_strategy | string | The strategy used for routing requests. Options: "simple-shuffle", "least-busy", "usage-based-routing", "latency-based-routing". Default is "simple-shuffle". [More information here](../routing) | +| redis_host | string | The host address for the Redis server. **Only set this if you have multiple instances of LiteLLM Proxy and want current tpm/rpm tracking to be shared across them** | +| redis_password | string | The password for the Redis server. **Only set this if you have multiple instances of LiteLLM Proxy and want current tpm/rpm tracking to be shared across them** | +| redis_port | string | The port number for the Redis server. **Only set this if you have multiple instances of LiteLLM Proxy and want current tpm/rpm tracking to be shared across them**| +| enable_pre_call_check | boolean | If true, checks if a call is within the model's context window before making the call. [More information here](reliability) | +| content_policy_fallbacks | array of objects | Specifies fallback models for content policy violations. [More information here](reliability) | +| fallbacks | array of objects | Specifies fallback models for all types of errors. [More information here](reliability) | +| enable_tag_filtering | boolean | If true, uses tag based routing for requests [Tag Based Routing](tag_routing) | +| cooldown_time | integer | The duration (in seconds) to cooldown a model if it exceeds the allowed failures. | +| disable_cooldowns | boolean | If true, disables cooldowns for all models. [More information here](reliability) | +| retry_policy | object | Specifies the number of retries for different types of exceptions. [More information here](reliability) | +| allowed_fails | integer | The number of failures allowed before cooling down a model. [More information here](reliability) | +| allowed_fails_policy | object | Specifies the number of allowed failures for different error types before cooling down a deployment. [More information here](reliability) | +| default_max_parallel_requests | Optional[int] | The default maximum number of parallel requests for a deployment. | +| default_priority | (Optional[int]) | The default priority for a request. Only for '.scheduler_acompletion()'. Default is None. | +| polling_interval | (Optional[float]) | frequency of polling queue. Only for '.scheduler_acompletion()'. Default is 3ms. | +| max_fallbacks | Optional[int] | The maximum number of fallbacks to try before exiting the call. Defaults to 5. | +| default_litellm_params | Optional[dict] | The default litellm parameters to add to all requests (e.g. `temperature`, `max_tokens`). | +| timeout | Optional[float] | The default timeout for a request. | +| debug_level | Literal["DEBUG", "INFO"] | The debug level for the logging library in the router. Defaults to "INFO". | +| client_ttl | int | Time-to-live for cached clients in seconds. Defaults to 3600. | +| cache_kwargs | dict | Additional keyword arguments for the cache initialization. | +| routing_strategy_args | dict | Additional keyword arguments for the routing strategy - e.g. lowest latency routing default ttl | +| model_group_alias | dict | Model group alias mapping. E.g. `{"claude-3-haiku": "claude-3-haiku-20240229"}` | +| num_retries | int | Number of retries for a request. Defaults to 3. | +| default_fallbacks | Optional[List[str]] | Fallbacks to try if no model group-specific fallbacks are defined. | +| caching_groups | Optional[List[tuple]] | List of model groups for caching across model groups. Defaults to None. - e.g. caching_groups=[("openai-gpt-3.5-turbo", "azure-gpt-3.5-turbo")]| +| alerting_config | AlertingConfig | [SDK-only arg] Slack alerting configuration. Defaults to None. [Further Docs](../routing.md#alerting-) | +| assistants_config | AssistantsConfig | Set on proxy via `assistant_settings`. [Further docs](../assistants.md) | +| set_verbose | boolean | [DEPRECATED PARAM - see debug docs](./debugging.md) If true, sets the logging level to verbose. | +| retry_after | int | Time to wait before retrying a request in seconds. Defaults to 0. If `x-retry-after` is received from LLM API, this value is overridden. | +| provider_budget_config | ProviderBudgetConfig | Provider budget configuration. Use this to set llm_provider budget limits. example $100/day to OpenAI, $100/day to Azure, etc. Defaults to None. [Further Docs](./provider_budget_routing.md) | +| enable_pre_call_checks | boolean | If true, checks if a call is within the model's context window before making the call. [More information here](reliability) | +| model_group_retry_policy | Dict[str, RetryPolicy] | [SDK-only arg] Set retry policy for model groups. | +| context_window_fallbacks | List[Dict[str, List[str]]] | Fallback models for context window violations. | +| redis_url | str | URL for Redis server. **Known performance issue with Redis URL.** | +| cache_responses | boolean | Flag to enable caching LLM Responses, if cache set under `router_settings`. If true, caches responses. Defaults to False. | +| router_general_settings | RouterGeneralSettings | [SDK-Only] Router general settings - contains optimizations like 'async_only_mode'. [Docs](../routing.md#router-general-settings) | + +### environment variables - Reference + +| Name | Description | +|------|-------------| +| ACTIONS_ID_TOKEN_REQUEST_TOKEN | Token for requesting ID in GitHub Actions +| ACTIONS_ID_TOKEN_REQUEST_URL | URL for requesting ID token in GitHub Actions +| AISPEND_ACCOUNT_ID | Account ID for AI Spend +| AISPEND_API_KEY | API Key for AI Spend +| ALLOWED_EMAIL_DOMAINS | List of email domains allowed for access +| ARIZE_API_KEY | API key for Arize platform integration +| ARIZE_SPACE_KEY | Space key for Arize platform +| ARGILLA_BATCH_SIZE | Batch size for Argilla logging +| ARGILLA_API_KEY | API key for Argilla platform +| ARGILLA_SAMPLING_RATE | Sampling rate for Argilla logging +| ARGILLA_DATASET_NAME | Dataset name for Argilla logging +| ARGILLA_BASE_URL | Base URL for Argilla service +| ATHINA_API_KEY | API key for Athina service +| AUTH_STRATEGY | Strategy used for authentication (e.g., OAuth, API key) +| AWS_ACCESS_KEY_ID | Access Key ID for AWS services +| AWS_PROFILE_NAME | AWS CLI profile name to be used +| AWS_REGION_NAME | Default AWS region for service interactions +| AWS_ROLE_NAME | Role name for AWS IAM usage +| AWS_SECRET_ACCESS_KEY | Secret Access Key for AWS services +| AWS_SESSION_NAME | Name for AWS session +| AWS_WEB_IDENTITY_TOKEN | Web identity token for AWS +| AZURE_API_VERSION | Version of the Azure API being used +| AZURE_AUTHORITY_HOST | Azure authority host URL +| AZURE_CLIENT_ID | Client ID for Azure services +| AZURE_CLIENT_SECRET | Client secret for Azure services +| AZURE_FEDERATED_TOKEN_FILE | File path to Azure federated token +| AZURE_KEY_VAULT_URI | URI for Azure Key Vault +| AZURE_TENANT_ID | Tenant ID for Azure Active Directory +| BERRISPEND_ACCOUNT_ID | Account ID for BerriSpend service +| BRAINTRUST_API_KEY | API key for Braintrust integration +| CIRCLE_OIDC_TOKEN | OpenID Connect token for CircleCI +| CIRCLE_OIDC_TOKEN_V2 | Version 2 of the OpenID Connect token for CircleCI +| CONFIG_FILE_PATH | File path for configuration file +| CUSTOM_TIKTOKEN_CACHE_DIR | Custom directory for Tiktoken cache +| DATABASE_HOST | Hostname for the database server +| DATABASE_NAME | Name of the database +| DATABASE_PASSWORD | Password for the database user +| DATABASE_PORT | Port number for database connection +| DATABASE_SCHEMA | Schema name used in the database +| DATABASE_URL | Connection URL for the database +| DATABASE_USER | Username for database connection +| DATABASE_USERNAME | Alias for database user +| DATABRICKS_API_BASE | Base URL for Databricks API +| DD_BASE_URL | Base URL for Datadog integration +| DATADOG_BASE_URL | (Alternative to DD_BASE_URL) Base URL for Datadog integration +| _DATADOG_BASE_URL | (Alternative to DD_BASE_URL) Base URL for Datadog integration +| DD_API_KEY | API key for Datadog integration +| DD_SITE | Site URL for Datadog (e.g., datadoghq.com) +| DD_SOURCE | Source identifier for Datadog logs +| DD_ENV | Environment identifier for Datadog logs. Only supported for `datadog_llm_observability` callback +| DD_SERVICE | Service identifier for Datadog logs. Defaults to "litellm-server" +| DD_VERSION | Version identifier for Datadog logs. Defaults to "unknown" +| DEBUG_OTEL | Enable debug mode for OpenTelemetry +| DIRECT_URL | Direct URL for service endpoint +| DISABLE_ADMIN_UI | Toggle to disable the admin UI +| DISABLE_SCHEMA_UPDATE | Toggle to disable schema updates +| DOCS_DESCRIPTION | Description text for documentation pages +| DOCS_FILTERED | Flag indicating filtered documentation +| DOCS_TITLE | Title of the documentation pages +| DOCS_URL | The path to the Swagger API documentation. **By default this is "/"** +| EMAIL_SUPPORT_CONTACT | Support contact email address +| GCS_BUCKET_NAME | Name of the Google Cloud Storage bucket +| GCS_PATH_SERVICE_ACCOUNT | Path to the Google Cloud service account JSON file +| GCS_FLUSH_INTERVAL | Flush interval for GCS logging (in seconds). Specify how often you want a log to be sent to GCS. **Default is 20 seconds** +| GCS_BATCH_SIZE | Batch size for GCS logging. Specify after how many logs you want to flush to GCS. If `BATCH_SIZE` is set to 10, logs are flushed every 10 logs. **Default is 2048** +| GENERIC_AUTHORIZATION_ENDPOINT | Authorization endpoint for generic OAuth providers +| GENERIC_CLIENT_ID | Client ID for generic OAuth providers +| GENERIC_CLIENT_SECRET | Client secret for generic OAuth providers +| GENERIC_CLIENT_STATE | State parameter for generic client authentication +| GENERIC_INCLUDE_CLIENT_ID | Include client ID in requests for OAuth +| GENERIC_SCOPE | Scope settings for generic OAuth providers +| GENERIC_TOKEN_ENDPOINT | Token endpoint for generic OAuth providers +| GENERIC_USER_DISPLAY_NAME_ATTRIBUTE | Attribute for user's display name in generic auth +| GENERIC_USER_EMAIL_ATTRIBUTE | Attribute for user's email in generic auth +| GENERIC_USER_FIRST_NAME_ATTRIBUTE | Attribute for user's first name in generic auth +| GENERIC_USER_ID_ATTRIBUTE | Attribute for user ID in generic auth +| GENERIC_USER_LAST_NAME_ATTRIBUTE | Attribute for user's last name in generic auth +| GENERIC_USER_PROVIDER_ATTRIBUTE | Attribute specifying the user's provider +| GENERIC_USER_ROLE_ATTRIBUTE | Attribute specifying the user's role +| GENERIC_USERINFO_ENDPOINT | Endpoint to fetch user information in generic OAuth +| GALILEO_BASE_URL | Base URL for Galileo platform +| GALILEO_PASSWORD | Password for Galileo authentication +| GALILEO_PROJECT_ID | Project ID for Galileo usage +| GALILEO_USERNAME | Username for Galileo authentication +| GREENSCALE_API_KEY | API key for Greenscale service +| GREENSCALE_ENDPOINT | Endpoint URL for Greenscale service +| GOOGLE_APPLICATION_CREDENTIALS | Path to Google Cloud credentials JSON file +| GOOGLE_CLIENT_ID | Client ID for Google OAuth +| GOOGLE_CLIENT_SECRET | Client secret for Google OAuth +| GOOGLE_KMS_RESOURCE_NAME | Name of the resource in Google KMS +| HF_API_BASE | Base URL for Hugging Face API +| HELICONE_API_KEY | API key for Helicone service +| HUGGINGFACE_API_BASE | Base URL for Hugging Face API +| IAM_TOKEN_DB_AUTH | IAM token for database authentication +| JSON_LOGS | Enable JSON formatted logging +| JWT_AUDIENCE | Expected audience for JWT tokens +| JWT_PUBLIC_KEY_URL | URL to fetch public key for JWT verification +| LAGO_API_BASE | Base URL for Lago API +| LAGO_API_CHARGE_BY | Parameter to determine charge basis in Lago +| LAGO_API_EVENT_CODE | Event code for Lago API events +| LAGO_API_KEY | API key for accessing Lago services +| LANGFUSE_DEBUG | Toggle debug mode for Langfuse +| LANGFUSE_FLUSH_INTERVAL | Interval for flushing Langfuse logs +| LANGFUSE_HOST | Host URL for Langfuse service +| LANGFUSE_PUBLIC_KEY | Public key for Langfuse authentication +| LANGFUSE_RELEASE | Release version of Langfuse integration +| LANGFUSE_SECRET_KEY | Secret key for Langfuse authentication +| LANGSMITH_API_KEY | API key for Langsmith platform +| LANGSMITH_BASE_URL | Base URL for Langsmith service +| LANGSMITH_BATCH_SIZE | Batch size for operations in Langsmith +| LANGSMITH_DEFAULT_RUN_NAME | Default name for Langsmith run +| LANGSMITH_PROJECT | Project name for Langsmith integration +| LANGSMITH_SAMPLING_RATE | Sampling rate for Langsmith logging +| LANGTRACE_API_KEY | API key for Langtrace service +| LITERAL_API_KEY | API key for Literal integration +| LITERAL_API_URL | API URL for Literal service +| LITERAL_BATCH_SIZE | Batch size for Literal operations +| LITELLM_DONT_SHOW_FEEDBACK_BOX | Flag to hide feedback box in LiteLLM UI +| LITELLM_DROP_PARAMS | Parameters to drop in LiteLLM requests +| LITELLM_EMAIL | Email associated with LiteLLM account +| LITELLM_GLOBAL_MAX_PARALLEL_REQUEST_RETRIES | Maximum retries for parallel requests in LiteLLM +| LITELLM_GLOBAL_MAX_PARALLEL_REQUEST_RETRY_TIMEOUT | Timeout for retries of parallel requests in LiteLLM +| LITELLM_HOSTED_UI | URL of the hosted UI for LiteLLM +| LITELLM_LICENSE | License key for LiteLLM usage +| LITELLM_LOCAL_MODEL_COST_MAP | Local configuration for model cost mapping in LiteLLM +| LITELLM_LOG | Enable detailed logging for LiteLLM +| LITELLM_MODE | Operating mode for LiteLLM (e.g., production, development) +| LITELLM_SALT_KEY | Salt key for encryption in LiteLLM +| LITELLM_SECRET_AWS_KMS_LITELLM_LICENSE | AWS KMS encrypted license for LiteLLM +| LITELLM_TOKEN | Access token for LiteLLM integration +| LOGFIRE_TOKEN | Token for Logfire logging service +| MICROSOFT_CLIENT_ID | Client ID for Microsoft services +| MICROSOFT_CLIENT_SECRET | Client secret for Microsoft services +| MICROSOFT_TENANT | Tenant ID for Microsoft Azure +| NO_DOCS | Flag to disable documentation generation +| NO_PROXY | List of addresses to bypass proxy +| OAUTH_TOKEN_INFO_ENDPOINT | Endpoint for OAuth token info retrieval +| OPENAI_API_BASE | Base URL for OpenAI API +| OPENAI_API_KEY | API key for OpenAI services +| OPENAI_ORGANIZATION | Organization identifier for OpenAI +| OPENID_BASE_URL | Base URL for OpenID Connect services +| OPENID_CLIENT_ID | Client ID for OpenID Connect authentication +| OPENID_CLIENT_SECRET | Client secret for OpenID Connect authentication +| OPENMETER_API_ENDPOINT | API endpoint for OpenMeter integration +| OPENMETER_API_KEY | API key for OpenMeter services +| OPENMETER_EVENT_TYPE | Type of events sent to OpenMeter +| OTEL_ENDPOINT | OpenTelemetry endpoint for traces +| OTEL_ENVIRONMENT_NAME | Environment name for OpenTelemetry +| OTEL_EXPORTER | Exporter type for OpenTelemetry +| OTEL_HEADERS | Headers for OpenTelemetry requests +| OTEL_SERVICE_NAME | Service name identifier for OpenTelemetry +| OTEL_TRACER_NAME | Tracer name for OpenTelemetry tracing +| PREDIBASE_API_BASE | Base URL for Predibase API +| PRESIDIO_ANALYZER_API_BASE | Base URL for Presidio Analyzer service +| PRESIDIO_ANONYMIZER_API_BASE | Base URL for Presidio Anonymizer service +| PROMETHEUS_URL | URL for Prometheus service +| PROMPTLAYER_API_KEY | API key for PromptLayer integration +| PROXY_ADMIN_ID | Admin identifier for proxy server +| PROXY_BASE_URL | Base URL for proxy service +| PROXY_LOGOUT_URL | URL for logging out of the proxy service +| PROXY_MASTER_KEY | Master key for proxy authentication +| QDRANT_API_BASE | Base URL for Qdrant API +| QDRANT_API_KEY | API key for Qdrant service +| QDRANT_URL | Connection URL for Qdrant database +| REDIS_HOST | Hostname for Redis server +| REDIS_PASSWORD | Password for Redis service +| REDIS_PORT | Port number for Redis server +| REDOC_URL | The path to the Redoc Fast API documentation. **By default this is "/redoc"** +| SERVER_ROOT_PATH | Root path for the server application +| SET_VERBOSE | Flag to enable verbose logging +| SLACK_DAILY_REPORT_FREQUENCY | Frequency of daily Slack reports (e.g., daily, weekly) +| SLACK_WEBHOOK_URL | Webhook URL for Slack integration +| SMTP_HOST | Hostname for the SMTP server +| SMTP_PASSWORD | Password for SMTP authentication +| SMTP_PORT | Port number for SMTP server +| SMTP_SENDER_EMAIL | Email address used as the sender in SMTP transactions +| SMTP_SENDER_LOGO | Logo used in emails sent via SMTP +| SMTP_TLS | Flag to enable or disable TLS for SMTP connections +| SMTP_USERNAME | Username for SMTP authentication +| SPEND_LOGS_URL | URL for retrieving spend logs +| SSL_CERTIFICATE | Path to the SSL certificate file +| SSL_VERIFY | Flag to enable or disable SSL certificate verification +| SUPABASE_KEY | API key for Supabase service +| SUPABASE_URL | Base URL for Supabase instance +| TEST_EMAIL_ADDRESS | Email address used for testing purposes +| UI_LOGO_PATH | Path to the logo image used in the UI +| UI_PASSWORD | Password for accessing the UI +| UI_USERNAME | Username for accessing the UI +| UPSTREAM_LANGFUSE_DEBUG | Flag to enable debugging for upstream Langfuse +| UPSTREAM_LANGFUSE_HOST | Host URL for upstream Langfuse service +| UPSTREAM_LANGFUSE_PUBLIC_KEY | Public key for upstream Langfuse authentication +| UPSTREAM_LANGFUSE_RELEASE | Release version identifier for upstream Langfuse +| UPSTREAM_LANGFUSE_SECRET_KEY | Secret key for upstream Langfuse authentication +| USE_AWS_KMS | Flag to enable AWS Key Management Service for encryption +| WEBHOOK_URL | URL for receiving webhooks from external services + diff --git a/docs/my-website/docs/proxy/configs.md b/docs/my-website/docs/proxy/configs.md index 3b6b336d6..7876c9dec 100644 --- a/docs/my-website/docs/proxy/configs.md +++ b/docs/my-website/docs/proxy/configs.md @@ -2,7 +2,7 @@ import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; -# Proxy Config.yaml +# Overview Set model list, `api_base`, `api_key`, `temperature` & proxy server settings (`master-key`) on the config.yaml. | Param Name | Description | @@ -357,77 +357,6 @@ curl --location 'http://0.0.0.0:4000/v1/model/info' \ --data '' ``` - -### Provider specific wildcard routing -**Proxy all models from a provider** - -Use this if you want to **proxy all models from a specific provider without defining them on the config.yaml** - -**Step 1** - define provider specific routing on config.yaml -```yaml -model_list: - # provider specific wildcard routing - - model_name: "anthropic/*" - litellm_params: - model: "anthropic/*" - api_key: os.environ/ANTHROPIC_API_KEY - - model_name: "groq/*" - litellm_params: - model: "groq/*" - api_key: os.environ/GROQ_API_KEY - - model_name: "fo::*:static::*" # all requests matching this pattern will be routed to this deployment, example: model="fo::hi::static::hi" will be routed to deployment: "openai/fo::*:static::*" - litellm_params: - model: "openai/fo::*:static::*" - api_key: os.environ/OPENAI_API_KEY -``` - -Step 2 - Run litellm proxy - -```shell -$ litellm --config /path/to/config.yaml -``` - -Step 3 Test it - -Test with `anthropic/` - all models with `anthropic/` prefix will get routed to `anthropic/*` -```shell -curl http://localhost:4000/v1/chat/completions \ - -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ - -d '{ - "model": "anthropic/claude-3-sonnet-20240229", - "messages": [ - {"role": "user", "content": "Hello, Claude!"} - ] - }' -``` - -Test with `groq/` - all models with `groq/` prefix will get routed to `groq/*` -```shell -curl http://localhost:4000/v1/chat/completions \ - -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ - -d '{ - "model": "groq/llama3-8b-8192", - "messages": [ - {"role": "user", "content": "Hello, Claude!"} - ] - }' -``` - -Test with `fo::*::static::*` - all requests matching this pattern will be routed to `openai/fo::*:static::*` -```shell -curl http://localhost:4000/v1/chat/completions \ - -H "Content-Type: application/json" \ - -H "Authorization: Bearer sk-1234" \ - -d '{ - "model": "fo::hi::static::hi", - "messages": [ - {"role": "user", "content": "Hello, Claude!"} - ] - }' -``` - ### Load Balancing :::info @@ -597,479 +526,6 @@ general_settings: database_connection_timeout: 60 # sets a 60s timeout for any connection call to the db ``` -## **All settings** - - -```yaml -environment_variables: {} - -model_list: - - model_name: string - litellm_params: {} - model_info: - id: string - mode: embedding - input_cost_per_token: 0 - output_cost_per_token: 0 - max_tokens: 2048 - base_model: gpt-4-1106-preview - additionalProp1: {} - -litellm_settings: - # Logging/Callback settings - success_callback: ["langfuse"] # list of success callbacks - failure_callback: ["sentry"] # list of failure callbacks - callbacks: ["otel"] # list of callbacks - runs on success and failure - service_callbacks: ["datadog", "prometheus"] # logs redis, postgres failures on datadog, prometheus - turn_off_message_logging: boolean # prevent the messages and responses from being logged to on your callbacks, but request metadata will still be logged. - redact_user_api_key_info: boolean # Redact information about the user api key (hashed token, user_id, team id, etc.), from logs. Currently supported for Langfuse, OpenTelemetry, Logfire, ArizeAI logging. - langfuse_default_tags: ["cache_hit", "cache_key", "proxy_base_url", "user_api_key_alias", "user_api_key_user_id", "user_api_key_user_email", "user_api_key_team_alias", "semantic-similarity", "proxy_base_url"] # default tags for Langfuse Logging - - # Networking settings - request_timeout: 10 # (int) llm requesttimeout in seconds. Raise Timeout error if call takes longer than 10s. Sets litellm.request_timeout - force_ipv4: boolean # If true, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6 + Anthropic API - - set_verbose: boolean # sets litellm.set_verbose=True to view verbose debug logs. DO NOT LEAVE THIS ON IN PRODUCTION - json_logs: boolean # if true, logs will be in json format - - # Fallbacks, reliability - default_fallbacks: ["claude-opus"] # set default_fallbacks, in case a specific model group is misconfigured / bad. - content_policy_fallbacks: [{"gpt-3.5-turbo-small": ["claude-opus"]}] # fallbacks for ContentPolicyErrors - context_window_fallbacks: [{"gpt-3.5-turbo-small": ["gpt-3.5-turbo-large", "claude-opus"]}] # fallbacks for ContextWindowExceededErrors - - - - # Caching settings - cache: true - cache_params: # set cache params for redis - type: redis # type of cache to initialize - - # Optional - Redis Settings - host: "localhost" # The host address for the Redis cache. Required if type is "redis". - port: 6379 # The port number for the Redis cache. Required if type is "redis". - password: "your_password" # The password for the Redis cache. Required if type is "redis". - namespace: "litellm.caching.caching" # namespace for redis cache - - # Optional - Redis Cluster Settings - redis_startup_nodes: [{"host": "127.0.0.1", "port": "7001"}] - - # Optional - Redis Sentinel Settings - service_name: "mymaster" - sentinel_nodes: [["localhost", 26379]] - - # Optional - Qdrant Semantic Cache Settings - qdrant_semantic_cache_embedding_model: openai-embedding # the model should be defined on the model_list - qdrant_collection_name: test_collection - qdrant_quantization_config: binary - similarity_threshold: 0.8 # similarity threshold for semantic cache - - # Optional - S3 Cache Settings - s3_bucket_name: cache-bucket-litellm # AWS Bucket Name for S3 - s3_region_name: us-west-2 # AWS Region Name for S3 - s3_aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID # us os.environ/ to pass environment variables. This is AWS Access Key ID for S3 - s3_aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY # AWS Secret Access Key for S3 - s3_endpoint_url: https://s3.amazonaws.com # [OPTIONAL] S3 endpoint URL, if you want to use Backblaze/cloudflare s3 bucket - - # Common Cache settings - # Optional - Supported call types for caching - supported_call_types: ["acompletion", "atext_completion", "aembedding", "atranscription"] - # /chat/completions, /completions, /embeddings, /audio/transcriptions - mode: default_off # if default_off, you need to opt in to caching on a per call basis - ttl: 600 # ttl for caching - - -callback_settings: - otel: - message_logging: boolean # OTEL logging callback specific settings - -general_settings: - completion_model: string - disable_spend_logs: boolean # turn off writing each transaction to the db - disable_master_key_return: boolean # turn off returning master key on UI (checked on '/user/info' endpoint) - disable_retry_on_max_parallel_request_limit_error: boolean # turn off retries when max parallel request limit is reached - disable_reset_budget: boolean # turn off reset budget scheduled task - disable_adding_master_key_hash_to_db: boolean # turn off storing master key hash in db, for spend tracking - enable_jwt_auth: boolean # allow proxy admin to auth in via jwt tokens with 'litellm_proxy_admin' in claims - enforce_user_param: boolean # requires all openai endpoint requests to have a 'user' param - allowed_routes: ["route1", "route2"] # list of allowed proxy API routes - a user can access. (currently JWT-Auth only) - key_management_system: google_kms # either google_kms or azure_kms - master_key: string - - # Database Settings - database_url: string - database_connection_pool_limit: 0 # default 100 - database_connection_timeout: 0 # default 60s - allow_requests_on_db_unavailable: boolean # if true, will allow requests that can not connect to the DB to verify Virtual Key to still work - - custom_auth: string - max_parallel_requests: 0 # the max parallel requests allowed per deployment - global_max_parallel_requests: 0 # the max parallel requests allowed on the proxy all up - infer_model_from_keys: true - background_health_checks: true - health_check_interval: 300 - alerting: ["slack", "email"] - alerting_threshold: 0 - use_client_credentials_pass_through_routes: boolean # use client credentials for all pass through routes like "/vertex-ai", /bedrock/. When this is True Virtual Key auth will not be applied on these endpoints -``` - -### litellm_settings - Reference - -| Name | Type | Description | -|------|------|-------------| -| success_callback | array of strings | List of success callbacks. [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | -| failure_callback | array of strings | List of failure callbacks [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | -| callbacks | array of strings | List of callbacks - runs on success and failure [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | -| service_callbacks | array of strings | System health monitoring - Logs redis, postgres failures on specified services (e.g. datadog, prometheus) [Doc Metrics](prometheus) | -| turn_off_message_logging | boolean | If true, prevents messages and responses from being logged to callbacks, but request metadata will still be logged [Proxy Logging](logging) | -| modify_params | boolean | If true, allows modifying the parameters of the request before it is sent to the LLM provider | -| enable_preview_features | boolean | If true, enables preview features - e.g. Azure O1 Models with streaming support.| -| redact_user_api_key_info | boolean | If true, redacts information about the user api key from logs [Proxy Logging](logging#redacting-userapikeyinfo) | -| langfuse_default_tags | array of strings | Default tags for Langfuse Logging. Use this if you want to control which LiteLLM-specific fields are logged as tags by the LiteLLM proxy. By default LiteLLM Proxy logs no LiteLLM-specific fields as tags. [Further docs](./logging#litellm-specific-tags-on-langfuse---cache_hit-cache_key) | -| set_verbose | boolean | If true, sets litellm.set_verbose=True to view verbose debug logs. DO NOT LEAVE THIS ON IN PRODUCTION | -| json_logs | boolean | If true, logs will be in json format. If you need to store the logs as JSON, just set the `litellm.json_logs = True`. We currently just log the raw POST request from litellm as a JSON [Further docs](./debugging) | -| default_fallbacks | array of strings | List of fallback models to use if a specific model group is misconfigured / bad. [Further docs](./reliability#default-fallbacks) | -| request_timeout | integer | The timeout for requests in seconds. If not set, the default value is `6000 seconds`. [For reference OpenAI Python SDK defaults to `600 seconds`.](https://github.com/openai/openai-python/blob/main/src/openai/_constants.py) | -| force_ipv4 | boolean | If true, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6 + Anthropic API | -| content_policy_fallbacks | array of objects | Fallbacks to use when a ContentPolicyViolationError is encountered. [Further docs](./reliability#content-policy-fallbacks) | -| context_window_fallbacks | array of objects | Fallbacks to use when a ContextWindowExceededError is encountered. [Further docs](./reliability#context-window-fallbacks) | -| cache | boolean | If true, enables caching. [Further docs](./caching) | -| cache_params | object | Parameters for the cache. [Further docs](./caching) | -| cache_params.type | string | The type of cache to initialize. Can be one of ["local", "redis", "redis-semantic", "s3", "disk", "qdrant-semantic"]. Defaults to "redis". [Furher docs](./caching) | -| cache_params.host | string | The host address for the Redis cache. Required if type is "redis". | -| cache_params.port | integer | The port number for the Redis cache. Required if type is "redis". | -| cache_params.password | string | The password for the Redis cache. Required if type is "redis". | -| cache_params.namespace | string | The namespace for the Redis cache. | -| cache_params.redis_startup_nodes | array of objects | Redis Cluster Settings. [Further docs](./caching) | -| cache_params.service_name | string | Redis Sentinel Settings. [Further docs](./caching) | -| cache_params.sentinel_nodes | array of arrays | Redis Sentinel Settings. [Further docs](./caching) | -| cache_params.ttl | integer | The time (in seconds) to store entries in cache. | -| cache_params.qdrant_semantic_cache_embedding_model | string | The embedding model to use for qdrant semantic cache. | -| cache_params.qdrant_collection_name | string | The name of the collection to use for qdrant semantic cache. | -| cache_params.qdrant_quantization_config | string | The quantization configuration for the qdrant semantic cache. | -| cache_params.similarity_threshold | float | The similarity threshold for the semantic cache. | -| cache_params.s3_bucket_name | string | The name of the S3 bucket to use for the semantic cache. | -| cache_params.s3_region_name | string | The region name for the S3 bucket. | -| cache_params.s3_aws_access_key_id | string | The AWS access key ID for the S3 bucket. | -| cache_params.s3_aws_secret_access_key | string | The AWS secret access key for the S3 bucket. | -| cache_params.s3_endpoint_url | string | Optional - The endpoint URL for the S3 bucket. | -| cache_params.supported_call_types | array of strings | The types of calls to cache. [Further docs](./caching) | -| cache_params.mode | string | The mode of the cache. [Further docs](./caching) | - -### general_settings - Reference - -| Name | Type | Description | -|------|------|-------------| -| completion_model | string | The default model to use for completions when `model` is not specified in the request | -| disable_spend_logs | boolean | If true, turns off writing each transaction to the database | -| disable_master_key_return | boolean | If true, turns off returning master key on UI. (checked on '/user/info' endpoint) | -| disable_retry_on_max_parallel_request_limit_error | boolean | If true, turns off retries when max parallel request limit is reached | -| disable_reset_budget | boolean | If true, turns off reset budget scheduled task | -| disable_adding_master_key_hash_to_db | boolean | If true, turns off storing master key hash in db | -| enable_jwt_auth | boolean | allow proxy admin to auth in via jwt tokens with 'litellm_proxy_admin' in claims. [Doc on JWT Tokens](token_auth) | -| enforce_user_param | boolean | If true, requires all OpenAI endpoint requests to have a 'user' param. [Doc on call hooks](call_hooks)| -| allowed_routes | array of strings | List of allowed proxy API routes a user can access [Doc on controlling allowed routes](enterprise#control-available-public-private-routes)| -| key_management_system | string | Specifies the key management system. [Doc Secret Managers](../secret) | -| master_key | string | The master key for the proxy [Set up Virtual Keys](virtual_keys) | -| database_url | string | The URL for the database connection [Set up Virtual Keys](virtual_keys) | -| database_connection_pool_limit | integer | The limit for database connection pool [Setting DB Connection Pool limit](#configure-db-pool-limits--connection-timeouts) | -| database_connection_timeout | integer | The timeout for database connections in seconds [Setting DB Connection Pool limit, timeout](#configure-db-pool-limits--connection-timeouts) | -| allow_requests_on_db_unavailable | boolean | If true, allows requests to succeed even if DB is unreachable. **Only use this if running LiteLLM in your VPC** This will allow requests to work even when LiteLLM cannot connect to the DB to verify a Virtual Key | -| custom_auth | string | Write your own custom authentication logic [Doc Custom Auth](virtual_keys#custom-auth) | -| max_parallel_requests | integer | The max parallel requests allowed per deployment | -| global_max_parallel_requests | integer | The max parallel requests allowed on the proxy overall | -| infer_model_from_keys | boolean | If true, infers the model from the provided keys | -| background_health_checks | boolean | If true, enables background health checks. [Doc on health checks](health) | -| health_check_interval | integer | The interval for health checks in seconds [Doc on health checks](health) | -| alerting | array of strings | List of alerting methods [Doc on Slack Alerting](alerting) | -| alerting_threshold | integer | The threshold for triggering alerts [Doc on Slack Alerting](alerting) | -| use_client_credentials_pass_through_routes | boolean | If true, uses client credentials for all pass-through routes. [Doc on pass through routes](pass_through) | -| health_check_details | boolean | If false, hides health check details (e.g. remaining rate limit). [Doc on health checks](health) | -| public_routes | List[str] | (Enterprise Feature) Control list of public routes | -| alert_types | List[str] | Control list of alert types to send to slack (Doc on alert types)[./alerting.md] | -| enforced_params | List[str] | (Enterprise Feature) List of params that must be included in all requests to the proxy | -| enable_oauth2_auth | boolean | (Enterprise Feature) If true, enables oauth2.0 authentication | -| use_x_forwarded_for | str | If true, uses the X-Forwarded-For header to get the client IP address | -| service_account_settings | List[Dict[str, Any]] | Set `service_account_settings` if you want to create settings that only apply to service account keys (Doc on service accounts)[./service_accounts.md] | -| image_generation_model | str | The default model to use for image generation - ignores model set in request | -| store_model_in_db | boolean | If true, allows `/model/new` endpoint to store model information in db. Endpoint disabled by default. [Doc on `/model/new` endpoint](./model_management.md#create-a-new-model) | -| max_request_size_mb | int | The maximum size for requests in MB. Requests above this size will be rejected. | -| max_response_size_mb | int | The maximum size for responses in MB. LLM Responses above this size will not be sent. | -| proxy_budget_rescheduler_min_time | int | The minimum time (in seconds) to wait before checking db for budget resets. **Default is 597 seconds** | -| proxy_budget_rescheduler_max_time | int | The maximum time (in seconds) to wait before checking db for budget resets. **Default is 605 seconds** | -| proxy_batch_write_at | int | Time (in seconds) to wait before batch writing spend logs to the db. **Default is 10 seconds** | -| alerting_args | dict | Args for Slack Alerting [Doc on Slack Alerting](./alerting.md) | -| custom_key_generate | str | Custom function for key generation [Doc on custom key generation](./virtual_keys.md#custom--key-generate) | -| allowed_ips | List[str] | List of IPs allowed to access the proxy. If not set, all IPs are allowed. | -| embedding_model | str | The default model to use for embeddings - ignores model set in request | -| default_team_disabled | boolean | If true, users cannot create 'personal' keys (keys with no team_id). | -| alert_to_webhook_url | Dict[str] | [Specify a webhook url for each alert type.](./alerting.md#set-specific-slack-channels-per-alert-type) | -| key_management_settings | List[Dict[str, Any]] | Settings for key management system (e.g. AWS KMS, Azure Key Vault) [Doc on key management](../secret.md) | -| allow_user_auth | boolean | (Deprecated) old approach for user authentication. | -| user_api_key_cache_ttl | int | The time (in seconds) to cache user api keys in memory. | -| disable_prisma_schema_update | boolean | If true, turns off automatic schema updates to DB | -| litellm_key_header_name | str | If set, allows passing LiteLLM keys as a custom header. [Doc on custom headers](./virtual_keys.md#custom-headers) | -| moderation_model | str | The default model to use for moderation. | -| custom_sso | str | Path to a python file that implements custom SSO logic. [Doc on custom SSO](./custom_sso.md) | -| allow_client_side_credentials | boolean | If true, allows passing client side credentials to the proxy. (Useful when testing finetuning models) [Doc on client side credentials](./virtual_keys.md#client-side-credentials) | -| admin_only_routes | List[str] | (Enterprise Feature) List of routes that are only accessible to admin users. [Doc on admin only routes](./enterprise#control-available-public-private-routes) | -| use_azure_key_vault | boolean | If true, load keys from azure key vault | -| use_google_kms | boolean | If true, load keys from google kms | -| spend_report_frequency | str | Specify how often you want a Spend Report to be sent (e.g. "1d", "2d", "30d") [More on this](./alerting.md#spend-report-frequency) | -| ui_access_mode | Literal["admin_only"] | If set, restricts access to the UI to admin users only. [Docs](./ui.md#restrict-ui-access) | -| litellm_jwtauth | Dict[str, Any] | Settings for JWT authentication. [Docs](./token_auth.md) | -| litellm_license | str | The license key for the proxy. [Docs](../enterprise.md#how-does-deployment-with-enterprise-license-work) | -| oauth2_config_mappings | Dict[str, str] | Define the OAuth2 config mappings | -| pass_through_endpoints | List[Dict[str, Any]] | Define the pass through endpoints. [Docs](./pass_through) | -| enable_oauth2_proxy_auth | boolean | (Enterprise Feature) If true, enables oauth2.0 authentication | -| forward_openai_org_id | boolean | If true, forwards the OpenAI Organization ID to the backend LLM call (if it's OpenAI). | -| forward_client_headers_to_llm_api | boolean | If true, forwards the client headers (any `x-` headers) to the backend LLM call | - -### router_settings - Reference - -```yaml -router_settings: - routing_strategy: usage-based-routing-v2 # Literal["simple-shuffle", "least-busy", "usage-based-routing","latency-based-routing"], default="simple-shuffle" - redis_host: # string - redis_password: # string - redis_port: # string - enable_pre_call_check: true # bool - Before call is made check if a call is within model context window - allowed_fails: 3 # cooldown model if it fails > 1 call in a minute. - cooldown_time: 30 # (in seconds) how long to cooldown model if fails/min > allowed_fails - disable_cooldowns: True # bool - Disable cooldowns for all models - enable_tag_filtering: True # bool - Use tag based routing for requests - retry_policy: { # Dict[str, int]: retry policy for different types of exceptions - "AuthenticationErrorRetries": 3, - "TimeoutErrorRetries": 3, - "RateLimitErrorRetries": 3, - "ContentPolicyViolationErrorRetries": 4, - "InternalServerErrorRetries": 4 - } - allowed_fails_policy: { - "BadRequestErrorAllowedFails": 1000, # Allow 1000 BadRequestErrors before cooling down a deployment - "AuthenticationErrorAllowedFails": 10, # int - "TimeoutErrorAllowedFails": 12, # int - "RateLimitErrorAllowedFails": 10000, # int - "ContentPolicyViolationErrorAllowedFails": 15, # int - "InternalServerErrorAllowedFails": 20, # int - } - content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}] # List[Dict[str, List[str]]]: Fallback model for content policy violations - fallbacks=[{"claude-2": ["my-fallback-model"]}] # List[Dict[str, List[str]]]: Fallback model for all errors -``` - -| Name | Type | Description | -|------|------|-------------| -| routing_strategy | string | The strategy used for routing requests. Options: "simple-shuffle", "least-busy", "usage-based-routing", "latency-based-routing". Default is "simple-shuffle". [More information here](../routing) | -| redis_host | string | The host address for the Redis server. **Only set this if you have multiple instances of LiteLLM Proxy and want current tpm/rpm tracking to be shared across them** | -| redis_password | string | The password for the Redis server. **Only set this if you have multiple instances of LiteLLM Proxy and want current tpm/rpm tracking to be shared across them** | -| redis_port | string | The port number for the Redis server. **Only set this if you have multiple instances of LiteLLM Proxy and want current tpm/rpm tracking to be shared across them**| -| enable_pre_call_check | boolean | If true, checks if a call is within the model's context window before making the call. [More information here](reliability) | -| content_policy_fallbacks | array of objects | Specifies fallback models for content policy violations. [More information here](reliability) | -| fallbacks | array of objects | Specifies fallback models for all types of errors. [More information here](reliability) | -| enable_tag_filtering | boolean | If true, uses tag based routing for requests [Tag Based Routing](tag_routing) | -| cooldown_time | integer | The duration (in seconds) to cooldown a model if it exceeds the allowed failures. | -| disable_cooldowns | boolean | If true, disables cooldowns for all models. [More information here](reliability) | -| retry_policy | object | Specifies the number of retries for different types of exceptions. [More information here](reliability) | -| allowed_fails | integer | The number of failures allowed before cooling down a model. [More information here](reliability) | -| allowed_fails_policy | object | Specifies the number of allowed failures for different error types before cooling down a deployment. [More information here](reliability) | - - -### environment variables - Reference - -| Name | Description | -|------|-------------| -| ACTIONS_ID_TOKEN_REQUEST_TOKEN | Token for requesting ID in GitHub Actions -| ACTIONS_ID_TOKEN_REQUEST_URL | URL for requesting ID token in GitHub Actions -| AISPEND_ACCOUNT_ID | Account ID for AI Spend -| AISPEND_API_KEY | API Key for AI Spend -| ALLOWED_EMAIL_DOMAINS | List of email domains allowed for access -| ARIZE_API_KEY | API key for Arize platform integration -| ARIZE_SPACE_KEY | Space key for Arize platform -| ARGILLA_BATCH_SIZE | Batch size for Argilla logging -| ARGILLA_API_KEY | API key for Argilla platform -| ARGILLA_SAMPLING_RATE | Sampling rate for Argilla logging -| ARGILLA_DATASET_NAME | Dataset name for Argilla logging -| ARGILLA_BASE_URL | Base URL for Argilla service -| ATHINA_API_KEY | API key for Athina service -| AUTH_STRATEGY | Strategy used for authentication (e.g., OAuth, API key) -| AWS_ACCESS_KEY_ID | Access Key ID for AWS services -| AWS_PROFILE_NAME | AWS CLI profile name to be used -| AWS_REGION_NAME | Default AWS region for service interactions -| AWS_ROLE_NAME | Role name for AWS IAM usage -| AWS_SECRET_ACCESS_KEY | Secret Access Key for AWS services -| AWS_SESSION_NAME | Name for AWS session -| AWS_WEB_IDENTITY_TOKEN | Web identity token for AWS -| AZURE_API_VERSION | Version of the Azure API being used -| AZURE_AUTHORITY_HOST | Azure authority host URL -| AZURE_CLIENT_ID | Client ID for Azure services -| AZURE_CLIENT_SECRET | Client secret for Azure services -| AZURE_FEDERATED_TOKEN_FILE | File path to Azure federated token -| AZURE_KEY_VAULT_URI | URI for Azure Key Vault -| AZURE_TENANT_ID | Tenant ID for Azure Active Directory -| BERRISPEND_ACCOUNT_ID | Account ID for BerriSpend service -| BRAINTRUST_API_KEY | API key for Braintrust integration -| CIRCLE_OIDC_TOKEN | OpenID Connect token for CircleCI -| CIRCLE_OIDC_TOKEN_V2 | Version 2 of the OpenID Connect token for CircleCI -| CONFIG_FILE_PATH | File path for configuration file -| CUSTOM_TIKTOKEN_CACHE_DIR | Custom directory for Tiktoken cache -| DATABASE_HOST | Hostname for the database server -| DATABASE_NAME | Name of the database -| DATABASE_PASSWORD | Password for the database user -| DATABASE_PORT | Port number for database connection -| DATABASE_SCHEMA | Schema name used in the database -| DATABASE_URL | Connection URL for the database -| DATABASE_USER | Username for database connection -| DATABASE_USERNAME | Alias for database user -| DATABRICKS_API_BASE | Base URL for Databricks API -| DD_BASE_URL | Base URL for Datadog integration -| DATADOG_BASE_URL | (Alternative to DD_BASE_URL) Base URL for Datadog integration -| _DATADOG_BASE_URL | (Alternative to DD_BASE_URL) Base URL for Datadog integration -| DD_API_KEY | API key for Datadog integration -| DD_SITE | Site URL for Datadog (e.g., datadoghq.com) -| DD_SOURCE | Source identifier for Datadog logs -| DD_ENV | Environment identifier for Datadog logs. Only supported for `datadog_llm_observability` callback -| DEBUG_OTEL | Enable debug mode for OpenTelemetry -| DIRECT_URL | Direct URL for service endpoint -| DISABLE_ADMIN_UI | Toggle to disable the admin UI -| DISABLE_SCHEMA_UPDATE | Toggle to disable schema updates -| DOCS_DESCRIPTION | Description text for documentation pages -| DOCS_FILTERED | Flag indicating filtered documentation -| DOCS_TITLE | Title of the documentation pages -| DOCS_URL | The path to the Swagger API documentation. **By default this is "/"** -| EMAIL_SUPPORT_CONTACT | Support contact email address -| GCS_BUCKET_NAME | Name of the Google Cloud Storage bucket -| GCS_PATH_SERVICE_ACCOUNT | Path to the Google Cloud service account JSON file -| GCS_FLUSH_INTERVAL | Flush interval for GCS logging (in seconds). Specify how often you want a log to be sent to GCS. **Default is 20 seconds** -| GCS_BATCH_SIZE | Batch size for GCS logging. Specify after how many logs you want to flush to GCS. If `BATCH_SIZE` is set to 10, logs are flushed every 10 logs. **Default is 2048** -| GENERIC_AUTHORIZATION_ENDPOINT | Authorization endpoint for generic OAuth providers -| GENERIC_CLIENT_ID | Client ID for generic OAuth providers -| GENERIC_CLIENT_SECRET | Client secret for generic OAuth providers -| GENERIC_CLIENT_STATE | State parameter for generic client authentication -| GENERIC_INCLUDE_CLIENT_ID | Include client ID in requests for OAuth -| GENERIC_SCOPE | Scope settings for generic OAuth providers -| GENERIC_TOKEN_ENDPOINT | Token endpoint for generic OAuth providers -| GENERIC_USER_DISPLAY_NAME_ATTRIBUTE | Attribute for user's display name in generic auth -| GENERIC_USER_EMAIL_ATTRIBUTE | Attribute for user's email in generic auth -| GENERIC_USER_FIRST_NAME_ATTRIBUTE | Attribute for user's first name in generic auth -| GENERIC_USER_ID_ATTRIBUTE | Attribute for user ID in generic auth -| GENERIC_USER_LAST_NAME_ATTRIBUTE | Attribute for user's last name in generic auth -| GENERIC_USER_PROVIDER_ATTRIBUTE | Attribute specifying the user's provider -| GENERIC_USER_ROLE_ATTRIBUTE | Attribute specifying the user's role -| GENERIC_USERINFO_ENDPOINT | Endpoint to fetch user information in generic OAuth -| GALILEO_BASE_URL | Base URL for Galileo platform -| GALILEO_PASSWORD | Password for Galileo authentication -| GALILEO_PROJECT_ID | Project ID for Galileo usage -| GALILEO_USERNAME | Username for Galileo authentication -| GREENSCALE_API_KEY | API key for Greenscale service -| GREENSCALE_ENDPOINT | Endpoint URL for Greenscale service -| GOOGLE_APPLICATION_CREDENTIALS | Path to Google Cloud credentials JSON file -| GOOGLE_CLIENT_ID | Client ID for Google OAuth -| GOOGLE_CLIENT_SECRET | Client secret for Google OAuth -| GOOGLE_KMS_RESOURCE_NAME | Name of the resource in Google KMS -| HF_API_BASE | Base URL for Hugging Face API -| HELICONE_API_KEY | API key for Helicone service -| HUGGINGFACE_API_BASE | Base URL for Hugging Face API -| IAM_TOKEN_DB_AUTH | IAM token for database authentication -| JSON_LOGS | Enable JSON formatted logging -| JWT_AUDIENCE | Expected audience for JWT tokens -| JWT_PUBLIC_KEY_URL | URL to fetch public key for JWT verification -| LAGO_API_BASE | Base URL for Lago API -| LAGO_API_CHARGE_BY | Parameter to determine charge basis in Lago -| LAGO_API_EVENT_CODE | Event code for Lago API events -| LAGO_API_KEY | API key for accessing Lago services -| LANGFUSE_DEBUG | Toggle debug mode for Langfuse -| LANGFUSE_FLUSH_INTERVAL | Interval for flushing Langfuse logs -| LANGFUSE_HOST | Host URL for Langfuse service -| LANGFUSE_PUBLIC_KEY | Public key for Langfuse authentication -| LANGFUSE_RELEASE | Release version of Langfuse integration -| LANGFUSE_SECRET_KEY | Secret key for Langfuse authentication -| LANGSMITH_API_KEY | API key for Langsmith platform -| LANGSMITH_BASE_URL | Base URL for Langsmith service -| LANGSMITH_BATCH_SIZE | Batch size for operations in Langsmith -| LANGSMITH_DEFAULT_RUN_NAME | Default name for Langsmith run -| LANGSMITH_PROJECT | Project name for Langsmith integration -| LANGSMITH_SAMPLING_RATE | Sampling rate for Langsmith logging -| LANGTRACE_API_KEY | API key for Langtrace service -| LITERAL_API_KEY | API key for Literal integration -| LITERAL_API_URL | API URL for Literal service -| LITERAL_BATCH_SIZE | Batch size for Literal operations -| LITELLM_DONT_SHOW_FEEDBACK_BOX | Flag to hide feedback box in LiteLLM UI -| LITELLM_DROP_PARAMS | Parameters to drop in LiteLLM requests -| LITELLM_EMAIL | Email associated with LiteLLM account -| LITELLM_GLOBAL_MAX_PARALLEL_REQUEST_RETRIES | Maximum retries for parallel requests in LiteLLM -| LITELLM_GLOBAL_MAX_PARALLEL_REQUEST_RETRY_TIMEOUT | Timeout for retries of parallel requests in LiteLLM -| LITELLM_HOSTED_UI | URL of the hosted UI for LiteLLM -| LITELLM_LICENSE | License key for LiteLLM usage -| LITELLM_LOCAL_MODEL_COST_MAP | Local configuration for model cost mapping in LiteLLM -| LITELLM_LOG | Enable detailed logging for LiteLLM -| LITELLM_MODE | Operating mode for LiteLLM (e.g., production, development) -| LITELLM_SALT_KEY | Salt key for encryption in LiteLLM -| LITELLM_SECRET_AWS_KMS_LITELLM_LICENSE | AWS KMS encrypted license for LiteLLM -| LITELLM_TOKEN | Access token for LiteLLM integration -| LOGFIRE_TOKEN | Token for Logfire logging service -| MICROSOFT_CLIENT_ID | Client ID for Microsoft services -| MICROSOFT_CLIENT_SECRET | Client secret for Microsoft services -| MICROSOFT_TENANT | Tenant ID for Microsoft Azure -| NO_DOCS | Flag to disable documentation generation -| NO_PROXY | List of addresses to bypass proxy -| OAUTH_TOKEN_INFO_ENDPOINT | Endpoint for OAuth token info retrieval -| OPENAI_API_BASE | Base URL for OpenAI API -| OPENAI_API_KEY | API key for OpenAI services -| OPENAI_ORGANIZATION | Organization identifier for OpenAI -| OPENID_BASE_URL | Base URL for OpenID Connect services -| OPENID_CLIENT_ID | Client ID for OpenID Connect authentication -| OPENID_CLIENT_SECRET | Client secret for OpenID Connect authentication -| OPENMETER_API_ENDPOINT | API endpoint for OpenMeter integration -| OPENMETER_API_KEY | API key for OpenMeter services -| OPENMETER_EVENT_TYPE | Type of events sent to OpenMeter -| OTEL_ENDPOINT | OpenTelemetry endpoint for traces -| OTEL_ENVIRONMENT_NAME | Environment name for OpenTelemetry -| OTEL_EXPORTER | Exporter type for OpenTelemetry -| OTEL_HEADERS | Headers for OpenTelemetry requests -| OTEL_SERVICE_NAME | Service name identifier for OpenTelemetry -| OTEL_TRACER_NAME | Tracer name for OpenTelemetry tracing -| PREDIBASE_API_BASE | Base URL for Predibase API -| PRESIDIO_ANALYZER_API_BASE | Base URL for Presidio Analyzer service -| PRESIDIO_ANONYMIZER_API_BASE | Base URL for Presidio Anonymizer service -| PROMETHEUS_URL | URL for Prometheus service -| PROMPTLAYER_API_KEY | API key for PromptLayer integration -| PROXY_ADMIN_ID | Admin identifier for proxy server -| PROXY_BASE_URL | Base URL for proxy service -| PROXY_LOGOUT_URL | URL for logging out of the proxy service -| PROXY_MASTER_KEY | Master key for proxy authentication -| QDRANT_API_BASE | Base URL for Qdrant API -| QDRANT_API_KEY | API key for Qdrant service -| QDRANT_URL | Connection URL for Qdrant database -| REDIS_HOST | Hostname for Redis server -| REDIS_PASSWORD | Password for Redis service -| REDIS_PORT | Port number for Redis server -| REDOC_URL | The path to the Redoc Fast API documentation. **By default this is "/redoc"** -| SERVER_ROOT_PATH | Root path for the server application -| SET_VERBOSE | Flag to enable verbose logging -| SLACK_DAILY_REPORT_FREQUENCY | Frequency of daily Slack reports (e.g., daily, weekly) -| SLACK_WEBHOOK_URL | Webhook URL for Slack integration -| SMTP_HOST | Hostname for the SMTP server -| SMTP_PASSWORD | Password for SMTP authentication -| SMTP_PORT | Port number for SMTP server -| SMTP_SENDER_EMAIL | Email address used as the sender in SMTP transactions -| SMTP_SENDER_LOGO | Logo used in emails sent via SMTP -| SMTP_TLS | Flag to enable or disable TLS for SMTP connections -| SMTP_USERNAME | Username for SMTP authentication -| SPEND_LOGS_URL | URL for retrieving spend logs -| SSL_CERTIFICATE | Path to the SSL certificate file -| SSL_VERIFY | Flag to enable or disable SSL certificate verification -| SUPABASE_KEY | API key for Supabase service -| SUPABASE_URL | Base URL for Supabase instance -| TEST_EMAIL_ADDRESS | Email address used for testing purposes -| UI_LOGO_PATH | Path to the logo image used in the UI -| UI_PASSWORD | Password for accessing the UI -| UI_USERNAME | Username for accessing the UI -| UPSTREAM_LANGFUSE_DEBUG | Flag to enable debugging for upstream Langfuse -| UPSTREAM_LANGFUSE_HOST | Host URL for upstream Langfuse service -| UPSTREAM_LANGFUSE_PUBLIC_KEY | Public key for upstream Langfuse authentication -| UPSTREAM_LANGFUSE_RELEASE | Release version identifier for upstream Langfuse -| UPSTREAM_LANGFUSE_SECRET_KEY | Secret key for upstream Langfuse authentication -| USE_AWS_KMS | Flag to enable AWS Key Management Service for encryption -| WEBHOOK_URL | URL for receiving webhooks from external services ## Extras diff --git a/docs/my-website/docs/proxy/db_info.md b/docs/my-website/docs/proxy/db_info.md index 6e6a48bd1..8429f6360 100644 --- a/docs/my-website/docs/proxy/db_info.md +++ b/docs/my-website/docs/proxy/db_info.md @@ -50,18 +50,22 @@ You can see the full DB Schema [here](https://github.com/BerriAI/litellm/blob/ma | LiteLLM_ErrorLogs | Captures failed requests and errors. Stores exception details and request information. Helps with debugging and monitoring. | **Medium - on errors only** | | LiteLLM_AuditLog | Tracks changes to system configuration. Records who made changes and what was modified. Maintains history of updates to teams, users, and models. | **Off by default**, **High - when enabled** | -## How to Disable `LiteLLM_SpendLogs` +## Disable `LiteLLM_SpendLogs` & `LiteLLM_ErrorLogs` -You can disable spend_logs by setting `disable_spend_logs` to `True` on the `general_settings` section of your proxy_config.yaml file. +You can disable spend_logs and error_logs by setting `disable_spend_logs` and `disable_error_logs` to `True` on the `general_settings` section of your proxy_config.yaml file. ```yaml general_settings: - disable_spend_logs: True + disable_spend_logs: True # Disable writing spend logs to DB + disable_error_logs: True # Disable writing error logs to DB ``` +### What is the impact of disabling these logs? -### What is the impact of disabling `LiteLLM_SpendLogs`? - +When disabling spend logs (`disable_spend_logs: True`): - You **will not** be able to view Usage on the LiteLLM UI - You **will** continue seeing cost metrics on s3, Prometheus, Langfuse (any other Logging integration you are using) +When disabling error logs (`disable_error_logs: True`): +- You **will not** be able to view Errors on the LiteLLM UI +- You **will** continue seeing error logs in your application logs and any other logging integrations you are using diff --git a/docs/my-website/docs/proxy/load_balancing.md b/docs/my-website/docs/proxy/load_balancing.md index 20b803777..dc5724066 100644 --- a/docs/my-website/docs/proxy/load_balancing.md +++ b/docs/my-website/docs/proxy/load_balancing.md @@ -1,4 +1,4 @@ -# Multiple Instances +# Proxy - Load Balancing Load balance multiple instances of the same model The proxy will handle routing requests (using LiteLLM's Router). **Set `rpm` in the config if you want maximize throughput** diff --git a/docs/my-website/docs/proxy/prod.md b/docs/my-website/docs/proxy/prod.md index 32a6fceee..9dacedaab 100644 --- a/docs/my-website/docs/proxy/prod.md +++ b/docs/my-website/docs/proxy/prod.md @@ -23,6 +23,7 @@ general_settings: # OPTIONAL Best Practices disable_spend_logs: True # turn off writing each transaction to the db. We recommend doing this is you don't need to see Usage on the LiteLLM UI and are tracking metrics via Prometheus + disable_error_logs: True # turn off writing LLM Exceptions to DB allow_requests_on_db_unavailable: True # Only USE when running LiteLLM on your VPC. Allow requests to still be processed even if the DB is unavailable. We recommend doing this if you're running LiteLLM on VPC that cannot be accessed from the public internet. litellm_settings: @@ -102,17 +103,22 @@ general_settings: allow_requests_on_db_unavailable: True ``` -## 6. Disable spend_logs if you're not using the LiteLLM UI +## 6. Disable spend_logs & error_logs if not using the LiteLLM UI -By default LiteLLM will write every request to the `LiteLLM_SpendLogs` table. This is used for viewing Usage on the LiteLLM UI. +By default, LiteLLM writes several types of logs to the database: +- Every LLM API request to the `LiteLLM_SpendLogs` table +- LLM Exceptions to the `LiteLLM_LogsErrors` table -If you're not viewing Usage on the LiteLLM UI (most users use Prometheus when this is disabled), you can disable spend_logs by setting `disable_spend_logs` to `True`. +If you're not viewing these logs on the LiteLLM UI (most users use Prometheus for monitoring), you can disable them by setting the following flags to `True`: ```yaml general_settings: - disable_spend_logs: True + disable_spend_logs: True # Disable writing spend logs to DB + disable_error_logs: True # Disable writing error logs to DB ``` +[More information about what the Database is used for here](db_info) + ## 7. Use Helm PreSync Hook for Database Migrations [BETA] To ensure only one service manages database migrations, use our [Helm PreSync hook for Database Migrations](https://github.com/BerriAI/litellm/blob/main/deploy/charts/litellm-helm/templates/migrations-job.yaml). This ensures migrations are handled during `helm upgrade` or `helm install`, while LiteLLM pods explicitly disable migrations. diff --git a/docs/my-website/docs/proxy/prometheus.md b/docs/my-website/docs/proxy/prometheus.md index 58dc3dae3..f19101b36 100644 --- a/docs/my-website/docs/proxy/prometheus.md +++ b/docs/my-website/docs/proxy/prometheus.md @@ -192,3 +192,13 @@ Here is a screenshot of the metrics you can monitor with the LiteLLM Grafana Das |----------------------|--------------------------------------| | `litellm_llm_api_failed_requests_metric` | **deprecated** use `litellm_proxy_failed_requests_metric` | | `litellm_requests_metric` | **deprecated** use `litellm_proxy_total_requests_metric` | + + +## FAQ + +### What are `_created` vs. `_total` metrics? + +- `_created` metrics are metrics that are created when the proxy starts +- `_total` metrics are metrics that are incremented for each request + +You should consume the `_total` metrics for your counting purposes \ No newline at end of file diff --git a/docs/my-website/docs/proxy/provider_budget_routing.md b/docs/my-website/docs/proxy/provider_budget_routing.md index fea3f483c..1cb75d667 100644 --- a/docs/my-website/docs/proxy/provider_budget_routing.md +++ b/docs/my-website/docs/proxy/provider_budget_routing.md @@ -16,25 +16,27 @@ model_list: api_key: os.environ/OPENAI_API_KEY router_settings: - redis_host: - redis_password: - redis_port: provider_budget_config: - openai: - budget_limit: 0.000000000001 # float of $ value budget for time period - time_period: 1d # can be 1d, 2d, 30d - azure: - budget_limit: 100 - time_period: 1d - anthropic: - budget_limit: 100 - time_period: 10d - vertexai: - budget_limit: 100 - time_period: 12d - gemini: - budget_limit: 100 - time_period: 12d + openai: + budget_limit: 0.000000000001 # float of $ value budget for time period + time_period: 1d # can be 1d, 2d, 30d, 1mo, 2mo + azure: + budget_limit: 100 + time_period: 1d + anthropic: + budget_limit: 100 + time_period: 10d + vertex_ai: + budget_limit: 100 + time_period: 12d + gemini: + budget_limit: 100 + time_period: 12d + + # OPTIONAL: Set Redis Host, Port, and Password if using multiple instance of LiteLLM + redis_host: os.environ/REDIS_HOST + redis_port: os.environ/REDIS_PORT + redis_password: os.environ/REDIS_PASSWORD general_settings: master_key: sk-1234 @@ -112,8 +114,11 @@ Expected response on failure - If all providers exceed budget, raises an error 3. **Supported Time Periods**: - - Format: "Xd" where X is number of days - - Examples: "1d" (1 day), "30d" (30 days) + - Seconds: "Xs" (e.g., "30s") + - Minutes: "Xm" (e.g., "10m") + - Hours: "Xh" (e.g., "24h") + - Days: "Xd" (e.g., "1d", "30d") + - Months: "Xmo" (e.g., "1mo", "2mo") 4. **Requirements**: - Redis required for tracking spend across instances @@ -129,6 +134,31 @@ This metric indicates the remaining budget for a provider in dollars (USD) litellm_provider_remaining_budget_metric{api_provider="openai"} 10 ``` +## Multi-instance setup + +If you are using a multi-instance setup, you will need to set the Redis host, port, and password in the `proxy_config.yaml` file. Redis is used to sync the spend across LiteLLM instances. + +```yaml +model_list: + - model_name: gpt-3.5-turbo + litellm_params: + model: openai/gpt-3.5-turbo + api_key: os.environ/OPENAI_API_KEY + +router_settings: + provider_budget_config: + openai: + budget_limit: 0.000000000001 # float of $ value budget for time period + time_period: 1d # can be 1d, 2d, 30d, 1mo, 2mo + + # 👇 Add this: Set Redis Host, Port, and Password if using multiple instance of LiteLLM + redis_host: os.environ/REDIS_HOST + redis_port: os.environ/REDIS_PORT + redis_password: os.environ/REDIS_PASSWORD + +general_settings: + master_key: sk-1234 +``` ## Spec for provider_budget_config @@ -136,7 +166,12 @@ The `provider_budget_config` is a dictionary where: - **Key**: Provider name (string) - Must be a valid [LiteLLM provider name](https://docs.litellm.ai/docs/providers) - **Value**: Budget configuration object with the following parameters: - `budget_limit`: Float value representing the budget in USD - - `time_period`: String in the format "Xd" where X is the number of days (e.g., "1d", "30d") + - `time_period`: Duration string in one of the following formats: + - Seconds: `"Xs"` (e.g., "30s") + - Minutes: `"Xm"` (e.g., "10m") + - Hours: `"Xh"` (e.g., "24h") + - Days: `"Xd"` (e.g., "1d", "30d") + - Months: `"Xmo"` (e.g., "1mo", "2mo") Example structure: ```yaml @@ -147,4 +182,10 @@ provider_budget_config: azure: budget_limit: 500.0 # $500 USD time_period: "30d" # 30 day period + anthropic: + budget_limit: 200.0 # $200 USD + time_period: "1mo" # 1 month period + gemini: + budget_limit: 50.0 # $50 USD + time_period: "24h" # 24 hour period ``` \ No newline at end of file diff --git a/docs/my-website/docs/proxy/reliability.md b/docs/my-website/docs/proxy/reliability.md index 73f25f817..1e6d0e26c 100644 --- a/docs/my-website/docs/proxy/reliability.md +++ b/docs/my-website/docs/proxy/reliability.md @@ -2,7 +2,7 @@ import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; -# Fallbacks, Load Balancing, Retries +# Proxy - Fallbacks, Retries - Quick Start [load balancing](#test---load-balancing) - Quick Start [client side fallbacks](#test---client-side-fallbacks) diff --git a/docs/my-website/docs/proxy/self_serve.md b/docs/my-website/docs/proxy/self_serve.md index e04aa4b44..494d9e60d 100644 --- a/docs/my-website/docs/proxy/self_serve.md +++ b/docs/my-website/docs/proxy/self_serve.md @@ -217,4 +217,10 @@ litellm_settings: max_parallel_requests: 1000 # (Optional[int], optional): Max number of requests that can be made in parallel. Defaults to None. tpm_limit: 1000 #(Optional[int], optional): Tpm limit. Defaults to None. rpm_limit: 1000 #(Optional[int], optional): Rpm limit. Defaults to None. -``` \ No newline at end of file + + key_generation_settings: # Restricts who can generate keys. [Further docs](./virtual_keys.md#restricting-key-generation) + team_key_generation: + allowed_team_member_roles: ["admin"] + personal_key_generation: # maps to 'Default Team' on UI + allowed_user_roles: ["proxy_admin"] +``` diff --git a/docs/my-website/docs/proxy/team_based_routing.md b/docs/my-website/docs/proxy/team_based_routing.md index 89b18ec63..bda286f4a 100644 --- a/docs/my-website/docs/proxy/team_based_routing.md +++ b/docs/my-website/docs/proxy/team_based_routing.md @@ -1,4 +1,4 @@ -# 👥 Team-based Routing +# Team-based Routing ## Routing Route calls to different model groups based on the team-id diff --git a/docs/my-website/docs/proxy/virtual_keys.md b/docs/my-website/docs/proxy/virtual_keys.md index 3b9a2a03e..5bbb6b2a0 100644 --- a/docs/my-website/docs/proxy/virtual_keys.md +++ b/docs/my-website/docs/proxy/virtual_keys.md @@ -811,6 +811,78 @@ litellm_settings: team_id: "core-infra" ``` +### Restricting Key Generation + +Use this to control who can generate keys. Useful when letting others create keys on the UI. + +```yaml +litellm_settings: + key_generation_settings: + team_key_generation: + allowed_team_member_roles: ["admin"] + required_params: ["tags"] # require team admins to set tags for cost-tracking when generating a team key + personal_key_generation: # maps to 'Default Team' on UI + allowed_user_roles: ["proxy_admin"] +``` + +#### Spec + +```python +class TeamUIKeyGenerationConfig(TypedDict): + allowed_team_member_roles: List[str] + required_params: List[str] # require params on `/key/generate` to be set if a team key (team_id in request) is being generated + + +class PersonalUIKeyGenerationConfig(TypedDict): + allowed_user_roles: List[LitellmUserRoles] + required_params: List[str] # require params on `/key/generate` to be set if a personal key (no team_id in request) is being generated + + +class StandardKeyGenerationConfig(TypedDict, total=False): + team_key_generation: TeamUIKeyGenerationConfig + personal_key_generation: PersonalUIKeyGenerationConfig + + +class LitellmUserRoles(str, enum.Enum): + """ + Admin Roles: + PROXY_ADMIN: admin over the platform + PROXY_ADMIN_VIEW_ONLY: can login, view all own keys, view all spend + ORG_ADMIN: admin over a specific organization, can create teams, users only within their organization + + Internal User Roles: + INTERNAL_USER: can login, view/create/delete their own keys, view their spend + INTERNAL_USER_VIEW_ONLY: can login, view their own keys, view their own spend + + + Team Roles: + TEAM: used for JWT auth + + + Customer Roles: + CUSTOMER: External users -> these are customers + + """ + + # Admin Roles + PROXY_ADMIN = "proxy_admin" + PROXY_ADMIN_VIEW_ONLY = "proxy_admin_viewer" + + # Organization admins + ORG_ADMIN = "org_admin" + + # Internal User Roles + INTERNAL_USER = "internal_user" + INTERNAL_USER_VIEW_ONLY = "internal_user_viewer" + + # Team Roles + TEAM = "team" + + # Customer Roles - External users of proxy + CUSTOMER = "customer" +``` + + ## **Next Steps - Set Budgets, Rate Limits per Virtual Key** [Follow this doc to set budgets, rate limiters per virtual key with LiteLLM](users) diff --git a/docs/my-website/docs/router_architecture.md b/docs/my-website/docs/router_architecture.md new file mode 100644 index 000000000..13e9e411c --- /dev/null +++ b/docs/my-website/docs/router_architecture.md @@ -0,0 +1,24 @@ +import Image from '@theme/IdealImage'; +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Router Architecture (Fallbacks / Retries) + +## High Level architecture + + + +### Request Flow + +1. **User Sends Request**: The process begins when a user sends a request to the LiteLLM Router endpoint. All unified endpoints (`.completion`, `.embeddings`, etc) are supported by LiteLLM Router. + +2. **function_with_fallbacks**: The initial request is sent to the `function_with_fallbacks` function. This function wraps the initial request in a try-except block, to handle any exceptions - doing fallbacks if needed. This request is then sent to the `function_with_retries` function. + + +3. **function_with_retries**: The `function_with_retries` function wraps the request in a try-except block and passes the initial request to a base litellm unified function (`litellm.completion`, `litellm.embeddings`, etc) to handle LLM API calling. `function_with_retries` handles any exceptions - doing retries on the model group if needed (i.e. if the request fails, it will retry on an available model within the model group). + +4. **litellm.completion**: The `litellm.completion` function is a base function that handles the LLM API calling. It is used by `function_with_retries` to make the actual request to the LLM API. + +## Legend + +**model_group**: A group of LLM API deployments that share the same `model_name`, are part of the same `model_group`, and can be load balanced across. \ No newline at end of file diff --git a/docs/my-website/docs/routing.md b/docs/my-website/docs/routing.md index 702cafa7f..87fad7437 100644 --- a/docs/my-website/docs/routing.md +++ b/docs/my-website/docs/routing.md @@ -1891,3 +1891,22 @@ router = Router( debug_level="DEBUG" # defaults to INFO ) ``` + +## Router General Settings + +### Usage + +```python +router = Router(model_list=..., router_general_settings=RouterGeneralSettings(async_only_mode=True)) +``` + +### Spec +```python +class RouterGeneralSettings(BaseModel): + async_only_mode: bool = Field( + default=False + ) # this will only initialize async clients. Good for memory utils + pass_through_all_models: bool = Field( + default=False + ) # if passed a model not llm_router model list, pass through the request to litellm.acompletion/embedding +``` \ No newline at end of file diff --git a/docs/my-website/docs/text_completion.md b/docs/my-website/docs/text_completion.md new file mode 100644 index 000000000..8be40dfdc --- /dev/null +++ b/docs/my-website/docs/text_completion.md @@ -0,0 +1,174 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Text Completion + +### Usage + + + +```python +from litellm import text_completion + +response = text_completion( + model="gpt-3.5-turbo-instruct", + prompt="Say this is a test", + max_tokens=7 +) +``` + + + + +1. Define models on config.yaml + +```yaml +model_list: + - model_name: gpt-3.5-turbo-instruct + litellm_params: + model: text-completion-openai/gpt-3.5-turbo-instruct # The `text-completion-openai/` prefix will call openai.completions.create + api_key: os.environ/OPENAI_API_KEY + - model_name: text-davinci-003 + litellm_params: + model: text-completion-openai/text-davinci-003 + api_key: os.environ/OPENAI_API_KEY +``` + +2. Start litellm proxy server + +``` +litellm --config config.yaml +``` + + + + +```python +from openai import OpenAI + +# set base_url to your proxy server +# set api_key to send to proxy server +client = OpenAI(api_key="", base_url="http://0.0.0.0:4000") + +response = client.completions.create( + model="gpt-3.5-turbo-instruct", + prompt="Say this is a test", + max_tokens=7 +) + +print(response) +``` + + + + +```shell +curl --location 'http://0.0.0.0:4000/completions' \ + --header 'Content-Type: application/json' \ + --header 'Authorization: Bearer sk-1234' \ + --data '{ + "model": "gpt-3.5-turbo-instruct", + "prompt": "Say this is a test", + "max_tokens": 7 + }' +``` + + + + + + +## Input Params + +LiteLLM accepts and translates the [OpenAI Text Completion params](https://platform.openai.com/docs/api-reference/completions) across all supported providers. + +### Required Fields + +- `model`: *string* - ID of the model to use +- `prompt`: *string or array* - The prompt(s) to generate completions for + +### Optional Fields + +- `best_of`: *integer* - Generates best_of completions server-side and returns the "best" one +- `echo`: *boolean* - Echo back the prompt in addition to the completion. +- `frequency_penalty`: *number* - Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency. +- `logit_bias`: *map* - Modify the likelihood of specified tokens appearing in the completion +- `logprobs`: *integer* - Include the log probabilities on the logprobs most likely tokens. Max value of 5 +- `max_tokens`: *integer* - The maximum number of tokens to generate. +- `n`: *integer* - How many completions to generate for each prompt. +- `presence_penalty`: *number* - Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far. +- `seed`: *integer* - If specified, system will attempt to make deterministic samples +- `stop`: *string or array* - Up to 4 sequences where the API will stop generating tokens +- `stream`: *boolean* - Whether to stream back partial progress. Defaults to false +- `suffix`: *string* - The suffix that comes after a completion of inserted text +- `temperature`: *number* - What sampling temperature to use, between 0 and 2. +- `top_p`: *number* - An alternative to sampling with temperature, called nucleus sampling. +- `user`: *string* - A unique identifier representing your end-user + +## Output Format +Here's the exact JSON output format you can expect from completion calls: + + +[**Follows OpenAI's output format**](https://platform.openai.com/docs/api-reference/completions/object) + + + + + +```python +{ + "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7", + "object": "text_completion", + "created": 1589478378, + "model": "gpt-3.5-turbo-instruct", + "system_fingerprint": "fp_44709d6fcb", + "choices": [ + { + "text": "\n\nThis is indeed a test", + "index": 0, + "logprobs": null, + "finish_reason": "length" + } + ], + "usage": { + "prompt_tokens": 5, + "completion_tokens": 7, + "total_tokens": 12 + } +} + +``` + + + +```python +{ + "id": "cmpl-7iA7iJjj8V2zOkCGvWF2hAkDWBQZe", + "object": "text_completion", + "created": 1690759702, + "choices": [ + { + "text": "This", + "index": 0, + "logprobs": null, + "finish_reason": null + } + ], + "model": "gpt-3.5-turbo-instruct" + "system_fingerprint": "fp_44709d6fcb", +} + +``` + + + + + +## **Supported Providers** + +| Provider | Link to Usage | +|-------------|--------------------| +| OpenAI | [Usage](../docs/providers/text_completion_openai) | +| Azure OpenAI| [Usage](../docs/providers/azure) | + + diff --git a/docs/my-website/docs/wildcard_routing.md b/docs/my-website/docs/wildcard_routing.md new file mode 100644 index 000000000..80926d73e --- /dev/null +++ b/docs/my-website/docs/wildcard_routing.md @@ -0,0 +1,140 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# Provider specific Wildcard routing + +**Proxy all models from a provider** + +Use this if you want to **proxy all models from a specific provider without defining them on the config.yaml** + +## Step 1. Define provider specific routing + + + + +```python +from litellm import Router + +router = Router( + model_list=[ + { + "model_name": "anthropic/*", + "litellm_params": { + "model": "anthropic/*", + "api_key": os.environ["ANTHROPIC_API_KEY"] + } + }, + { + "model_name": "groq/*", + "litellm_params": { + "model": "groq/*", + "api_key": os.environ["GROQ_API_KEY"] + } + }, + { + "model_name": "fo::*:static::*", # all requests matching this pattern will be routed to this deployment, example: model="fo::hi::static::hi" will be routed to deployment: "openai/fo::*:static::*" + "litellm_params": { + "model": "openai/fo::*:static::*", + "api_key": os.environ["OPENAI_API_KEY"] + } + } + ] +) +``` + + + + +**Step 1** - define provider specific routing on config.yaml +```yaml +model_list: + # provider specific wildcard routing + - model_name: "anthropic/*" + litellm_params: + model: "anthropic/*" + api_key: os.environ/ANTHROPIC_API_KEY + - model_name: "groq/*" + litellm_params: + model: "groq/*" + api_key: os.environ/GROQ_API_KEY + - model_name: "fo::*:static::*" # all requests matching this pattern will be routed to this deployment, example: model="fo::hi::static::hi" will be routed to deployment: "openai/fo::*:static::*" + litellm_params: + model: "openai/fo::*:static::*" + api_key: os.environ/OPENAI_API_KEY +``` + + + +## [PROXY-Only] Step 2 - Run litellm proxy + +```shell +$ litellm --config /path/to/config.yaml +``` + +## Step 3 - Test it + + + + +```python +from litellm import Router + +router = Router(model_list=...) + +# Test with `anthropic/` - all models with `anthropic/` prefix will get routed to `anthropic/*` +resp = completion(model="anthropic/claude-3-sonnet-20240229", messages=[{"role": "user", "content": "Hello, Claude!"}]) +print(resp) + +# Test with `groq/` - all models with `groq/` prefix will get routed to `groq/*` +resp = completion(model="groq/llama3-8b-8192", messages=[{"role": "user", "content": "Hello, Groq!"}]) +print(resp) + +# Test with `fo::*::static::*` - all requests matching this pattern will be routed to `openai/fo::*:static::*` +resp = completion(model="fo::hi::static::hi", messages=[{"role": "user", "content": "Hello, Claude!"}]) +print(resp) +``` + + + + +Test with `anthropic/` - all models with `anthropic/` prefix will get routed to `anthropic/*` +```bash +curl http://localhost:4000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -H "Authorization: Bearer sk-1234" \ + -d '{ + "model": "anthropic/claude-3-sonnet-20240229", + "messages": [ + {"role": "user", "content": "Hello, Claude!"} + ] + }' +``` + +Test with `groq/` - all models with `groq/` prefix will get routed to `groq/*` +```shell +curl http://localhost:4000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -H "Authorization: Bearer sk-1234" \ + -d '{ + "model": "groq/llama3-8b-8192", + "messages": [ + {"role": "user", "content": "Hello, Claude!"} + ] + }' +``` + +Test with `fo::*::static::*` - all requests matching this pattern will be routed to `openai/fo::*:static::*` +```shell +curl http://localhost:4000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -H "Authorization: Bearer sk-1234" \ + -d '{ + "model": "fo::hi::static::hi", + "messages": [ + {"role": "user", "content": "Hello, Claude!"} + ] + }' +``` + + + diff --git a/docs/my-website/img/router_architecture.png b/docs/my-website/img/router_architecture.png new file mode 100644 index 000000000..195834185 Binary files /dev/null and b/docs/my-website/img/router_architecture.png differ diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js index f01402299..e6a028d83 100644 --- a/docs/my-website/sidebars.js +++ b/docs/my-website/sidebars.js @@ -29,13 +29,17 @@ const sidebars = { }, items: [ "proxy/docker_quick_start", + { + "type": "category", + "label": "Config.yaml", + "items": ["proxy/configs", "proxy/config_management", "proxy/config_settings"] + }, { type: "category", label: "Setup & Deployment", items: [ "proxy/deploy", "proxy/prod", - "proxy/configs", "proxy/cli", "proxy/model_management", "proxy/health", @@ -47,7 +51,7 @@ const sidebars = { { type: "category", label: "Architecture", - items: ["proxy/architecture", "proxy/db_info"], + items: ["proxy/architecture", "proxy/db_info", "router_architecture"], }, { type: "link", @@ -96,11 +100,10 @@ const sidebars = { label: "Spend Tracking + Budgets", items: ["proxy/cost_tracking", "proxy/users", "proxy/custom_pricing", "proxy/team_budgets", "proxy/billing", "proxy/customers"], }, - "proxy/reliability", { - type: "category", - label: "Routing", - items: ["proxy/load_balancing", "proxy/tag_routing", "proxy/provider_budget_routing", "proxy/team_based_routing", "proxy/customer_routing",], + type: "link", + label: "Load Balancing, Routing, Fallbacks", + href: "https://docs.litellm.ai/docs/routing-load-balancing", }, { type: "category", @@ -199,6 +202,31 @@ const sidebars = { ], }, + { + type: "category", + label: "Guides", + items: [ + "exception_mapping", + "completion/provider_specific_params", + "guides/finetuned_models", + "completion/audio", + "completion/vision", + "completion/json_mode", + "completion/prompt_caching", + "completion/predict_outputs", + "completion/prefix", + "completion/drop_params", + "completion/prompt_formatting", + "completion/stream", + "completion/message_trimming", + "completion/function_call", + "completion/model_alias", + "completion/batching", + "completion/mock_requests", + "completion/reliable_completions", + + ] + }, { type: "category", label: "Supported Endpoints", @@ -214,27 +242,11 @@ const sidebars = { }, items: [ "completion/input", - "completion/provider_specific_params", - "completion/json_mode", - "completion/prompt_caching", - "completion/audio", - "completion/vision", - "completion/predict_outputs", - "completion/prefix", - "completion/drop_params", - "completion/prompt_formatting", "completion/output", "completion/usage", - "exception_mapping", - "completion/stream", - "completion/message_trimming", - "completion/function_call", - "completion/model_alias", - "completion/batching", - "completion/mock_requests", - "completion/reliable_completions", ], }, + "text_completion", "embedding/supported_embedding", "image_generation", { @@ -250,6 +262,7 @@ const sidebars = { "batches", "realtime", "fine_tuning", + "moderation", { type: "link", label: "Use LiteLLM Proxy with Vertex, Bedrock SDK", @@ -259,8 +272,14 @@ const sidebars = { }, { type: "category", - label: "Load Balancing", - items: ["routing", "scheduler"], + label: "Routing, Loadbalancing & Fallbacks", + link: { + type: "generated-index", + title: "Routing, Loadbalancing & Fallbacks", + description: "Learn how to load balance, route, and set fallbacks for your LLM requests", + slug: "/routing-load-balancing", + }, + items: ["routing", "scheduler", "proxy/load_balancing", "proxy/reliability", "proxy/tag_routing", "proxy/provider_budget_routing", "proxy/team_based_routing", "proxy/customer_routing", "wildcard_routing"], }, { type: "category", diff --git a/enterprise/utils.py b/enterprise/utils.py index f0af1d676..cc97661d7 100644 --- a/enterprise/utils.py +++ b/enterprise/utils.py @@ -2,7 +2,9 @@ from typing import Optional, List from litellm._logging import verbose_logger from litellm.proxy.proxy_server import PrismaClient, HTTPException +from litellm.llms.custom_httpx.http_handler import HTTPHandler import collections +import httpx from datetime import datetime @@ -114,7 +116,6 @@ async def ui_get_spend_by_tags( def _forecast_daily_cost(data: list): - import requests # type: ignore from datetime import datetime, timedelta if len(data) == 0: @@ -136,17 +137,17 @@ def _forecast_daily_cost(data: list): print("last entry date", last_entry_date) - # Assuming today_date is a datetime object - today_date = datetime.now() - # Calculate the last day of the month last_day_of_todays_month = datetime( today_date.year, today_date.month % 12 + 1, 1 ) - timedelta(days=1) + print("last day of todays month", last_day_of_todays_month) # Calculate the remaining days in the month remaining_days = (last_day_of_todays_month - last_entry_date).days + print("remaining days", remaining_days) + current_spend_this_month = 0 series = {} for entry in data: @@ -176,13 +177,19 @@ def _forecast_daily_cost(data: list): "Content-Type": "application/json", } - response = requests.post( - url="https://trend-api-production.up.railway.app/forecast", - json=payload, - headers=headers, - ) - # check the status code - response.raise_for_status() + client = HTTPHandler() + + try: + response = client.post( + url="https://trend-api-production.up.railway.app/forecast", + json=payload, + headers=headers, + ) + except httpx.HTTPStatusError as e: + raise HTTPException( + status_code=500, + detail={"error": f"Error getting forecast: {e.response.text}"}, + ) json_response = response.json() forecast_data = json_response["forecast"] @@ -206,13 +213,3 @@ def _forecast_daily_cost(data: list): f"Predicted Spend for { today_month } 2024, ${total_predicted_spend}" ) return {"response": response_data, "predicted_spend": predicted_spend} - - # print(f"Date: {entry['date']}, Spend: {entry['spend']}, Response: {response.text}") - - -# _forecast_daily_cost( -# [ -# {"date": "2022-01-01", "spend": 100}, - -# ] -# ) diff --git a/litellm/__init__.py b/litellm/__init__.py index 9a8c56a56..43f91fe58 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -24,6 +24,7 @@ from litellm.proxy._types import ( KeyManagementSettings, LiteLLM_UpperboundKeyGenerateParams, ) +from litellm.types.utils import StandardKeyGenerationConfig import httpx import dotenv from enum import Enum @@ -67,6 +68,7 @@ callbacks: List[Union[Callable, _custom_logger_compatible_callbacks_literal]] = langfuse_default_tags: Optional[List[str]] = None langsmith_batch_size: Optional[int] = None argilla_batch_size: Optional[int] = None +datadog_use_v1: Optional[bool] = False # if you want to use v1 datadog logged payload argilla_transformation_object: Optional[Dict[str, Any]] = None _async_input_callback: List[Callable] = ( [] @@ -133,7 +135,7 @@ use_client: bool = False ssl_verify: Union[str, bool] = True ssl_certificate: Optional[str] = None disable_streaming_logging: bool = False -in_memory_llm_clients_cache: dict = {} +in_memory_llm_clients_cache: InMemoryCache = InMemoryCache() safe_memory_mode: bool = False enable_azure_ad_token_refresh: Optional[bool] = False ### DEFAULT AZURE API VERSION ### @@ -273,6 +275,7 @@ s3_callback_params: Optional[Dict] = None generic_logger_headers: Optional[Dict] = None default_key_generate_params: Optional[Dict] = None upperbound_key_generate_params: Optional[LiteLLM_UpperboundKeyGenerateParams] = None +key_generation_settings: Optional[StandardKeyGenerationConfig] = None default_internal_user_params: Optional[Dict] = None default_team_settings: Optional[List] = None max_user_budget: Optional[float] = None @@ -280,6 +283,7 @@ default_max_internal_user_budget: Optional[float] = None max_internal_user_budget: Optional[float] = None internal_user_budget_duration: Optional[str] = None max_end_user_budget: Optional[float] = None +disable_end_user_cost_tracking: Optional[bool] = None #### REQUEST PRIORITIZATION #### priority_reservation: Optional[Dict[str, float]] = None #### RELIABILITY #### diff --git a/litellm/_redis.py b/litellm/_redis.py index 2fba9d146..d905f1c9d 100644 --- a/litellm/_redis.py +++ b/litellm/_redis.py @@ -313,12 +313,13 @@ def get_redis_async_client(**env_overrides) -> async_redis.Redis: def get_redis_connection_pool(**env_overrides): redis_kwargs = _get_redis_client_logic(**env_overrides) + verbose_logger.debug("get_redis_connection_pool: redis_kwargs", redis_kwargs) if "url" in redis_kwargs and redis_kwargs["url"] is not None: return async_redis.BlockingConnectionPool.from_url( timeout=5, url=redis_kwargs["url"] ) connection_class = async_redis.Connection - if "ssl" in redis_kwargs and redis_kwargs["ssl"] is not None: + if "ssl" in redis_kwargs: connection_class = async_redis.SSLConnection redis_kwargs.pop("ssl", None) redis_kwargs["connection_class"] = connection_class diff --git a/litellm/caching/redis_cache.py b/litellm/caching/redis_cache.py index e15a3f83d..ba5c3a695 100644 --- a/litellm/caching/redis_cache.py +++ b/litellm/caching/redis_cache.py @@ -20,6 +20,7 @@ from typing import TYPE_CHECKING, Any, List, Optional, Tuple import litellm from litellm._logging import print_verbose, verbose_logger from litellm.litellm_core_utils.core_helpers import _get_parent_otel_span_from_kwargs +from litellm.types.caching import RedisPipelineIncrementOperation from litellm.types.services import ServiceLoggerPayload, ServiceTypes from litellm.types.utils import all_litellm_params @@ -890,3 +891,92 @@ class RedisCache(BaseCache): def delete_cache(self, key): self.redis_client.delete(key) + + async def _pipeline_increment_helper( + self, + pipe: pipeline, + increment_list: List[RedisPipelineIncrementOperation], + ) -> Optional[List[float]]: + """Helper function for pipeline increment operations""" + # Iterate through each increment operation and add commands to pipeline + for increment_op in increment_list: + cache_key = self.check_and_fix_namespace(key=increment_op["key"]) + print_verbose( + f"Increment ASYNC Redis Cache PIPELINE: key: {cache_key}\nValue {increment_op['increment_value']}\nttl={increment_op['ttl']}" + ) + pipe.incrbyfloat(cache_key, increment_op["increment_value"]) + if increment_op["ttl"] is not None: + _td = timedelta(seconds=increment_op["ttl"]) + pipe.expire(cache_key, _td) + # Execute the pipeline and return results + results = await pipe.execute() + print_verbose(f"Increment ASYNC Redis Cache PIPELINE: results: {results}") + return results + + async def async_increment_pipeline( + self, increment_list: List[RedisPipelineIncrementOperation], **kwargs + ) -> Optional[List[float]]: + """ + Use Redis Pipelines for bulk increment operations + Args: + increment_list: List of RedisPipelineIncrementOperation dicts containing: + - key: str + - increment_value: float + - ttl_seconds: int + """ + # don't waste a network request if there's nothing to increment + if len(increment_list) == 0: + return None + + from redis.asyncio import Redis + + _redis_client: Redis = self.init_async_client() # type: ignore + start_time = time.time() + + print_verbose( + f"Increment Async Redis Cache Pipeline: increment list: {increment_list}" + ) + + try: + async with _redis_client as redis_client: + async with redis_client.pipeline(transaction=True) as pipe: + results = await self._pipeline_increment_helper( + pipe, increment_list + ) + + print_verbose(f"pipeline increment results: {results}") + + ## LOGGING ## + end_time = time.time() + _duration = end_time - start_time + asyncio.create_task( + self.service_logger_obj.async_service_success_hook( + service=ServiceTypes.REDIS, + duration=_duration, + call_type="async_increment_pipeline", + start_time=start_time, + end_time=end_time, + parent_otel_span=_get_parent_otel_span_from_kwargs(kwargs), + ) + ) + return results + except Exception as e: + ## LOGGING ## + end_time = time.time() + _duration = end_time - start_time + asyncio.create_task( + self.service_logger_obj.async_service_failure_hook( + service=ServiceTypes.REDIS, + duration=_duration, + error=e, + call_type="async_increment_pipeline", + start_time=start_time, + end_time=end_time, + parent_otel_span=_get_parent_otel_span_from_kwargs(kwargs), + ) + ) + verbose_logger.error( + "LiteLLM Redis Caching: async increment_pipeline() - Got exception from REDIS %s", + str(e), + ) + raise e diff --git a/litellm/integrations/datadog/datadog.py b/litellm/integrations/datadog/datadog.py index 40044ce9f..482c2bc10 100644 --- a/litellm/integrations/datadog/datadog.py +++ b/litellm/integrations/datadog/datadog.py @@ -32,9 +32,11 @@ from litellm.llms.custom_httpx.http_handler import ( get_async_httpx_client, httpxSpecialProvider, ) +from litellm.proxy._types import UserAPIKeyAuth +from litellm.types.integrations.datadog import * from litellm.types.services import ServiceLoggerPayload +from litellm.types.utils import StandardLoggingPayload -from .types import DD_ERRORS, DatadogPayload, DataDogStatus from .utils import make_json_serializable DD_MAX_BATCH_SIZE = 1000 # max number of logs DD API can accept @@ -106,20 +108,20 @@ class DataDogLogger(CustomBatchLogger): verbose_logger.debug( "Datadog: Logging - Enters logging function for model %s", kwargs ) - dd_payload = self.create_datadog_logging_payload( - kwargs=kwargs, - response_obj=response_obj, - start_time=start_time, - end_time=end_time, - ) + await self._log_async_event(kwargs, response_obj, start_time, end_time) - self.log_queue.append(dd_payload) + except Exception as e: + verbose_logger.exception( + f"Datadog Layer Error - {str(e)}\n{traceback.format_exc()}" + ) + pass + + async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + try: verbose_logger.debug( - f"Datadog, event added to queue. Will flush in {self.flush_interval} seconds..." + "Datadog: Logging - Enters logging function for model %s", kwargs ) - - if len(self.log_queue) >= self.batch_size: - await self.async_send_batch() + await self._log_async_event(kwargs, response_obj, start_time, end_time) except Exception as e: verbose_logger.exception( @@ -181,12 +183,20 @@ class DataDogLogger(CustomBatchLogger): verbose_logger.debug( "Datadog: Logging - Enters logging function for model %s", kwargs ) - dd_payload = self.create_datadog_logging_payload( - kwargs=kwargs, - response_obj=response_obj, - start_time=start_time, - end_time=end_time, - ) + if litellm.datadog_use_v1 is True: + dd_payload = self._create_v0_logging_payload( + kwargs=kwargs, + response_obj=response_obj, + start_time=start_time, + end_time=end_time, + ) + else: + dd_payload = self.create_datadog_logging_payload( + kwargs=kwargs, + response_obj=response_obj, + start_time=start_time, + end_time=end_time, + ) response = self.sync_client.post( url=self.intake_url, @@ -215,6 +225,22 @@ class DataDogLogger(CustomBatchLogger): pass pass + async def _log_async_event(self, kwargs, response_obj, start_time, end_time): + dd_payload = self.create_datadog_logging_payload( + kwargs=kwargs, + response_obj=response_obj, + start_time=start_time, + end_time=end_time, + ) + + self.log_queue.append(dd_payload) + verbose_logger.debug( + f"Datadog, event added to queue. Will flush in {self.flush_interval} seconds..." + ) + + if len(self.log_queue) >= self.batch_size: + await self.async_send_batch() + def create_datadog_logging_payload( self, kwargs: Union[dict, Any], @@ -236,73 +262,29 @@ class DataDogLogger(CustomBatchLogger): """ import json - litellm_params = kwargs.get("litellm_params", {}) - metadata = ( - litellm_params.get("metadata", {}) or {} - ) # if litellm_params['metadata'] == None - messages = kwargs.get("messages") - optional_params = kwargs.get("optional_params", {}) - call_type = kwargs.get("call_type", "litellm.completion") - cache_hit = kwargs.get("cache_hit", False) - usage = response_obj["usage"] - id = response_obj.get("id", str(uuid.uuid4())) - usage = dict(usage) - try: - response_time = (end_time - start_time).total_seconds() * 1000 - except Exception: - response_time = None + standard_logging_object: Optional[StandardLoggingPayload] = kwargs.get( + "standard_logging_object", None + ) + if standard_logging_object is None: + raise ValueError("standard_logging_object not found in kwargs") - try: - response_obj = dict(response_obj) - except Exception: - response_obj = response_obj - - # Clean Metadata before logging - never log raw metadata - # the raw metadata can contain circular references which leads to infinite recursion - # we clean out all extra litellm metadata params before logging - clean_metadata = {} - if isinstance(metadata, dict): - for key, value in metadata.items(): - # clean litellm metadata before logging - if key in [ - "endpoint", - "caching_groups", - "previous_models", - ]: - continue - else: - clean_metadata[key] = value + status = DataDogStatus.INFO + if standard_logging_object.get("status") == "failure": + status = DataDogStatus.ERROR # Build the initial payload - payload = { - "id": id, - "call_type": call_type, - "cache_hit": cache_hit, - "start_time": start_time, - "end_time": end_time, - "response_time": response_time, - "model": kwargs.get("model", ""), - "user": kwargs.get("user", ""), - "model_parameters": optional_params, - "spend": kwargs.get("response_cost", 0), - "messages": messages, - "response": response_obj, - "usage": usage, - "metadata": clean_metadata, - } - - make_json_serializable(payload) - json_payload = json.dumps(payload) + make_json_serializable(standard_logging_object) + json_payload = json.dumps(standard_logging_object) verbose_logger.debug("Datadog: Logger - Logging payload = %s", json_payload) dd_payload = DatadogPayload( - ddsource=os.getenv("DD_SOURCE", "litellm"), - ddtags="", - hostname="", + ddsource=self._get_datadog_source(), + ddtags=self._get_datadog_tags(), + hostname=self._get_datadog_hostname(), message=json_payload, - service="litellm-server", - status=DataDogStatus.INFO, + service=self._get_datadog_service(), + status=status, ) return dd_payload @@ -382,3 +364,140 @@ class DataDogLogger(CustomBatchLogger): No user has asked for this so far, this might be spammy on datatdog. If need arises we can implement this """ return + + async def async_post_call_failure_hook( + self, + request_data: dict, + original_exception: Exception, + user_api_key_dict: UserAPIKeyAuth, + ): + """ + Handles Proxy Errors (not-related to LLM API), ex: Authentication Errors + """ + import json + + _exception_payload = DatadogProxyFailureHookJsonMessage( + exception=str(original_exception), + error_class=str(original_exception.__class__.__name__), + status_code=getattr(original_exception, "status_code", None), + traceback=traceback.format_exc(), + user_api_key_dict=user_api_key_dict.model_dump(), + ) + + json_payload = json.dumps(_exception_payload) + verbose_logger.debug("Datadog: Logger - Logging payload = %s", json_payload) + dd_payload = DatadogPayload( + ddsource=self._get_datadog_source(), + ddtags=self._get_datadog_tags(), + hostname=self._get_datadog_hostname(), + message=json_payload, + service=self._get_datadog_service(), + status=DataDogStatus.ERROR, + ) + + self.log_queue.append(dd_payload) + + def _create_v0_logging_payload( + self, + kwargs: Union[dict, Any], + response_obj: Any, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> DatadogPayload: + """ + Note: This is our V1 Version of DataDog Logging Payload + + + (Not Recommended) If you want this to get logged set `litellm.datadog_use_v1 = True` + """ + import json + + litellm_params = kwargs.get("litellm_params", {}) + metadata = ( + litellm_params.get("metadata", {}) or {} + ) # if litellm_params['metadata'] == None + messages = kwargs.get("messages") + optional_params = kwargs.get("optional_params", {}) + call_type = kwargs.get("call_type", "litellm.completion") + cache_hit = kwargs.get("cache_hit", False) + usage = response_obj["usage"] + id = response_obj.get("id", str(uuid.uuid4())) + usage = dict(usage) + try: + response_time = (end_time - start_time).total_seconds() * 1000 + except Exception: + response_time = None + + try: + response_obj = dict(response_obj) + except Exception: + response_obj = response_obj + + # Clean Metadata before logging - never log raw metadata + # the raw metadata can contain circular references which leads to infinite recursion + # we clean out all extra litellm metadata params before logging + clean_metadata = {} + if isinstance(metadata, dict): + for key, value in metadata.items(): + # clean litellm metadata before logging + if key in [ + "endpoint", + "caching_groups", + "previous_models", + ]: + continue + else: + clean_metadata[key] = value + + # Build the initial payload + payload = { + "id": id, + "call_type": call_type, + "cache_hit": cache_hit, + "start_time": start_time, + "end_time": end_time, + "response_time": response_time, + "model": kwargs.get("model", ""), + "user": kwargs.get("user", ""), + "model_parameters": optional_params, + "spend": kwargs.get("response_cost", 0), + "messages": messages, + "response": response_obj, + "usage": usage, + "metadata": clean_metadata, + } + + make_json_serializable(payload) + json_payload = json.dumps(payload) + + verbose_logger.debug("Datadog: Logger - Logging payload = %s", json_payload) + + dd_payload = DatadogPayload( + ddsource=self._get_datadog_source(), + ddtags=self._get_datadog_tags(), + hostname=self._get_datadog_hostname(), + message=json_payload, + service=self._get_datadog_service(), + status=DataDogStatus.INFO, + ) + return dd_payload + + @staticmethod + def _get_datadog_tags(): + return f"env:{os.getenv('DD_ENV', 'unknown')},service:{os.getenv('DD_SERVICE', 'litellm')},version:{os.getenv('DD_VERSION', 'unknown')}" + + @staticmethod + def _get_datadog_source(): + return os.getenv("DD_SOURCE", "litellm") + + @staticmethod + def _get_datadog_service(): + return os.getenv("DD_SERVICE", "litellm-server") + + @staticmethod + def _get_datadog_hostname(): + return "" + + @staticmethod + def _get_datadog_env(): + return os.getenv("DD_ENV", "unknown") diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index bb28719a3..1460a1d7f 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -18,6 +18,7 @@ from litellm.integrations.custom_logger import CustomLogger from litellm.proxy._types import UserAPIKeyAuth from litellm.types.integrations.prometheus import * from litellm.types.utils import StandardLoggingPayload +from litellm.utils import get_end_user_id_for_cost_tracking class PrometheusLogger(CustomLogger): @@ -364,8 +365,7 @@ class PrometheusLogger(CustomLogger): model = kwargs.get("model", "") litellm_params = kwargs.get("litellm_params", {}) or {} _metadata = litellm_params.get("metadata", {}) - proxy_server_request = litellm_params.get("proxy_server_request") or {} - end_user_id = proxy_server_request.get("body", {}).get("user", None) + end_user_id = get_end_user_id_for_cost_tracking(litellm_params) user_id = standard_logging_payload["metadata"]["user_api_key_user_id"] user_api_key = standard_logging_payload["metadata"]["user_api_key_hash"] user_api_key_alias = standard_logging_payload["metadata"]["user_api_key_alias"] @@ -664,13 +664,11 @@ class PrometheusLogger(CustomLogger): # unpack kwargs model = kwargs.get("model", "") - litellm_params = kwargs.get("litellm_params", {}) or {} standard_logging_payload: StandardLoggingPayload = kwargs.get( "standard_logging_object", {} ) - proxy_server_request = litellm_params.get("proxy_server_request") or {} - - end_user_id = proxy_server_request.get("body", {}).get("user", None) + litellm_params = kwargs.get("litellm_params", {}) or {} + end_user_id = get_end_user_id_for_cost_tracking(litellm_params) user_id = standard_logging_payload["metadata"]["user_api_key_user_id"] user_api_key = standard_logging_payload["metadata"]["user_api_key_hash"] user_api_key_alias = standard_logging_payload["metadata"]["user_api_key_alias"] diff --git a/litellm/litellm_core_utils/README.md b/litellm/litellm_core_utils/README.md index 9cd351453..649404129 100644 --- a/litellm/litellm_core_utils/README.md +++ b/litellm/litellm_core_utils/README.md @@ -8,4 +8,5 @@ Core files: - `exception_mapping_utils.py`: utils for mapping exceptions to openai-compatible error types. - `default_encoding.py`: code for loading the default encoding (tiktoken) - `get_llm_provider_logic.py`: code for inferring the LLM provider from a given model name. +- `duration_parser.py`: code for parsing durations - e.g. "1d", "1mo", "10s" diff --git a/litellm/litellm_core_utils/duration_parser.py b/litellm/litellm_core_utils/duration_parser.py new file mode 100644 index 000000000..c8c6bea83 --- /dev/null +++ b/litellm/litellm_core_utils/duration_parser.py @@ -0,0 +1,92 @@ +""" +Helper utilities for parsing durations - 1s, 1d, 10d, 30d, 1mo, 2mo + +duration_in_seconds is used in diff parts of the code base, example +- Router - Provider budget routing +- Proxy - Key, Team Generation +""" + +import re +import time +from datetime import datetime, timedelta +from typing import Tuple + + +def _extract_from_regex(duration: str) -> Tuple[int, str]: + match = re.match(r"(\d+)(mo|[smhd]?)", duration) + + if not match: + raise ValueError("Invalid duration format") + + value, unit = match.groups() + value = int(value) + + return value, unit + + +def get_last_day_of_month(year, month): + # Handle December case + if month == 12: + return 31 + # Next month is January, so subtract a day from March 1st + next_month = datetime(year=year, month=month + 1, day=1) + last_day_of_month = (next_month - timedelta(days=1)).day + return last_day_of_month + + +def duration_in_seconds(duration: str) -> int: + """ + Parameters: + - duration: + - "s" - seconds + - "m" - minutes + - "h" - hours + - "d" - days + - "mo" - months + + Returns time in seconds till when budget needs to be reset + """ + value, unit = _extract_from_regex(duration=duration) + + if unit == "s": + return value + elif unit == "m": + return value * 60 + elif unit == "h": + return value * 3600 + elif unit == "d": + return value * 86400 + elif unit == "mo": + now = time.time() + current_time = datetime.fromtimestamp(now) + + if current_time.month == 12: + target_year = current_time.year + 1 + target_month = 1 + else: + target_year = current_time.year + target_month = current_time.month + value + + # Determine the day to set for next month + target_day = current_time.day + last_day_of_target_month = get_last_day_of_month(target_year, target_month) + + if target_day > last_day_of_target_month: + target_day = last_day_of_target_month + + next_month = datetime( + year=target_year, + month=target_month, + day=target_day, + hour=current_time.hour, + minute=current_time.minute, + second=current_time.second, + microsecond=current_time.microsecond, + ) + + # Calculate the duration until the first day of the next month + duration_until_next_month = next_month - current_time + return int(duration_until_next_month.total_seconds()) + + else: + raise ValueError(f"Unsupported duration unit, passed duration: {duration}") diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 69d6adca4..298e28974 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -934,19 +934,10 @@ class Logging: status="success", ) ) - if self.dynamic_success_callbacks is not None and isinstance( - self.dynamic_success_callbacks, list - ): - callbacks = self.dynamic_success_callbacks - ## keep the internal functions ## - for callback in litellm.success_callback: - if ( - isinstance(callback, CustomLogger) - and "_PROXY_" in callback.__class__.__name__ - ): - callbacks.append(callback) - else: - callbacks = litellm.success_callback + callbacks = get_combined_callback_list( + dynamic_success_callbacks=self.dynamic_success_callbacks, + global_callbacks=litellm.success_callback, + ) ## REDACT MESSAGES ## result = redact_message_input_output_from_logging( @@ -1368,8 +1359,11 @@ class Logging: and customLogger is not None ): # custom logger functions print_verbose( - "success callbacks: Running Custom Callback Function" + "success callbacks: Running Custom Callback Function - {}".format( + callback + ) ) + customLogger.log_event( kwargs=self.model_call_details, response_obj=result, @@ -1466,21 +1460,10 @@ class Logging: status="success", ) ) - if self.dynamic_async_success_callbacks is not None and isinstance( - self.dynamic_async_success_callbacks, list - ): - callbacks = self.dynamic_async_success_callbacks - ## keep the internal functions ## - for callback in litellm._async_success_callback: - callback_name = "" - if isinstance(callback, CustomLogger): - callback_name = callback.__class__.__name__ - if callable(callback): - callback_name = callback.__name__ - if "_PROXY_" in callback_name: - callbacks.append(callback) - else: - callbacks = litellm._async_success_callback + callbacks = get_combined_callback_list( + dynamic_success_callbacks=self.dynamic_async_success_callbacks, + global_callbacks=litellm._async_success_callback, + ) result = redact_message_input_output_from_logging( model_call_details=( @@ -1747,21 +1730,10 @@ class Logging: start_time=start_time, end_time=end_time, ) - callbacks = [] # init this to empty incase it's not created - - if self.dynamic_failure_callbacks is not None and isinstance( - self.dynamic_failure_callbacks, list - ): - callbacks = self.dynamic_failure_callbacks - ## keep the internal functions ## - for callback in litellm.failure_callback: - if ( - isinstance(callback, CustomLogger) - and "_PROXY_" in callback.__class__.__name__ - ): - callbacks.append(callback) - else: - callbacks = litellm.failure_callback + callbacks = get_combined_callback_list( + dynamic_success_callbacks=self.dynamic_failure_callbacks, + global_callbacks=litellm.failure_callback, + ) result = None # result sent to all loggers, init this to None incase it's not created @@ -1944,21 +1916,10 @@ class Logging: end_time=end_time, ) - callbacks = [] # init this to empty incase it's not created - - if self.dynamic_async_failure_callbacks is not None and isinstance( - self.dynamic_async_failure_callbacks, list - ): - callbacks = self.dynamic_async_failure_callbacks - ## keep the internal functions ## - for callback in litellm._async_failure_callback: - if ( - isinstance(callback, CustomLogger) - and "_PROXY_" in callback.__class__.__name__ - ): - callbacks.append(callback) - else: - callbacks = litellm._async_failure_callback + callbacks = get_combined_callback_list( + dynamic_success_callbacks=self.dynamic_async_failure_callbacks, + global_callbacks=litellm._async_failure_callback, + ) result = None # result sent to all loggers, init this to None incase it's not created for callback in callbacks: @@ -2359,6 +2320,7 @@ def _init_custom_logger_compatible_class( # noqa: PLR0915 _in_memory_loggers.append(_mlflow_logger) return _mlflow_logger # type: ignore + def get_custom_logger_compatible_class( logging_integration: litellm._custom_logger_compatible_callbacks_literal, ) -> Optional[CustomLogger]: @@ -2949,3 +2911,11 @@ def modify_integration(integration_name, integration_params): if integration_name == "supabase": if "table_name" in integration_params: Supabase.supabase_table_name = integration_params["table_name"] + + +def get_combined_callback_list( + dynamic_success_callbacks: Optional[List], global_callbacks: List +) -> List: + if dynamic_success_callbacks is None: + return global_callbacks + return list(set(dynamic_success_callbacks + global_callbacks)) diff --git a/litellm/llms/AzureOpenAI/azure.py b/litellm/llms/AzureOpenAI/azure.py index 39dea14e2..24303ef2f 100644 --- a/litellm/llms/AzureOpenAI/azure.py +++ b/litellm/llms/AzureOpenAI/azure.py @@ -12,7 +12,11 @@ from typing_extensions import overload import litellm from litellm.caching.caching import DualCache from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.types.utils import EmbeddingResponse from litellm.utils import ( CustomStreamWrapper, @@ -977,7 +981,10 @@ class AzureChatCompletion(BaseLLM): else: _params["timeout"] = httpx.Timeout(timeout=600.0, connect=5.0) - async_handler = AsyncHTTPHandler(**_params) # type: ignore + async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.AZURE, + params=_params, + ) else: async_handler = client # type: ignore @@ -1521,7 +1528,8 @@ class AzureChatCompletion(BaseLLM): prompt: Optional[str] = None, ) -> dict: client_session = ( - litellm.aclient_session or httpx.AsyncClient() + litellm.aclient_session + or get_async_httpx_client(llm_provider=litellm.LlmProviders.AZURE).client ) # handle dall-e-2 calls if "gateway.ai.cloudflare.com" in api_base: diff --git a/litellm/llms/OpenAI/openai.py b/litellm/llms/OpenAI/openai.py index 7d701d26c..057340b51 100644 --- a/litellm/llms/OpenAI/openai.py +++ b/litellm/llms/OpenAI/openai.py @@ -18,6 +18,7 @@ import litellm from litellm import LlmProviders from litellm._logging import verbose_logger from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.custom_httpx.http_handler import _DEFAULT_TTL_FOR_HTTPX_CLIENTS from litellm.secret_managers.main import get_secret_str from litellm.types.utils import ProviderField from litellm.utils import ( @@ -562,8 +563,9 @@ class OpenAIChatCompletion(BaseLLM): _cache_key = f"hashed_api_key={hashed_api_key},api_base={api_base},timeout={timeout},max_retries={max_retries},organization={organization},is_async={is_async}" - if _cache_key in litellm.in_memory_llm_clients_cache: - return litellm.in_memory_llm_clients_cache[_cache_key] + _cached_client = litellm.in_memory_llm_clients_cache.get_cache(_cache_key) + if _cached_client: + return _cached_client if is_async: _new_client: Union[OpenAI, AsyncOpenAI] = AsyncOpenAI( api_key=api_key, @@ -584,7 +586,11 @@ class OpenAIChatCompletion(BaseLLM): ) ## SAVE CACHE KEY - litellm.in_memory_llm_clients_cache[_cache_key] = _new_client + litellm.in_memory_llm_clients_cache.set_cache( + key=_cache_key, + value=_new_client, + ttl=_DEFAULT_TTL_FOR_HTTPX_CLIENTS, + ) return _new_client else: diff --git a/litellm/llms/anthropic/chat/handler.py b/litellm/llms/anthropic/chat/handler.py index 86b1117ab..be46051c6 100644 --- a/litellm/llms/anthropic/chat/handler.py +++ b/litellm/llms/anthropic/chat/handler.py @@ -779,3 +779,32 @@ class ModelResponseIterator: raise StopAsyncIteration except ValueError as e: raise RuntimeError(f"Error parsing chunk: {e},\nReceived chunk: {chunk}") + + def convert_str_chunk_to_generic_chunk(self, chunk: str) -> GenericStreamingChunk: + """ + Convert a string chunk to a GenericStreamingChunk + + Note: This is used for Anthropic pass through streaming logging + + We can move __anext__, and __next__ to use this function since it's common logic. + Did not migrate them to minmize changes made in 1 PR. + """ + str_line = chunk + if isinstance(chunk, bytes): # Handle binary data + str_line = chunk.decode("utf-8") # Convert bytes to string + index = str_line.find("data:") + if index != -1: + str_line = str_line[index:] + + if str_line.startswith("data:"): + data_json = json.loads(str_line[5:]) + return self.chunk_parser(chunk=data_json) + else: + return GenericStreamingChunk( + text="", + is_finished=False, + finish_reason="", + usage=None, + index=0, + tool_use=None, + ) diff --git a/litellm/llms/anthropic/completion.py b/litellm/llms/anthropic/completion.py index 89a50db6a..dc06401d6 100644 --- a/litellm/llms/anthropic/completion.py +++ b/litellm/llms/anthropic/completion.py @@ -13,7 +13,11 @@ import httpx import requests import litellm -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.utils import CustomStreamWrapper, ModelResponse, Usage from ..base import BaseLLM @@ -162,7 +166,10 @@ class AnthropicTextCompletion(BaseLLM): client=None, ): if client is None: - client = AsyncHTTPHandler(timeout=httpx.Timeout(timeout=600.0, connect=5.0)) + client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.ANTHROPIC, + params={"timeout": httpx.Timeout(timeout=600.0, connect=5.0)}, + ) response = await client.post(api_base, headers=headers, data=json.dumps(data)) @@ -198,7 +205,10 @@ class AnthropicTextCompletion(BaseLLM): client=None, ): if client is None: - client = AsyncHTTPHandler(timeout=httpx.Timeout(timeout=600.0, connect=5.0)) + client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.ANTHROPIC, + params={"timeout": httpx.Timeout(timeout=600.0, connect=5.0)}, + ) response = await client.post(api_base, headers=headers, data=json.dumps(data)) diff --git a/litellm/llms/azure_ai/embed/handler.py b/litellm/llms/azure_ai/embed/handler.py index 638a77479..2946a84dd 100644 --- a/litellm/llms/azure_ai/embed/handler.py +++ b/litellm/llms/azure_ai/embed/handler.py @@ -74,7 +74,10 @@ class AzureAIEmbedding(OpenAIChatCompletion): client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, ) -> EmbeddingResponse: if client is None or not isinstance(client, AsyncHTTPHandler): - client = AsyncHTTPHandler(timeout=timeout, concurrent_limit=1) + client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.AZURE_AI, + params={"timeout": timeout}, + ) url = "{}/images/embeddings".format(api_base) diff --git a/litellm/llms/azure_ai/rerank/handler.py b/litellm/llms/azure_ai/rerank/handler.py index a67c893f2..60edfd296 100644 --- a/litellm/llms/azure_ai/rerank/handler.py +++ b/litellm/llms/azure_ai/rerank/handler.py @@ -4,6 +4,7 @@ import httpx from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.llms.cohere.rerank import CohereRerank +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.types.rerank import RerankResponse @@ -73,6 +74,7 @@ class AzureAIRerank(CohereRerank): return_documents: Optional[bool] = True, max_chunks_per_doc: Optional[int] = None, _is_async: Optional[bool] = False, + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, ) -> RerankResponse: if headers is None: diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py index 6c08758dd..23ee97a47 100644 --- a/litellm/llms/bedrock/chat/converse_transformation.py +++ b/litellm/llms/bedrock/chat/converse_transformation.py @@ -458,7 +458,7 @@ class AmazonConverseConfig: """ Abbreviations of regions AWS Bedrock supports for cross region inference """ - return ["us", "eu"] + return ["us", "eu", "apac"] def _get_base_model(self, model: str) -> str: """ diff --git a/litellm/llms/clarifai.py b/litellm/llms/clarifai.py index 2011c0bee..61d445423 100644 --- a/litellm/llms/clarifai.py +++ b/litellm/llms/clarifai.py @@ -9,7 +9,10 @@ import httpx import requests import litellm -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + get_async_httpx_client, +) from litellm.utils import Choices, CustomStreamWrapper, Message, ModelResponse, Usage from .prompt_templates.factory import custom_prompt, prompt_factory @@ -185,7 +188,10 @@ async def async_completion( headers={}, ): - async_handler = AsyncHTTPHandler(timeout=httpx.Timeout(timeout=600.0, connect=5.0)) + async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.CLARIFAI, + params={"timeout": 600.0}, + ) response = await async_handler.post( url=model, headers=headers, data=json.dumps(data) ) diff --git a/litellm/llms/cohere/embed/handler.py b/litellm/llms/cohere/embed/handler.py index 95cbec225..afeba10b5 100644 --- a/litellm/llms/cohere/embed/handler.py +++ b/litellm/llms/cohere/embed/handler.py @@ -11,7 +11,11 @@ import requests # type: ignore import litellm from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.types.llms.bedrock import CohereEmbeddingRequest from litellm.utils import Choices, Message, ModelResponse, Usage @@ -70,8 +74,12 @@ async def async_embedding( }, ) ## COMPLETION CALL + if client is None: - client = AsyncHTTPHandler(concurrent_limit=1, timeout=timeout) + client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.COHERE, + params={"timeout": timeout}, + ) try: response = await client.post(api_base, headers=headers, data=json.dumps(data)) @@ -144,6 +152,11 @@ def embedding( api_key=api_key, headers=headers, encoding=encoding, + client=( + client + if client is not None and isinstance(client, AsyncHTTPHandler) + else None + ), ) ## LOGGING diff --git a/litellm/llms/cohere/rerank.py b/litellm/llms/cohere/rerank.py index 022ffc6f9..8de2dfbb4 100644 --- a/litellm/llms/cohere/rerank.py +++ b/litellm/llms/cohere/rerank.py @@ -6,10 +6,14 @@ LiteLLM supports the re rank API format, no paramter transformation occurs from typing import Any, Dict, List, Optional, Union +import httpx + import litellm from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.llms.base import BaseLLM from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, _get_httpx_client, get_async_httpx_client, ) @@ -34,6 +38,23 @@ class CohereRerank(BaseLLM): # Merge other headers, overriding any default ones except Authorization return {**default_headers, **headers} + def ensure_rerank_endpoint(self, api_base: str) -> str: + """ + Ensures the `/v1/rerank` endpoint is appended to the given `api_base`. + If `/v1/rerank` is already present, the original URL is returned. + + :param api_base: The base API URL. + :return: A URL with `/v1/rerank` appended if missing. + """ + # Parse the base URL to ensure proper structure + url = httpx.URL(api_base) + + # Check if the URL already ends with `/v1/rerank` + if not url.path.endswith("/v1/rerank"): + url = url.copy_with(path=f"{url.path.rstrip('/')}/v1/rerank") + + return str(url) + def rerank( self, model: str, @@ -48,9 +69,10 @@ class CohereRerank(BaseLLM): return_documents: Optional[bool] = True, max_chunks_per_doc: Optional[int] = None, _is_async: Optional[bool] = False, # New parameter + client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, ) -> RerankResponse: headers = self.validate_environment(api_key=api_key, headers=headers) - + api_base = self.ensure_rerank_endpoint(api_base) request_data = RerankRequest( model=model, query=query, @@ -76,9 +98,13 @@ class CohereRerank(BaseLLM): if _is_async: return self.async_rerank(request_data=request_data, api_key=api_key, api_base=api_base, headers=headers) # type: ignore # Call async method - client = _get_httpx_client() + if client is not None and isinstance(client, HTTPHandler): + client = client + else: + client = _get_httpx_client() + response = client.post( - api_base, + url=api_base, headers=headers, json=request_data_dict, ) @@ -100,10 +126,13 @@ class CohereRerank(BaseLLM): api_key: str, api_base: str, headers: dict, + client: Optional[AsyncHTTPHandler] = None, ) -> RerankResponse: request_data_dict = request_data.dict(exclude_none=True) - client = get_async_httpx_client(llm_provider=litellm.LlmProviders.COHERE) + client = client or get_async_httpx_client( + llm_provider=litellm.LlmProviders.COHERE + ) response = await client.post( api_base, diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py index 020af7e90..f4d20f8fb 100644 --- a/litellm/llms/custom_httpx/http_handler.py +++ b/litellm/llms/custom_httpx/http_handler.py @@ -7,8 +7,8 @@ import httpx from httpx import USE_CLIENT_DEFAULT, AsyncHTTPTransport, HTTPTransport import litellm - -from .types import httpxSpecialProvider +from litellm.caching import InMemoryCache +from litellm.types.llms.custom_http import * if TYPE_CHECKING: from litellm import LlmProviders @@ -26,6 +26,63 @@ headers = { # https://www.python-httpx.org/advanced/timeouts _DEFAULT_TIMEOUT = httpx.Timeout(timeout=5.0, connect=5.0) +_DEFAULT_TTL_FOR_HTTPX_CLIENTS = 3600 # 1 hour, re-use the same httpx client for 1 hour + +import re + + +def mask_sensitive_info(error_message): + # Find the start of the key parameter + if isinstance(error_message, str): + key_index = error_message.find("key=") + else: + return error_message + + # If key is found + if key_index != -1: + # Find the end of the key parameter (next & or end of string) + next_param = error_message.find("&", key_index) + + if next_param == -1: + # If no more parameters, mask until the end of the string + masked_message = error_message[: key_index + 4] + "[REDACTED_API_KEY]" + else: + # Replace the key with redacted value, keeping other parameters + masked_message = ( + error_message[: key_index + 4] + + "[REDACTED_API_KEY]" + + error_message[next_param:] + ) + + return masked_message + + return error_message + + +class MaskedHTTPStatusError(httpx.HTTPStatusError): + def __init__( + self, original_error, message: Optional[str] = None, text: Optional[str] = None + ): + # Create a new error with the masked URL + masked_url = mask_sensitive_info(str(original_error.request.url)) + # Create a new error that looks like the original, but with a masked URL + + super().__init__( + message=original_error.message, + request=httpx.Request( + method=original_error.request.method, + url=masked_url, + headers=original_error.request.headers, + content=original_error.request.content, + ), + response=httpx.Response( + status_code=original_error.response.status_code, + content=original_error.response.content, + headers=original_error.response.headers, + ), + ) + self.message = message + self.text = text class AsyncHTTPHandler: @@ -154,13 +211,16 @@ class AsyncHTTPHandler: headers=headers, ) except httpx.HTTPStatusError as e: - setattr(e, "status_code", e.response.status_code) + if stream is True: setattr(e, "message", await e.response.aread()) setattr(e, "text", await e.response.aread()) else: - setattr(e, "message", e.response.text) - setattr(e, "text", e.response.text) + setattr(e, "message", mask_sensitive_info(e.response.text)) + setattr(e, "text", mask_sensitive_info(e.response.text)) + + setattr(e, "status_code", e.response.status_code) + raise e except Exception as e: raise e @@ -398,11 +458,17 @@ class HTTPHandler: llm_provider="litellm-httpx-handler", ) except httpx.HTTPStatusError as e: - setattr(e, "status_code", e.response.status_code) + if stream is True: - setattr(e, "message", e.response.read()) + setattr(e, "message", mask_sensitive_info(e.response.read())) + setattr(e, "text", mask_sensitive_info(e.response.read())) else: - setattr(e, "message", e.response.text) + error_text = mask_sensitive_info(e.response.text) + setattr(e, "message", error_text) + setattr(e, "text", error_text) + + setattr(e, "status_code", e.response.status_code) + raise e except Exception as e: raise e @@ -476,8 +542,9 @@ def get_async_httpx_client( pass _cache_key_name = "async_httpx_client" + _params_key_name + llm_provider - if _cache_key_name in litellm.in_memory_llm_clients_cache: - return litellm.in_memory_llm_clients_cache[_cache_key_name] + _cached_client = litellm.in_memory_llm_clients_cache.get_cache(_cache_key_name) + if _cached_client: + return _cached_client if params is not None: _new_client = AsyncHTTPHandler(**params) @@ -485,7 +552,11 @@ def get_async_httpx_client( _new_client = AsyncHTTPHandler( timeout=httpx.Timeout(timeout=600.0, connect=5.0) ) - litellm.in_memory_llm_clients_cache[_cache_key_name] = _new_client + litellm.in_memory_llm_clients_cache.set_cache( + key=_cache_key_name, + value=_new_client, + ttl=_DEFAULT_TTL_FOR_HTTPX_CLIENTS, + ) return _new_client @@ -505,13 +576,18 @@ def _get_httpx_client(params: Optional[dict] = None) -> HTTPHandler: pass _cache_key_name = "httpx_client" + _params_key_name - if _cache_key_name in litellm.in_memory_llm_clients_cache: - return litellm.in_memory_llm_clients_cache[_cache_key_name] + _cached_client = litellm.in_memory_llm_clients_cache.get_cache(_cache_key_name) + if _cached_client: + return _cached_client if params is not None: _new_client = HTTPHandler(**params) else: _new_client = HTTPHandler(timeout=httpx.Timeout(timeout=600.0, connect=5.0)) - litellm.in_memory_llm_clients_cache[_cache_key_name] = _new_client + litellm.in_memory_llm_clients_cache.set_cache( + key=_cache_key_name, + value=_new_client, + ttl=_DEFAULT_TTL_FOR_HTTPX_CLIENTS, + ) return _new_client diff --git a/litellm/llms/custom_httpx/types.py b/litellm/llms/custom_httpx/types.py deleted file mode 100644 index 8e6ad0eda..000000000 --- a/litellm/llms/custom_httpx/types.py +++ /dev/null @@ -1,11 +0,0 @@ -from enum import Enum - -import litellm - - -class httpxSpecialProvider(str, Enum): - LoggingCallback = "logging_callback" - GuardrailCallback = "guardrail_callback" - Caching = "caching" - Oauth2Check = "oauth2_check" - SecretManager = "secret_manager" diff --git a/litellm/llms/databricks/chat.py b/litellm/llms/databricks/chat.py index 79e885646..e752f4d98 100644 --- a/litellm/llms/databricks/chat.py +++ b/litellm/llms/databricks/chat.py @@ -393,7 +393,10 @@ class DatabricksChatCompletion(BaseLLM): if timeout is None: timeout = httpx.Timeout(timeout=600.0, connect=5.0) - self.async_handler = AsyncHTTPHandler(timeout=timeout) + self.async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.DATABRICKS, + params={"timeout": timeout}, + ) try: response = await self.async_handler.post( @@ -610,7 +613,10 @@ class DatabricksChatCompletion(BaseLLM): response = None try: if client is None or isinstance(client, AsyncHTTPHandler): - self.async_client = AsyncHTTPHandler(timeout=timeout) # type: ignore + self.async_client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.DATABRICKS, + params={"timeout": timeout}, + ) else: self.async_client = client diff --git a/litellm/llms/fine_tuning_apis/vertex_ai.py b/litellm/llms/fine_tuning_apis/vertex_ai.py index 11d052191..fd418103e 100644 --- a/litellm/llms/fine_tuning_apis/vertex_ai.py +++ b/litellm/llms/fine_tuning_apis/vertex_ai.py @@ -5,9 +5,14 @@ from typing import Any, Coroutine, Literal, Optional, Union import httpx from openai.types.fine_tuning.fine_tuning_job import FineTuningJob, Hyperparameters +import litellm from litellm._logging import verbose_logger from litellm.llms.base import BaseLLM -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import ( VertexLLM, ) @@ -26,8 +31,9 @@ class VertexFineTuningAPI(VertexLLM): def __init__(self) -> None: super().__init__() - self.async_handler = AsyncHTTPHandler( - timeout=httpx.Timeout(timeout=600.0, connect=5.0) + self.async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.VERTEX_AI, + params={"timeout": 600.0}, ) def convert_response_created_at(self, response: ResponseTuningJob): diff --git a/litellm/llms/huggingface_restapi.py b/litellm/llms/huggingface_restapi.py index 907d72a60..8b45f1ae7 100644 --- a/litellm/llms/huggingface_restapi.py +++ b/litellm/llms/huggingface_restapi.py @@ -263,7 +263,11 @@ def get_hf_task_for_model(model: str) -> Tuple[hf_tasks, str]: return "text-generation-inference", model # default to tgi -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) def get_hf_task_embedding_for_model( @@ -301,7 +305,9 @@ async def async_get_hf_task_embedding_for_model( task_type, hf_tasks_embeddings ) ) - http_client = AsyncHTTPHandler(concurrent_limit=1) + http_client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.HUGGINGFACE, + ) model_info = await http_client.get(url=api_base) @@ -1067,7 +1073,9 @@ class Huggingface(BaseLLM): ) ## COMPLETION CALL if client is None: - client = AsyncHTTPHandler(concurrent_limit=1) + client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.HUGGINGFACE, + ) response = await client.post(api_base, headers=headers, data=json.dumps(data)) diff --git a/litellm/llms/ollama.py b/litellm/llms/ollama.py index 896b93be5..e9dd2b53f 100644 --- a/litellm/llms/ollama.py +++ b/litellm/llms/ollama.py @@ -14,6 +14,7 @@ import requests # type: ignore import litellm from litellm import verbose_logger +from litellm.llms.custom_httpx.http_handler import get_async_httpx_client from litellm.secret_managers.main import get_secret_str from litellm.types.utils import ModelInfo, ProviderField, StreamingChoices @@ -456,7 +457,10 @@ def ollama_completion_stream(url, data, logging_obj): async def ollama_async_streaming(url, data, model_response, encoding, logging_obj): try: - client = httpx.AsyncClient() + _async_http_client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.OLLAMA + ) + client = _async_http_client.client async with client.stream( url=f"{url}", json=data, method="POST", timeout=litellm.request_timeout ) as response: diff --git a/litellm/llms/ollama_chat.py b/litellm/llms/ollama_chat.py index 536f766e0..ce0df139d 100644 --- a/litellm/llms/ollama_chat.py +++ b/litellm/llms/ollama_chat.py @@ -13,6 +13,7 @@ from pydantic import BaseModel import litellm from litellm import verbose_logger +from litellm.llms.custom_httpx.http_handler import get_async_httpx_client from litellm.types.llms.ollama import OllamaToolCall, OllamaToolCallFunction from litellm.types.llms.openai import ChatCompletionAssistantToolCall from litellm.types.utils import StreamingChoices @@ -445,7 +446,10 @@ async def ollama_async_streaming( url, api_key, data, model_response, encoding, logging_obj ): try: - client = httpx.AsyncClient() + _async_http_client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.OLLAMA + ) + client = _async_http_client.client _request = { "url": f"{url}", "json": data, diff --git a/litellm/llms/openai_like/embedding/handler.py b/litellm/llms/openai_like/embedding/handler.py index 7ddf43cb8..e786b5db8 100644 --- a/litellm/llms/openai_like/embedding/handler.py +++ b/litellm/llms/openai_like/embedding/handler.py @@ -45,7 +45,10 @@ class OpenAILikeEmbeddingHandler(OpenAILikeBase): response = None try: if client is None or isinstance(client, AsyncHTTPHandler): - self.async_client = AsyncHTTPHandler(timeout=timeout) # type: ignore + self.async_client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.OPENAI, + params={"timeout": timeout}, + ) else: self.async_client = client diff --git a/litellm/llms/predibase.py b/litellm/llms/predibase.py index 96796f9dc..e80964551 100644 --- a/litellm/llms/predibase.py +++ b/litellm/llms/predibase.py @@ -19,7 +19,10 @@ import litellm.litellm_core_utils import litellm.litellm_core_utils.litellm_logging from litellm import verbose_logger from litellm.litellm_core_utils.core_helpers import map_finish_reason -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + get_async_httpx_client, +) from litellm.utils import Choices, CustomStreamWrapper, Message, ModelResponse, Usage from .base import BaseLLM @@ -549,7 +552,10 @@ class PredibaseChatCompletion(BaseLLM): headers={}, ) -> ModelResponse: - async_handler = AsyncHTTPHandler(timeout=httpx.Timeout(timeout=timeout)) + async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.PREDIBASE, + params={"timeout": timeout}, + ) try: response = await async_handler.post( api_base, headers=headers, data=json.dumps(data) diff --git a/litellm/llms/prompt_templates/factory.py b/litellm/llms/prompt_templates/factory.py index 45b7a6c5b..bfd35ca47 100644 --- a/litellm/llms/prompt_templates/factory.py +++ b/litellm/llms/prompt_templates/factory.py @@ -33,6 +33,7 @@ from litellm.types.llms.openai import ( ChatCompletionAssistantToolCall, ChatCompletionFunctionMessage, ChatCompletionImageObject, + ChatCompletionImageUrlObject, ChatCompletionTextObject, ChatCompletionToolCallFunctionChunk, ChatCompletionToolMessage, @@ -681,6 +682,27 @@ def construct_tool_use_system_prompt( return tool_use_system_prompt +def convert_generic_image_chunk_to_openai_image_obj( + image_chunk: GenericImageParsingChunk, +) -> str: + """ + Convert a generic image chunk to an OpenAI image object. + + Input: + GenericImageParsingChunk( + type="base64", + media_type="image/jpeg", + data="...", + ) + + Return: + "data:image/jpeg;base64,{base64_image}" + """ + return "data:{};{},{}".format( + image_chunk["media_type"], image_chunk["type"], image_chunk["data"] + ) + + def convert_to_anthropic_image_obj(openai_image_url: str) -> GenericImageParsingChunk: """ Input: @@ -706,6 +728,7 @@ def convert_to_anthropic_image_obj(openai_image_url: str) -> GenericImageParsing data=base64_data, ) except Exception as e: + traceback.print_exc() if "Error: Unable to fetch image from URL" in str(e): raise e raise Exception( @@ -1136,15 +1159,44 @@ def convert_to_anthropic_tool_result( ] } """ - content_str: str = "" + anthropic_content: Union[ + str, + List[Union[AnthropicMessagesToolResultContent, AnthropicMessagesImageParam]], + ] = "" if isinstance(message["content"], str): - content_str = message["content"] + anthropic_content = message["content"] elif isinstance(message["content"], List): content_list = message["content"] + anthropic_content_list: List[ + Union[AnthropicMessagesToolResultContent, AnthropicMessagesImageParam] + ] = [] for content in content_list: if content["type"] == "text": - content_str += content["text"] + anthropic_content_list.append( + AnthropicMessagesToolResultContent( + type="text", + text=content["text"], + ) + ) + elif content["type"] == "image_url": + if isinstance(content["image_url"], str): + image_chunk = convert_to_anthropic_image_obj(content["image_url"]) + else: + image_chunk = convert_to_anthropic_image_obj( + content["image_url"]["url"] + ) + anthropic_content_list.append( + AnthropicMessagesImageParam( + type="image", + source=AnthropicContentParamSource( + type="base64", + media_type=image_chunk["media_type"], + data=image_chunk["data"], + ), + ) + ) + anthropic_content = anthropic_content_list anthropic_tool_result: Optional[AnthropicMessagesToolResultParam] = None ## PROMPT CACHING CHECK ## cache_control = message.get("cache_control", None) @@ -1155,14 +1207,14 @@ def convert_to_anthropic_tool_result( # We can't determine from openai message format whether it's a successful or # error call result so default to the successful result template anthropic_tool_result = AnthropicMessagesToolResultParam( - type="tool_result", tool_use_id=tool_call_id, content=content_str + type="tool_result", tool_use_id=tool_call_id, content=anthropic_content ) if message["role"] == "function": function_message: ChatCompletionFunctionMessage = message tool_call_id = function_message.get("tool_call_id") or str(uuid.uuid4()) anthropic_tool_result = AnthropicMessagesToolResultParam( - type="tool_result", tool_use_id=tool_call_id, content=content_str + type="tool_result", tool_use_id=tool_call_id, content=anthropic_content ) if anthropic_tool_result is None: diff --git a/litellm/llms/replicate.py b/litellm/llms/replicate.py index 094110234..2e9bbb333 100644 --- a/litellm/llms/replicate.py +++ b/litellm/llms/replicate.py @@ -9,7 +9,10 @@ import httpx # type: ignore import requests # type: ignore import litellm -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + get_async_httpx_client, +) from litellm.utils import CustomStreamWrapper, ModelResponse, Usage from .prompt_templates.factory import custom_prompt, prompt_factory @@ -325,7 +328,7 @@ def handle_prediction_response_streaming(prediction_url, api_token, print_verbos async def async_handle_prediction_response_streaming( prediction_url, api_token, print_verbose ): - http_handler = AsyncHTTPHandler(concurrent_limit=1) + http_handler = get_async_httpx_client(llm_provider=litellm.LlmProviders.REPLICATE) previous_output = "" output_string = "" @@ -560,7 +563,9 @@ async def async_completion( logging_obj, print_verbose, ) -> Union[ModelResponse, CustomStreamWrapper]: - http_handler = AsyncHTTPHandler(concurrent_limit=1) + http_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.REPLICATE, + ) prediction_url = await async_start_prediction( version_id, input_data, diff --git a/litellm/llms/text_completion_codestral.py b/litellm/llms/text_completion_codestral.py index 21582d26c..d3c1ae3cb 100644 --- a/litellm/llms/text_completion_codestral.py +++ b/litellm/llms/text_completion_codestral.py @@ -18,7 +18,10 @@ import litellm from litellm import verbose_logger from litellm.litellm_core_utils.core_helpers import map_finish_reason from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + get_async_httpx_client, +) from litellm.types.llms.databricks import GenericStreamingChunk from litellm.utils import ( Choices, @@ -479,8 +482,9 @@ class CodestralTextCompletion(BaseLLM): headers={}, ) -> TextCompletionResponse: - async_handler = AsyncHTTPHandler( - timeout=httpx.Timeout(timeout=timeout), concurrent_limit=1 + async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.TEXT_COMPLETION_CODESTRAL, + params={"timeout": timeout}, ) try: diff --git a/litellm/llms/triton.py b/litellm/llms/triton.py index be4179ccc..efd0d0a2d 100644 --- a/litellm/llms/triton.py +++ b/litellm/llms/triton.py @@ -8,7 +8,11 @@ import httpx # type: ignore import requests # type: ignore import litellm -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.utils import ( Choices, CustomStreamWrapper, @@ -50,8 +54,8 @@ class TritonChatCompletion(BaseLLM): logging_obj: Any, api_key: Optional[str] = None, ) -> EmbeddingResponse: - async_handler = AsyncHTTPHandler( - timeout=httpx.Timeout(timeout=600.0, connect=5.0) + async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.TRITON, params={"timeout": 600.0} ) response = await async_handler.post(url=api_base, data=json.dumps(data)) @@ -261,7 +265,9 @@ class TritonChatCompletion(BaseLLM): model_response, type_of_model, ) -> ModelResponse: - handler = AsyncHTTPHandler() + handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.TRITON, params={"timeout": 600.0} + ) if stream: return self._ahandle_stream( # type: ignore handler, api_base, data_for_triton, model, logging_obj diff --git a/litellm/llms/vertex_ai_and_google_ai_studio/gemini/transformation.py b/litellm/llms/vertex_ai_and_google_ai_studio/gemini/transformation.py index f828d93c8..c9fe6e3f4 100644 --- a/litellm/llms/vertex_ai_and_google_ai_studio/gemini/transformation.py +++ b/litellm/llms/vertex_ai_and_google_ai_studio/gemini/transformation.py @@ -107,6 +107,10 @@ def _get_image_mime_type_from_url(url: str) -> Optional[str]: return "image/png" elif url.endswith(".webp"): return "image/webp" + elif url.endswith(".mp4"): + return "video/mp4" + elif url.endswith(".pdf"): + return "application/pdf" return None @@ -294,7 +298,12 @@ def _transform_request_body( optional_params = {k: v for k, v in optional_params.items() if k not in remove_keys} try: - content = _gemini_convert_messages_with_history(messages=messages) + if custom_llm_provider == "gemini": + content = litellm.GoogleAIStudioGeminiConfig._transform_messages( + messages=messages + ) + else: + content = litellm.VertexGeminiConfig._transform_messages(messages=messages) tools: Optional[Tools] = optional_params.pop("tools", None) tool_choice: Optional[ToolConfig] = optional_params.pop("tool_choice", None) safety_settings: Optional[List[SafetSettingsConfig]] = optional_params.pop( diff --git a/litellm/llms/vertex_ai_and_google_ai_studio/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai_and_google_ai_studio/gemini/vertex_and_google_ai_studio_gemini.py index 39c63dbb3..4287ed1bc 100644 --- a/litellm/llms/vertex_ai_and_google_ai_studio/gemini/vertex_and_google_ai_studio_gemini.py +++ b/litellm/llms/vertex_ai_and_google_ai_studio/gemini/vertex_and_google_ai_studio_gemini.py @@ -35,7 +35,12 @@ from litellm.llms.custom_httpx.http_handler import ( HTTPHandler, get_async_httpx_client, ) +from litellm.llms.prompt_templates.factory import ( + convert_generic_image_chunk_to_openai_image_obj, + convert_to_anthropic_image_obj, +) from litellm.types.llms.openai import ( + AllMessageValues, ChatCompletionResponseMessage, ChatCompletionToolCallChunk, ChatCompletionToolCallFunctionChunk, @@ -78,6 +83,8 @@ from ..common_utils import ( ) from ..vertex_llm_base import VertexBase from .transformation import ( + _gemini_convert_messages_with_history, + _process_gemini_image, async_transform_request_body, set_headers, sync_transform_request_body, @@ -912,6 +919,10 @@ class VertexGeminiConfig: return model_response + @staticmethod + def _transform_messages(messages: List[AllMessageValues]) -> List[ContentType]: + return _gemini_convert_messages_with_history(messages=messages) + class GoogleAIStudioGeminiConfig( VertexGeminiConfig @@ -1015,6 +1026,32 @@ class GoogleAIStudioGeminiConfig( model, non_default_params, optional_params, drop_params ) + @staticmethod + def _transform_messages(messages: List[AllMessageValues]) -> List[ContentType]: + """ + Google AI Studio Gemini does not support image urls in messages. + """ + for message in messages: + _message_content = message.get("content") + if _message_content is not None and isinstance(_message_content, list): + _parts: List[PartType] = [] + for element in _message_content: + if element.get("type") == "image_url": + img_element = element + _image_url: Optional[str] = None + if isinstance(img_element.get("image_url"), dict): + _image_url = img_element["image_url"].get("url") # type: ignore + else: + _image_url = img_element.get("image_url") # type: ignore + if _image_url and "https://" in _image_url: + image_obj = convert_to_anthropic_image_obj(_image_url) + img_element["image_url"] = ( # type: ignore + convert_generic_image_chunk_to_openai_image_obj( + image_obj + ) + ) + return _gemini_convert_messages_with_history(messages=messages) + async def make_call( client: Optional[AsyncHTTPHandler], @@ -1026,7 +1063,9 @@ async def make_call( logging_obj, ): if client is None: - client = AsyncHTTPHandler() # Create a new client if none provided + client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.VERTEX_AI, + ) try: response = await client.post(api_base, headers=headers, data=data, stream=True) diff --git a/litellm/llms/vertex_ai_and_google_ai_studio/gemini_embeddings/batch_embed_content_handler.py b/litellm/llms/vertex_ai_and_google_ai_studio/gemini_embeddings/batch_embed_content_handler.py index 314e129c2..8e2d1f39a 100644 --- a/litellm/llms/vertex_ai_and_google_ai_studio/gemini_embeddings/batch_embed_content_handler.py +++ b/litellm/llms/vertex_ai_and_google_ai_studio/gemini_embeddings/batch_embed_content_handler.py @@ -7,8 +7,13 @@ from typing import Any, List, Literal, Optional, Union import httpx +import litellm from litellm import EmbeddingResponse -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.types.llms.openai import EmbeddingInput from litellm.types.llms.vertex_ai import ( VertexAIBatchEmbeddingsRequestBody, @@ -150,7 +155,10 @@ class GoogleBatchEmbeddings(VertexLLM): else: _params["timeout"] = httpx.Timeout(timeout=600.0, connect=5.0) - async_handler: AsyncHTTPHandler = AsyncHTTPHandler(**_params) # type: ignore + async_handler: AsyncHTTPHandler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.VERTEX_AI, + params={"timeout": timeout}, + ) else: async_handler = client # type: ignore diff --git a/litellm/llms/vertex_ai_and_google_ai_studio/image_generation/image_generation_handler.py b/litellm/llms/vertex_ai_and_google_ai_studio/image_generation/image_generation_handler.py index 1531464c8..6cb5771e6 100644 --- a/litellm/llms/vertex_ai_and_google_ai_studio/image_generation/image_generation_handler.py +++ b/litellm/llms/vertex_ai_and_google_ai_studio/image_generation/image_generation_handler.py @@ -5,7 +5,11 @@ import httpx from openai.types.image import Image import litellm -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import ( VertexLLM, ) @@ -156,7 +160,10 @@ class VertexImageGeneration(VertexLLM): else: _params["timeout"] = httpx.Timeout(timeout=600.0, connect=5.0) - self.async_handler = AsyncHTTPHandler(**_params) # type: ignore + self.async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.VERTEX_AI, + params={"timeout": timeout}, + ) else: self.async_handler = client # type: ignore diff --git a/litellm/llms/vertex_ai_and_google_ai_studio/multimodal_embeddings/embedding_handler.py b/litellm/llms/vertex_ai_and_google_ai_studio/multimodal_embeddings/embedding_handler.py index d8af891b0..27b77fdd9 100644 --- a/litellm/llms/vertex_ai_and_google_ai_studio/multimodal_embeddings/embedding_handler.py +++ b/litellm/llms/vertex_ai_and_google_ai_studio/multimodal_embeddings/embedding_handler.py @@ -5,7 +5,11 @@ import httpx import litellm from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + get_async_httpx_client, +) from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import ( VertexAIError, VertexLLM, @@ -172,7 +176,10 @@ class VertexMultimodalEmbedding(VertexLLM): if isinstance(timeout, float) or isinstance(timeout, int): timeout = httpx.Timeout(timeout) _params["timeout"] = timeout - client = AsyncHTTPHandler(**_params) # type: ignore + client = get_async_httpx_client( + llm_provider=litellm.LlmProviders.VERTEX_AI, + params={"timeout": timeout}, + ) else: client = client # type: ignore diff --git a/litellm/llms/vertex_ai_and_google_ai_studio/vertex_ai_non_gemini.py b/litellm/llms/vertex_ai_and_google_ai_studio/vertex_ai_non_gemini.py index 80295ec40..829bf6528 100644 --- a/litellm/llms/vertex_ai_and_google_ai_studio/vertex_ai_non_gemini.py +++ b/litellm/llms/vertex_ai_and_google_ai_studio/vertex_ai_non_gemini.py @@ -14,6 +14,7 @@ from pydantic import BaseModel import litellm from litellm._logging import verbose_logger from litellm.litellm_core_utils.core_helpers import map_finish_reason +from litellm.llms.custom_httpx.http_handler import _DEFAULT_TTL_FOR_HTTPX_CLIENTS from litellm.llms.prompt_templates.factory import ( convert_to_anthropic_image_obj, convert_to_gemini_tool_call_invoke, @@ -93,11 +94,15 @@ def _get_client_cache_key( def _get_client_from_cache(client_cache_key: str): - return litellm.in_memory_llm_clients_cache.get(client_cache_key, None) + return litellm.in_memory_llm_clients_cache.get_cache(client_cache_key) def _set_client_in_cache(client_cache_key: str, vertex_llm_model: Any): - litellm.in_memory_llm_clients_cache[client_cache_key] = vertex_llm_model + litellm.in_memory_llm_clients_cache.set_cache( + key=client_cache_key, + value=vertex_llm_model, + ttl=_DEFAULT_TTL_FOR_HTTPX_CLIENTS, + ) def completion( # noqa: PLR0915 diff --git a/litellm/llms/watsonx/completion/handler.py b/litellm/llms/watsonx/completion/handler.py index fda25ba0f..9618f6342 100644 --- a/litellm/llms/watsonx/completion/handler.py +++ b/litellm/llms/watsonx/completion/handler.py @@ -24,7 +24,10 @@ import httpx # type: ignore import requests # type: ignore import litellm -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + get_async_httpx_client, +) from litellm.secret_managers.main import get_secret_str from litellm.types.llms.watsonx import WatsonXAIEndpoint from litellm.utils import EmbeddingResponse, ModelResponse, Usage, map_finish_reason @@ -710,10 +713,13 @@ class RequestManager: if stream: request_params["stream"] = stream try: - self.async_handler = AsyncHTTPHandler( - timeout=httpx.Timeout( - timeout=request_params.pop("timeout", 600.0), connect=5.0 - ), + self.async_handler = get_async_httpx_client( + llm_provider=litellm.LlmProviders.WATSONX, + params={ + "timeout": httpx.Timeout( + timeout=request_params.pop("timeout", 600.0), connect=5.0 + ), + }, ) if "json" in request_params: request_params["data"] = json.dumps(request_params.pop("json", {})) diff --git a/litellm/main.py b/litellm/main.py index 5d433eb36..5095ce518 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -3440,6 +3440,10 @@ def embedding( # noqa: PLR0915 or litellm.openai_key or get_secret_str("OPENAI_API_KEY") ) + + if extra_headers is not None: + optional_params["extra_headers"] = extra_headers + api_type = "openai" api_version = None diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index a56472f7f..ac22871bc 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -2032,7 +2032,6 @@ "tool_use_system_prompt_tokens": 264, "supports_assistant_prefill": true, "supports_prompt_caching": true, - "supports_pdf_input": true, "supports_response_schema": true }, "claude-3-opus-20240229": { @@ -2098,6 +2097,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 159, "supports_assistant_prefill": true, + "supports_pdf_input": true, "supports_prompt_caching": true, "supports_response_schema": true }, @@ -3383,6 +3383,8 @@ "supports_vision": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-001": { @@ -3406,6 +3408,8 @@ "supports_vision": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash": { @@ -3428,6 +3432,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-latest": { @@ -3450,6 +3456,32 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 2000, + "source": "https://ai.google.dev/pricing" + }, + "gemini/gemini-1.5-flash-8b": { + "max_tokens": 8192, + "max_input_tokens": 1048576, + "max_output_tokens": 8192, + "max_images_per_prompt": 3000, + "max_videos_per_prompt": 10, + "max_video_length": 1, + "max_audio_length_hours": 8.4, + "max_audio_per_prompt": 1, + "max_pdf_size_mb": 30, + "input_cost_per_token": 0, + "input_cost_per_token_above_128k_tokens": 0, + "output_cost_per_token": 0, + "output_cost_per_token_above_128k_tokens": 0, + "litellm_provider": "gemini", + "mode": "chat", + "supports_system_messages": true, + "supports_function_calling": true, + "supports_vision": true, + "supports_response_schema": true, + "tpm": 4000000, + "rpm": 4000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-8b-exp-0924": { @@ -3472,6 +3504,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 4000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-exp-1114": { @@ -3494,7 +3528,12 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, - "source": "https://ai.google.dev/pricing" + "tpm": 4000000, + "rpm": 1000, + "source": "https://ai.google.dev/pricing", + "metadata": { + "notes": "Rate limits not documented for gemini-exp-1114. Assuming same as gemini-1.5-pro." + } }, "gemini/gemini-1.5-flash-exp-0827": { "max_tokens": 8192, @@ -3516,6 +3555,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-8b-exp-0827": { @@ -3537,6 +3578,9 @@ "supports_system_messages": true, "supports_function_calling": true, "supports_vision": true, + "supports_response_schema": true, + "tpm": 4000000, + "rpm": 4000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-pro": { @@ -3550,7 +3594,10 @@ "litellm_provider": "gemini", "mode": "chat", "supports_function_calling": true, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" + "rpd": 30000, + "tpm": 120000, + "rpm": 360, + "source": "https://ai.google.dev/gemini-api/docs/models/gemini" }, "gemini/gemini-1.5-pro": { "max_tokens": 8192, @@ -3567,6 +3614,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-002": { @@ -3585,6 +3634,8 @@ "supports_tool_choice": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-001": { @@ -3603,6 +3654,8 @@ "supports_tool_choice": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-exp-0801": { @@ -3620,6 +3673,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-exp-0827": { @@ -3637,6 +3692,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-latest": { @@ -3654,6 +3711,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-pro-vision": { @@ -3668,6 +3727,9 @@ "mode": "chat", "supports_function_calling": true, "supports_vision": true, + "rpd": 30000, + "tpm": 120000, + "rpm": 360, "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" }, "gemini/gemini-gemma-2-27b-it": { diff --git a/litellm/proxy/_experimental/out/404.html b/litellm/proxy/_experimental/out/404.html deleted file mode 100644 index 09dcdd244..000000000 --- a/litellm/proxy/_experimental/out/404.html +++ /dev/null @@ -1 +0,0 @@ -404: This page could not be found.LiteLLM Dashboard

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deployment_name="azure-embedding-model",\n azure_endpoint="http://0.0.0.0:4000",\n api_key="sk-1234",\n api_version="2023-07-01-preview",\n)\n\n\ndocuments = SimpleDirectoryReader("llama_index_data").load_data()\nservice_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)\nindex = VectorStoreIndex.from_documents(documents, service_context=service_context)\n\nquery_engine = index.as_query_engine()\nresponse = query_engine.query("What did the author do growing up?")\nprint(response)\n\n ')})}),(0,t.jsx)(u.Z,{children:(0,t.jsx)(_.Z,{language:"python",children:'\nfrom langchain.chat_models import ChatOpenAI\nfrom langchain.prompts.chat import (\n ChatPromptTemplate,\n HumanMessagePromptTemplate,\n SystemMessagePromptTemplate,\n)\nfrom langchain.schema import HumanMessage, SystemMessage\n\nchat = ChatOpenAI(\n openai_api_base="http://0.0.0.0:4000",\n model = "'.concat(P.model_group,'",\n temperature=0.1\n)\n\nmessages = [\n SystemMessage(\n content="You are a helpful assistant that im using to make a test request to."\n ),\n HumanMessage(\n content="test from litellm. tell me why it\'s amazing in 1 sentence"\n ),\n]\nresponse = chat(messages)\n\nprint(response)\n\n ')})})]})]})]})})]})}}},function(e){e.O(0,[665,936,902,131,684,626,777,971,69,744],function(){return e(e.s=79615)}),_N_E=e.O()}]); \ No newline at end of file diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/webpack-a13477d480030cb3.js b/litellm/proxy/_experimental/out/_next/static/chunks/webpack-b9c71b6f9761a436.js similarity index 98% rename from litellm/proxy/_experimental/out/_next/static/chunks/webpack-a13477d480030cb3.js rename to litellm/proxy/_experimental/out/_next/static/chunks/webpack-b9c71b6f9761a436.js index 9752919c6..d47975f90 100644 --- a/litellm/proxy/_experimental/out/_next/static/chunks/webpack-a13477d480030cb3.js +++ b/litellm/proxy/_experimental/out/_next/static/chunks/webpack-b9c71b6f9761a436.js @@ -1 +1 @@ -!function(){"use strict";var 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+ routing_strategy: usage-based-routing-v2 + #redis_url: "os.environ/REDIS_URL" + redis_host: "os.environ/REDIS_HOST" + redis_port: "os.environ/REDIS_PORT" + +litellm_settings: + cache: true + cache_params: + type: redis + host: "os.environ/REDIS_HOST" + port: "os.environ/REDIS_PORT" + namespace: "litellm.caching" + ttl: 600 +# key_generation_settings: +# team_key_generation: +# allowed_team_member_roles: ["admin"] +# required_params: ["tags"] # require team admins to set tags for cost-tracking when generating a team key +# personal_key_generation: # maps to 'Default Team' on UI +# allowed_user_roles: ["proxy_admin"] \ No newline at end of file diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 8b8dbf2e5..d2b417c9d 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -2,6 +2,7 @@ import enum import json import os import sys +import traceback import uuid from dataclasses import fields from datetime import datetime @@ -12,7 +13,15 @@ from typing_extensions import Annotated, TypedDict from litellm.types.integrations.slack_alerting import AlertType from litellm.types.router import RouterErrors, UpdateRouterConfig -from litellm.types.utils import ProviderField, StandardCallbackDynamicParams +from litellm.types.utils import ( + EmbeddingResponse, + ImageResponse, + ModelResponse, + ProviderField, + StandardCallbackDynamicParams, + StandardPassThroughResponseObject, + TextCompletionResponse, +) if TYPE_CHECKING: from opentelemetry.trace import Span as _Span @@ -882,15 +891,7 @@ class DeleteCustomerRequest(LiteLLMBase): user_ids: List[str] -class Member(LiteLLMBase): - role: Literal[ - LitellmUserRoles.ORG_ADMIN, - LitellmUserRoles.INTERNAL_USER, - LitellmUserRoles.INTERNAL_USER_VIEW_ONLY, - # older Member roles - "admin", - "user", - ] +class MemberBase(LiteLLMBase): user_id: Optional[str] = None user_email: Optional[str] = None @@ -904,6 +905,21 @@ class Member(LiteLLMBase): return values +class Member(MemberBase): + role: Literal[ + "admin", + "user", + ] + + +class OrgMember(MemberBase): + role: Literal[ + LitellmUserRoles.ORG_ADMIN, + LitellmUserRoles.INTERNAL_USER, + LitellmUserRoles.INTERNAL_USER_VIEW_ONLY, + ] + + class TeamBase(LiteLLMBase): team_alias: Optional[str] = None team_id: Optional[str] = None @@ -1969,6 +1985,25 @@ class MemberAddRequest(LiteLLMBase): super().__init__(**data) +class OrgMemberAddRequest(LiteLLMBase): + member: Union[List[OrgMember], OrgMember] + + def __init__(self, **data): + member_data = data.get("member") + if isinstance(member_data, list): + # If member is a list of dictionaries, convert each dictionary to a Member object + members = [OrgMember(**item) for item in member_data] + # Replace member_data with the list of Member objects + data["member"] = members + elif isinstance(member_data, dict): + # If member is a dictionary, convert it to a single Member object + member = OrgMember(**member_data) + # Replace member_data with the single Member object + data["member"] = member + # Call the superclass __init__ method to initialize the object + super().__init__(**data) + + class TeamAddMemberResponse(LiteLLM_TeamTable): updated_users: List[LiteLLM_UserTable] updated_team_memberships: List[LiteLLM_TeamMembership] @@ -2017,7 +2052,7 @@ class TeamMemberUpdateResponse(MemberUpdateResponse): # Organization Member Requests -class OrganizationMemberAddRequest(MemberAddRequest): +class OrganizationMemberAddRequest(OrgMemberAddRequest): organization_id: str max_budget_in_organization: Optional[float] = ( None # Users max budget within the organization @@ -2075,6 +2110,7 @@ class SpecialHeaders(enum.Enum): openai_authorization = "Authorization" azure_authorization = "API-Key" anthropic_authorization = "x-api-key" + google_ai_studio_authorization = "x-goog-api-key" class LitellmDataForBackendLLMCall(TypedDict, total=False): @@ -2133,3 +2169,25 @@ class UserManagementEndpointParamDocStringEnums(str, enum.Enum): spend_doc_str = """Optional[float] - Amount spent by user. Default is 0. Will be updated by proxy whenever user is used.""" team_id_doc_str = """Optional[str] - [DEPRECATED PARAM] The team id of the user. Default is None.""" duration_doc_str = """Optional[str] - Duration for the key auto-created on `/user/new`. Default is None.""" + + +PassThroughEndpointLoggingResultValues = Union[ + ModelResponse, + TextCompletionResponse, + ImageResponse, + EmbeddingResponse, + StandardPassThroughResponseObject, +] + + +class PassThroughEndpointLoggingTypedDict(TypedDict): + result: Optional[PassThroughEndpointLoggingResultValues] + kwargs: dict + + +LiteLLM_ManagementEndpoint_MetadataFields = [ + "model_rpm_limit", + "model_tpm_limit", + "guardrails", + "tags", +] diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 7d29032c6..21a25c8c1 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -60,6 +60,7 @@ def common_checks( # noqa: PLR0915 global_proxy_spend: Optional[float], general_settings: dict, route: str, + llm_router: Optional[litellm.Router], ) -> bool: """ Common checks across jwt + key-based auth. @@ -97,7 +98,12 @@ def common_checks( # noqa: PLR0915 # this means the team has access to all models on the proxy pass # check if the team model is an access_group - elif model_in_access_group(_model, team_object.models) is True: + elif ( + model_in_access_group( + model=_model, team_models=team_object.models, llm_router=llm_router + ) + is True + ): pass elif _model and "*" in _model: pass @@ -373,36 +379,33 @@ async def get_end_user_object( return None -def model_in_access_group(model: str, team_models: Optional[List[str]]) -> bool: +def model_in_access_group( + model: str, team_models: Optional[List[str]], llm_router: Optional[litellm.Router] +) -> bool: from collections import defaultdict - from litellm.proxy.proxy_server import llm_router - if team_models is None: return True if model in team_models: return True - access_groups = defaultdict(list) + access_groups: dict[str, list[str]] = defaultdict(list) if llm_router: - access_groups = llm_router.get_model_access_groups() + access_groups = llm_router.get_model_access_groups(model_name=model) - models_in_current_access_groups = [] if len(access_groups) > 0: # check if token contains any model access groups for idx, m in enumerate( team_models ): # loop token models, if any of them are an access group add the access group if m in access_groups: - # if it is an access group we need to remove it from valid_token.models - models_in_group = access_groups[m] - models_in_current_access_groups.extend(models_in_group) + return True # Filter out models that are access_groups filtered_models = [m for m in team_models if m not in access_groups] - filtered_models += models_in_current_access_groups if model in filtered_models: return True + return False @@ -586,26 +589,63 @@ async def _get_team_db_check(team_id: str, prisma_client: PrismaClient): ) -async def get_team_object( - team_id: str, - prisma_client: Optional[PrismaClient], - user_api_key_cache: DualCache, - parent_otel_span: Optional[Span] = None, - proxy_logging_obj: Optional[ProxyLogging] = None, - check_cache_only: Optional[bool] = None, -) -> LiteLLM_TeamTableCachedObj: - """ - - Check if team id in proxy Team Table - - if valid, return LiteLLM_TeamTable object with defined limits - - if not, then raise an error - """ - if prisma_client is None: - raise Exception( - "No DB Connected. See - https://docs.litellm.ai/docs/proxy/virtual_keys" - ) +async def _get_team_object_from_db(team_id: str, prisma_client: PrismaClient): + return await prisma_client.db.litellm_teamtable.find_unique( + where={"team_id": team_id} + ) - # check if in cache - key = "team_id:{}".format(team_id) + +async def _get_team_object_from_user_api_key_cache( + team_id: str, + prisma_client: PrismaClient, + user_api_key_cache: DualCache, + last_db_access_time: LimitedSizeOrderedDict, + db_cache_expiry: int, + proxy_logging_obj: Optional[ProxyLogging], + key: str, +) -> LiteLLM_TeamTableCachedObj: + db_access_time_key = key + should_check_db = _should_check_db( + key=db_access_time_key, + last_db_access_time=last_db_access_time, + db_cache_expiry=db_cache_expiry, + ) + if should_check_db: + response = await _get_team_db_check( + team_id=team_id, prisma_client=prisma_client + ) + else: + response = None + + if response is None: + raise Exception + + _response = LiteLLM_TeamTableCachedObj(**response.dict()) + # save the team object to cache + await _cache_team_object( + team_id=team_id, + team_table=_response, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) + + # save to db access time + # save to db access time + _update_last_db_access_time( + key=db_access_time_key, + value=_response, + last_db_access_time=last_db_access_time, + ) + + return _response + + +async def _get_team_object_from_cache( + key: str, + proxy_logging_obj: Optional[ProxyLogging], + user_api_key_cache: DualCache, + parent_otel_span: Optional[Span], +) -> Optional[LiteLLM_TeamTableCachedObj]: cached_team_obj: Optional[LiteLLM_TeamTableCachedObj] = None ## CHECK REDIS CACHE ## @@ -613,6 +653,7 @@ async def get_team_object( proxy_logging_obj is not None and proxy_logging_obj.internal_usage_cache.dual_cache ): + cached_team_obj = ( await proxy_logging_obj.internal_usage_cache.dual_cache.async_get_cache( key=key, parent_otel_span=parent_otel_span @@ -628,47 +669,58 @@ async def get_team_object( elif isinstance(cached_team_obj, LiteLLM_TeamTableCachedObj): return cached_team_obj - if check_cache_only: + return None + + +async def get_team_object( + team_id: str, + prisma_client: Optional[PrismaClient], + user_api_key_cache: DualCache, + parent_otel_span: Optional[Span] = None, + proxy_logging_obj: Optional[ProxyLogging] = None, + check_cache_only: Optional[bool] = None, + check_db_only: Optional[bool] = None, +) -> LiteLLM_TeamTableCachedObj: + """ + - Check if team id in proxy Team Table + - if valid, return LiteLLM_TeamTable object with defined limits + - if not, then raise an error + """ + if prisma_client is None: raise Exception( - f"Team doesn't exist in cache + check_cache_only=True. Team={team_id}." + "No DB Connected. See - https://docs.litellm.ai/docs/proxy/virtual_keys" ) + # check if in cache + key = "team_id:{}".format(team_id) + + if not check_db_only: + cached_team_obj = await _get_team_object_from_cache( + key=key, + proxy_logging_obj=proxy_logging_obj, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + ) + + if cached_team_obj is not None: + return cached_team_obj + + if check_cache_only: + raise Exception( + f"Team doesn't exist in cache + check_cache_only=True. Team={team_id}." + ) + # else, check db try: - db_access_time_key = "team_id:{}".format(team_id) - should_check_db = _should_check_db( - key=db_access_time_key, - last_db_access_time=last_db_access_time, - db_cache_expiry=db_cache_expiry, - ) - if should_check_db: - response = await _get_team_db_check( - team_id=team_id, prisma_client=prisma_client - ) - else: - response = None - - if response is None: - raise Exception - - _response = LiteLLM_TeamTableCachedObj(**response.dict()) - # save the team object to cache - await _cache_team_object( + return await _get_team_object_from_user_api_key_cache( team_id=team_id, - team_table=_response, + prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, - ) - - # save to db access time - # save to db access time - _update_last_db_access_time( - key=db_access_time_key, - value=_response, last_db_access_time=last_db_access_time, + db_cache_expiry=db_cache_expiry, + key=key, ) - - return _response except Exception: raise Exception( f"Team doesn't exist in db. Team={team_id}. Create team via `/team/new` call." @@ -825,7 +877,10 @@ async def get_org_object( async def can_key_call_model( - model: str, llm_model_list: Optional[list], valid_token: UserAPIKeyAuth + model: str, + llm_model_list: Optional[list], + valid_token: UserAPIKeyAuth, + llm_router: Optional[litellm.Router], ) -> Literal[True]: """ Checks if token can call a given model @@ -845,35 +900,29 @@ async def can_key_call_model( ) from collections import defaultdict - from litellm.proxy.proxy_server import llm_router - access_groups = defaultdict(list) if llm_router: - access_groups = llm_router.get_model_access_groups() + access_groups = llm_router.get_model_access_groups(model_name=model) - models_in_current_access_groups = [] - if len(access_groups) > 0: # check if token contains any model access groups + if ( + len(access_groups) > 0 and llm_router is not None + ): # check if token contains any model access groups for idx, m in enumerate( valid_token.models ): # loop token models, if any of them are an access group add the access group if m in access_groups: - # if it is an access group we need to remove it from valid_token.models - models_in_group = access_groups[m] - models_in_current_access_groups.extend(models_in_group) + return True # Filter out models that are access_groups filtered_models = [m for m in valid_token.models if m not in access_groups] - filtered_models += models_in_current_access_groups verbose_proxy_logger.debug(f"model: {model}; allowed_models: {filtered_models}") all_model_access: bool = False if ( - len(filtered_models) == 0 - or "*" in filtered_models - or "openai/*" in filtered_models - ): + len(filtered_models) == 0 and len(valid_token.models) == 0 + ) or "*" in filtered_models: all_model_access = True if model is not None and model not in filtered_models and all_model_access is False: diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 669661e94..d0d3b2e9f 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -28,6 +28,8 @@ from fastapi import ( Request, Response, UploadFile, + WebSocket, + WebSocketDisconnect, status, ) from fastapi.middleware.cors import CORSMiddleware @@ -95,6 +97,11 @@ anthropic_api_key_header = APIKeyHeader( auto_error=False, description="If anthropic client used.", ) +google_ai_studio_api_key_header = APIKeyHeader( + name=SpecialHeaders.google_ai_studio_authorization.value, + auto_error=False, + description="If google ai studio client used.", +) def _get_bearer_token( @@ -190,6 +197,52 @@ def _is_allowed_route( ) +async def user_api_key_auth_websocket(websocket: WebSocket): + # Accept the WebSocket connection + + request = Request(scope={"type": "http"}) + request._url = websocket.url + + query_params = websocket.query_params + + model = query_params.get("model") + + async def return_body(): + return_string = f'{{"model": "{model}"}}' + # return string as bytes + return return_string.encode() + + request.body = return_body # type: ignore + + # Extract the Authorization header + authorization = websocket.headers.get("authorization") + + # If no Authorization header, try the api-key header + if not authorization: + api_key = websocket.headers.get("api-key") + if not api_key: + await websocket.close(code=status.WS_1008_POLICY_VIOLATION) + raise HTTPException(status_code=403, detail="No API key provided") + else: + # Extract the API key from the Bearer token + if not authorization.startswith("Bearer "): + await websocket.close(code=status.WS_1008_POLICY_VIOLATION) + raise HTTPException( + status_code=403, detail="Invalid Authorization header format" + ) + + api_key = authorization[len("Bearer ") :].strip() + + # Call user_api_key_auth with the extracted API key + # Note: You'll need to modify this to work with WebSocket context if needed + try: + return await user_api_key_auth(request=request, api_key=f"Bearer {api_key}") + except Exception as e: + verbose_proxy_logger.exception(e) + await websocket.close(code=status.WS_1008_POLICY_VIOLATION) + raise HTTPException(status_code=403, detail=str(e)) + + async def user_api_key_auth( # noqa: PLR0915 request: Request, api_key: str = fastapi.Security(api_key_header), @@ -197,12 +250,16 @@ async def user_api_key_auth( # noqa: PLR0915 anthropic_api_key_header: Optional[str] = fastapi.Security( anthropic_api_key_header ), + google_ai_studio_api_key_header: Optional[str] = fastapi.Security( + google_ai_studio_api_key_header + ), ) -> UserAPIKeyAuth: from litellm.proxy.proxy_server import ( general_settings, jwt_handler, litellm_proxy_admin_name, llm_model_list, + llm_router, master_key, open_telemetry_logger, prisma_client, @@ -233,6 +290,8 @@ async def user_api_key_auth( # noqa: PLR0915 api_key = azure_api_key_header elif isinstance(anthropic_api_key_header, str): api_key = anthropic_api_key_header + elif isinstance(google_ai_studio_api_key_header, str): + api_key = google_ai_studio_api_key_header elif pass_through_endpoints is not None: for endpoint in pass_through_endpoints: if endpoint.get("path", "") == route: @@ -484,6 +543,7 @@ async def user_api_key_auth( # noqa: PLR0915 general_settings=general_settings, global_proxy_spend=global_proxy_spend, route=route, + llm_router=llm_router, ) # return UserAPIKeyAuth object @@ -847,6 +907,7 @@ async def user_api_key_auth( # noqa: PLR0915 model=model, llm_model_list=llm_model_list, valid_token=valid_token, + llm_router=llm_router, ) if fallback_models is not None: @@ -855,6 +916,7 @@ async def user_api_key_auth( # noqa: PLR0915 model=m, llm_model_list=llm_model_list, valid_token=valid_token, + llm_router=llm_router, ) # Check 2. If user_id for this token is in budget - done in common_checks() @@ -1115,6 +1177,7 @@ async def user_api_key_auth( # noqa: PLR0915 general_settings=general_settings, global_proxy_spend=global_proxy_spend, route=route, + llm_router=llm_router, ) # Token passed all checks if valid_token is None: @@ -1187,13 +1250,15 @@ async def user_api_key_auth( # noqa: PLR0915 extra={"requester_ip": requester_ip}, ) - # Log this exception to OTEL - if open_telemetry_logger is not None: - await open_telemetry_logger.async_post_call_failure_hook( # type: ignore + # Log this exception to OTEL, Datadog etc + asyncio.create_task( + proxy_logging_obj.async_log_proxy_authentication_errors( original_exception=e, - request_data={}, - user_api_key_dict=UserAPIKeyAuth(parent_otel_span=parent_otel_span), + request=request, + parent_otel_span=parent_otel_span, + api_key=api_key, ) + ) if isinstance(e, litellm.BudgetExceededError): raise ProxyException( diff --git a/litellm/proxy/common_utils/http_parsing_utils.py b/litellm/proxy/common_utils/http_parsing_utils.py index 0a8dd86eb..deb259895 100644 --- a/litellm/proxy/common_utils/http_parsing_utils.py +++ b/litellm/proxy/common_utils/http_parsing_utils.py @@ -1,6 +1,6 @@ import ast import json -from typing import List, Optional +from typing import Dict, List, Optional from fastapi import Request, UploadFile, status @@ -8,31 +8,43 @@ from litellm._logging import verbose_proxy_logger from litellm.types.router import Deployment -async def _read_request_body(request: Optional[Request]) -> dict: +async def _read_request_body(request: Optional[Request]) -> Dict: """ - Asynchronous function to read the request body and parse it as JSON or literal data. + Safely read the request body and parse it as JSON. Parameters: - request: The request object to read the body from Returns: - - dict: Parsed request data as a dictionary + - dict: Parsed request data as a dictionary or an empty dictionary if parsing fails """ try: - request_data: dict = {} if request is None: - return request_data + return {} + + # Read the request body body = await request.body() - if body == b"" or body is None: - return request_data + # Return empty dict if body is empty or None + if not body: + return {} + + # Decode the body to a string body_str = body.decode() - try: - request_data = ast.literal_eval(body_str) - except Exception: - request_data = json.loads(body_str) - return request_data - except Exception: + + # Attempt JSON parsing (safe for untrusted input) + return json.loads(body_str) + + except json.JSONDecodeError: + # Log detailed information for debugging + verbose_proxy_logger.exception("Invalid JSON payload received.") + return {} + + except Exception as e: + # Catch unexpected errors to avoid crashes + verbose_proxy_logger.exception( + "Unexpected error reading request body - {}".format(e) + ) return {} diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py index 1127e4e7c..ef41ce9b1 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py +++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py @@ -214,10 +214,10 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): prepared_request.url, prepared_request.headers, ) - _json_data = json.dumps(request_data) # type: ignore + response = await self.async_handler.post( url=prepared_request.url, - json=request_data, # type: ignore + data=prepared_request.body, # type: ignore headers=prepared_request.headers, # type: ignore ) verbose_proxy_logger.debug("Bedrock AI response: %s", response.text) diff --git a/litellm/proxy/hooks/proxy_failure_handler.py b/litellm/proxy/hooks/proxy_failure_handler.py new file mode 100644 index 000000000..d316eab13 --- /dev/null +++ b/litellm/proxy/hooks/proxy_failure_handler.py @@ -0,0 +1,87 @@ +""" +Runs when LLM Exceptions occur on LiteLLM Proxy +""" + +import copy +import json +import uuid + +import litellm +from litellm.proxy._types import LiteLLM_ErrorLogs + + +async def _PROXY_failure_handler( + kwargs, # kwargs to completion + completion_response: litellm.ModelResponse, # response from completion + start_time=None, + end_time=None, # start/end time for completion +): + """ + Async Failure Handler - runs when LLM Exceptions occur on LiteLLM Proxy. + This function logs the errors to the Prisma DB + + Can be disabled by setting the following on proxy_config.yaml: + ```yaml + general_settings: + disable_error_logs: True + ``` + + """ + from litellm._logging import verbose_proxy_logger + from litellm.proxy.proxy_server import general_settings, prisma_client + + if general_settings.get("disable_error_logs") is True: + return + + if prisma_client is not None: + verbose_proxy_logger.debug( + "inside _PROXY_failure_handler kwargs=", extra=kwargs + ) + + _exception = kwargs.get("exception") + _exception_type = _exception.__class__.__name__ + _model = kwargs.get("model", None) + + _optional_params = kwargs.get("optional_params", {}) + _optional_params = copy.deepcopy(_optional_params) + + for k, v in _optional_params.items(): + v = str(v) + v = v[:100] + + _status_code = "500" + try: + _status_code = str(_exception.status_code) + except Exception: + # Don't let this fail logging the exception to the dB + pass + + _litellm_params = kwargs.get("litellm_params", {}) or {} + _metadata = _litellm_params.get("metadata", {}) or {} + _model_id = _metadata.get("model_info", {}).get("id", "") + _model_group = _metadata.get("model_group", "") + api_base = litellm.get_api_base(model=_model, optional_params=_litellm_params) + _exception_string = str(_exception) + + error_log = LiteLLM_ErrorLogs( + request_id=str(uuid.uuid4()), + model_group=_model_group, + model_id=_model_id, + litellm_model_name=kwargs.get("model"), + request_kwargs=_optional_params, + api_base=api_base, + exception_type=_exception_type, + status_code=_status_code, + exception_string=_exception_string, + startTime=kwargs.get("start_time"), + endTime=kwargs.get("end_time"), + ) + + error_log_dict = error_log.model_dump() + error_log_dict["request_kwargs"] = json.dumps(error_log_dict["request_kwargs"]) + + await prisma_client.db.litellm_errorlogs.create( + data=error_log_dict # type: ignore + ) + + pass diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index 3d1d3b491..6ac792696 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -288,12 +288,12 @@ class LiteLLMProxyRequestSetup: ## KEY-LEVEL SPEND LOGS / TAGS if "tags" in key_metadata and key_metadata["tags"] is not None: - if "tags" in data[_metadata_variable_name] and isinstance( - data[_metadata_variable_name]["tags"], list - ): - data[_metadata_variable_name]["tags"].extend(key_metadata["tags"]) - else: - data[_metadata_variable_name]["tags"] = key_metadata["tags"] + data[_metadata_variable_name]["tags"] = ( + LiteLLMProxyRequestSetup._merge_tags( + request_tags=data[_metadata_variable_name].get("tags"), + tags_to_add=key_metadata["tags"], + ) + ) if "spend_logs_metadata" in key_metadata and isinstance( key_metadata["spend_logs_metadata"], dict ): @@ -319,6 +319,30 @@ class LiteLLMProxyRequestSetup: data["disable_fallbacks"] = key_metadata["disable_fallbacks"] return data + @staticmethod + def _merge_tags(request_tags: Optional[list], tags_to_add: Optional[list]) -> list: + """ + Helper function to merge two lists of tags, ensuring no duplicates. + + Args: + request_tags (Optional[list]): List of tags from the original request + tags_to_add (Optional[list]): List of tags to add + + Returns: + list: Combined list of unique tags + """ + final_tags = [] + + if request_tags and isinstance(request_tags, list): + final_tags.extend(request_tags) + + if tags_to_add and isinstance(tags_to_add, list): + for tag in tags_to_add: + if tag not in final_tags: + final_tags.append(tag) + + return final_tags + async def add_litellm_data_to_request( # noqa: PLR0915 data: dict, @@ -442,12 +466,10 @@ async def add_litellm_data_to_request( # noqa: PLR0915 ## TEAM-LEVEL SPEND LOGS/TAGS team_metadata = user_api_key_dict.team_metadata or {} if "tags" in team_metadata and team_metadata["tags"] is not None: - if "tags" in data[_metadata_variable_name] and isinstance( - data[_metadata_variable_name]["tags"], list - ): - data[_metadata_variable_name]["tags"].extend(team_metadata["tags"]) - else: - data[_metadata_variable_name]["tags"] = team_metadata["tags"] + data[_metadata_variable_name]["tags"] = LiteLLMProxyRequestSetup._merge_tags( + request_tags=data[_metadata_variable_name].get("tags"), + tags_to_add=team_metadata["tags"], + ) if "spend_logs_metadata" in team_metadata and isinstance( team_metadata["spend_logs_metadata"], dict ): diff --git a/litellm/proxy/management_endpoints/internal_user_endpoints.py b/litellm/proxy/management_endpoints/internal_user_endpoints.py index c69e255f2..857399034 100644 --- a/litellm/proxy/management_endpoints/internal_user_endpoints.py +++ b/litellm/proxy/management_endpoints/internal_user_endpoints.py @@ -30,8 +30,9 @@ from litellm._logging import verbose_proxy_logger from litellm.proxy._types import * from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.management_endpoints.key_management_endpoints import ( - _duration_in_seconds, + duration_in_seconds, generate_key_helper_fn, + prepare_metadata_fields, ) from litellm.proxy.management_helpers.utils import ( add_new_member, @@ -42,7 +43,7 @@ from litellm.proxy.utils import handle_exception_on_proxy router = APIRouter() -def _update_internal_user_params(data_json: dict, data: NewUserRequest) -> dict: +def _update_internal_new_user_params(data_json: dict, data: NewUserRequest) -> dict: if "user_id" in data_json and data_json["user_id"] is None: data_json["user_id"] = str(uuid.uuid4()) auto_create_key = data_json.pop("auto_create_key", True) @@ -145,7 +146,7 @@ async def new_user( from litellm.proxy.proxy_server import general_settings, proxy_logging_obj data_json = data.json() # type: ignore - data_json = _update_internal_user_params(data_json, data) + data_json = _update_internal_new_user_params(data_json, data) response = await generate_key_helper_fn(request_type="user", **data_json) # Admin UI Logic @@ -438,6 +439,52 @@ async def user_info( # noqa: PLR0915 raise handle_exception_on_proxy(e) +def _update_internal_user_params(data_json: dict, data: UpdateUserRequest) -> dict: + non_default_values = {} + for k, v in data_json.items(): + if ( + v is not None + and v + not in ( + [], + {}, + 0, + ) + and k not in LiteLLM_ManagementEndpoint_MetadataFields + ): # models default to [], spend defaults to 0, we should not reset these values + non_default_values[k] = v + + is_internal_user = False + if data.user_role == LitellmUserRoles.INTERNAL_USER: + is_internal_user = True + + if "budget_duration" in non_default_values: + duration_s = duration_in_seconds(duration=non_default_values["budget_duration"]) + user_reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + non_default_values["budget_reset_at"] = user_reset_at + + if "max_budget" not in non_default_values: + if ( + is_internal_user and litellm.max_internal_user_budget is not None + ): # applies internal user limits, if user role updated + non_default_values["max_budget"] = litellm.max_internal_user_budget + + if ( + "budget_duration" not in non_default_values + ): # applies internal user limits, if user role updated + if is_internal_user and litellm.internal_user_budget_duration is not None: + non_default_values["budget_duration"] = ( + litellm.internal_user_budget_duration + ) + duration_s = duration_in_seconds( + duration=non_default_values["budget_duration"] + ) + user_reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + non_default_values["budget_reset_at"] = user_reset_at + + return non_default_values + + @router.post( "/user/update", tags=["Internal User management"], @@ -459,7 +506,8 @@ async def user_update( "user_id": "test-litellm-user-4", "user_role": "proxy_admin_viewer" }' - + ``` + Parameters: - user_id: Optional[str] - Specify a user id. If not set, a unique id will be generated. - user_email: Optional[str] - Specify a user email. @@ -491,7 +539,7 @@ async def user_update( - duration: Optional[str] - [NOT IMPLEMENTED]. - key_alias: Optional[str] - [NOT IMPLEMENTED]. - ``` + """ from litellm.proxy.proxy_server import prisma_client @@ -502,46 +550,21 @@ async def user_update( raise Exception("Not connected to DB!") # get non default values for key - non_default_values = {} - for k, v in data_json.items(): - if v is not None and v not in ( - [], - {}, - 0, - ): # models default to [], spend defaults to 0, we should not reset these values - non_default_values[k] = v + non_default_values = _update_internal_user_params( + data_json=data_json, data=data + ) - is_internal_user = False - if data.user_role == LitellmUserRoles.INTERNAL_USER: - is_internal_user = True + existing_user_row = await prisma_client.get_data( + user_id=data.user_id, table_name="user", query_type="find_unique" + ) - if "budget_duration" in non_default_values: - duration_s = _duration_in_seconds( - duration=non_default_values["budget_duration"] - ) - user_reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) - non_default_values["budget_reset_at"] = user_reset_at + existing_metadata = existing_user_row.metadata if existing_user_row else {} - if "max_budget" not in non_default_values: - if ( - is_internal_user and litellm.max_internal_user_budget is not None - ): # applies internal user limits, if user role updated - non_default_values["max_budget"] = litellm.max_internal_user_budget - - if ( - "budget_duration" not in non_default_values - ): # applies internal user limits, if user role updated - if is_internal_user and litellm.internal_user_budget_duration is not None: - non_default_values["budget_duration"] = ( - litellm.internal_user_budget_duration - ) - duration_s = _duration_in_seconds( - duration=non_default_values["budget_duration"] - ) - user_reset_at = datetime.now(timezone.utc) + timedelta( - seconds=duration_s - ) - non_default_values["budget_reset_at"] = user_reset_at + non_default_values = prepare_metadata_fields( + data=data, + non_default_values=non_default_values, + existing_metadata=existing_metadata or {}, + ) ## ADD USER, IF NEW ## verbose_proxy_logger.debug("/user/update: Received data = %s", data) @@ -725,8 +748,8 @@ async def delete_user( - user_ids: List[str] - The list of user id's to be deleted. """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, user_api_key_cache, diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index e4493a28c..287de5696 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -17,7 +17,7 @@ import secrets import traceback import uuid from datetime import datetime, timedelta, timezone -from typing import List, Optional, Tuple +from typing import List, Optional, Tuple, cast import fastapi from fastapi import APIRouter, Depends, Header, HTTPException, Query, Request, status @@ -29,16 +29,182 @@ from litellm.proxy.auth.auth_checks import ( _cache_key_object, _delete_cache_key_object, get_key_object, + get_team_object, ) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.hooks.key_management_event_hooks import KeyManagementEventHooks from litellm.proxy.management_helpers.utils import management_endpoint_wrapper from litellm.proxy.utils import ( - _duration_in_seconds, _hash_token_if_needed, + duration_in_seconds, handle_exception_on_proxy, ) from litellm.secret_managers.main import get_secret +from litellm.types.utils import PersonalUIKeyGenerationConfig, TeamUIKeyGenerationConfig + + +def _is_team_key(data: GenerateKeyRequest): + return data.team_id is not None + + +def _get_user_in_team( + team_table: LiteLLM_TeamTableCachedObj, user_id: Optional[str] +) -> Optional[Member]: + if user_id is None: + return None + for member in team_table.members_with_roles: + if member.user_id is not None and member.user_id == user_id: + return member + return None + + +def _team_key_generation_team_member_check( + team_table: LiteLLM_TeamTableCachedObj, + user_api_key_dict: UserAPIKeyAuth, + team_key_generation: Optional[TeamUIKeyGenerationConfig], +): + if ( + team_key_generation is None + or "allowed_team_member_roles" not in team_key_generation + ): + return True + + user_in_team = _get_user_in_team( + team_table=team_table, user_id=user_api_key_dict.user_id + ) + if user_in_team is None: + raise HTTPException( + status_code=400, + detail=f"User={user_api_key_dict.user_id} not assigned to team={team_table.team_id}", + ) + + if user_in_team.role not in team_key_generation["allowed_team_member_roles"]: + raise HTTPException( + status_code=400, + detail=f"Team member role {user_in_team.role} not in allowed_team_member_roles={team_key_generation['allowed_team_member_roles']}", + ) + return True + + +def _key_generation_required_param_check( + data: GenerateKeyRequest, required_params: Optional[List[str]] +): + if required_params is None: + return True + + data_dict = data.model_dump(exclude_unset=True) + for param in required_params: + if param not in data_dict: + raise HTTPException( + status_code=400, + detail=f"Required param {param} not in data", + ) + return True + + +def _team_key_generation_check( + team_table: LiteLLM_TeamTableCachedObj, + user_api_key_dict: UserAPIKeyAuth, + data: GenerateKeyRequest, +): + if ( + litellm.key_generation_settings is None + or litellm.key_generation_settings.get("team_key_generation") is None + ): + return True + + _team_key_generation = litellm.key_generation_settings["team_key_generation"] # type: ignore + + _team_key_generation_team_member_check( + team_table=team_table, + user_api_key_dict=user_api_key_dict, + team_key_generation=_team_key_generation, + ) + _key_generation_required_param_check( + data, + _team_key_generation.get("required_params"), + ) + + return True + + +def _personal_key_membership_check( + user_api_key_dict: UserAPIKeyAuth, + personal_key_generation: Optional[PersonalUIKeyGenerationConfig], +): + if ( + personal_key_generation is None + or "allowed_user_roles" not in personal_key_generation + ): + return True + + if user_api_key_dict.user_role not in personal_key_generation["allowed_user_roles"]: + raise HTTPException( + status_code=400, + detail=f"Personal key creation has been restricted by admin. Allowed roles={litellm.key_generation_settings['personal_key_generation']['allowed_user_roles']}. Your role={user_api_key_dict.user_role}", # type: ignore + ) + + return True + + +def _personal_key_generation_check( + user_api_key_dict: UserAPIKeyAuth, data: GenerateKeyRequest +): + + if ( + litellm.key_generation_settings is None + or litellm.key_generation_settings.get("personal_key_generation") is None + ): + return True + + _personal_key_generation = litellm.key_generation_settings["personal_key_generation"] # type: ignore + + _personal_key_membership_check( + user_api_key_dict, + personal_key_generation=_personal_key_generation, + ) + + _key_generation_required_param_check( + data, + _personal_key_generation.get("required_params"), + ) + + return True + + +def key_generation_check( + team_table: Optional[LiteLLM_TeamTableCachedObj], + user_api_key_dict: UserAPIKeyAuth, + data: GenerateKeyRequest, +) -> bool: + """ + Check if admin has restricted key creation to certain roles for teams or individuals + """ + if ( + litellm.key_generation_settings is None + or user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN.value + ): + return True + + ## check if key is for team or individual + is_team_key = _is_team_key(data=data) + + if is_team_key: + if team_table is None: + raise HTTPException( + status_code=400, + detail=f"Unable to find team object in database. Team ID: {data.team_id}", + ) + return _team_key_generation_check( + team_table=team_table, + user_api_key_dict=user_api_key_dict, + data=data, + ) + else: + return _personal_key_generation_check( + user_api_key_dict=user_api_key_dict, data=data + ) + router = APIRouter() @@ -115,6 +281,7 @@ async def generate_key_fn( # noqa: PLR0915 litellm_proxy_admin_name, prisma_client, proxy_logging_obj, + user_api_key_cache, user_custom_key_generate, ) @@ -131,6 +298,21 @@ async def generate_key_fn( # noqa: PLR0915 raise HTTPException( status_code=status.HTTP_403_FORBIDDEN, detail=message ) + elif litellm.key_generation_settings is not None: + if data.team_id is None: + team_table: Optional[LiteLLM_TeamTableCachedObj] = None + else: + team_table = await get_team_object( + team_id=data.team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=user_api_key_dict.parent_otel_span, + ) + key_generation_check( + team_table=team_table, + user_api_key_dict=user_api_key_dict, + data=data, + ) # check if user set default key/generate params on config.yaml if litellm.default_key_generate_params is not None: for elem in data: @@ -180,10 +362,10 @@ async def generate_key_fn( # noqa: PLR0915 ) # Compare durations elif key in ["budget_duration", "duration"]: - upperbound_duration = _duration_in_seconds( + upperbound_duration = duration_in_seconds( duration=upperbound_value ) - user_duration = _duration_in_seconds(duration=value) + user_duration = duration_in_seconds(duration=value) if user_duration > upperbound_duration: raise HTTPException( status_code=400, @@ -212,7 +394,8 @@ async def generate_key_fn( # noqa: PLR0915 } ) _budget_id = getattr(_budget, "budget_id", None) - data_json = data.json() # type: ignore + data_json = data.model_dump(exclude_unset=True, exclude_none=True) # type: ignore + # if we get max_budget passed to /key/generate, then use it as key_max_budget. Since generate_key_helper_fn is used to make new users if "max_budget" in data_json: data_json["key_max_budget"] = data_json.pop("max_budget", None) @@ -238,6 +421,11 @@ async def generate_key_fn( # noqa: PLR0915 data_json.pop("tags") + await _enforce_unique_key_alias( + key_alias=data_json.get("key_alias", None), + prisma_client=prisma_client, + ) + response = await generate_key_helper_fn( request_type="key", **data_json, table_name="key" ) @@ -265,12 +453,52 @@ async def generate_key_fn( # noqa: PLR0915 raise handle_exception_on_proxy(e) +def prepare_metadata_fields( + data: BaseModel, non_default_values: dict, existing_metadata: dict +) -> dict: + """ + Check LiteLLM_ManagementEndpoint_MetadataFields (proxy/_types.py) for fields that are allowed to be updated + """ + + if "metadata" not in non_default_values: # allow user to set metadata to none + non_default_values["metadata"] = existing_metadata.copy() + + casted_metadata = cast(dict, non_default_values["metadata"]) + + data_json = data.model_dump(exclude_unset=True, exclude_none=True) + + try: + for k, v in data_json.items(): + if k == "model_tpm_limit" or k == "model_rpm_limit": + if k not in casted_metadata or casted_metadata[k] is None: + casted_metadata[k] = {} + casted_metadata[k].update(v) + + if k == "tags" or k == "guardrails": + if k not in casted_metadata or casted_metadata[k] is None: + casted_metadata[k] = [] + seen = set(casted_metadata[k]) + casted_metadata[k].extend( + x for x in v if x not in seen and not seen.add(x) # type: ignore + ) # prevent duplicates from being added + maintain initial order + + except Exception as e: + verbose_proxy_logger.exception( + "litellm.proxy.proxy_server.prepare_metadata_fields(): Exception occured - {}".format( + str(e) + ) + ) + + non_default_values["metadata"] = casted_metadata + return non_default_values + + def prepare_key_update_data( data: Union[UpdateKeyRequest, RegenerateKeyRequest], existing_key_row ): data_json: dict = data.model_dump(exclude_unset=True) data_json.pop("key", None) - _metadata_fields = ["model_rpm_limit", "model_tpm_limit", "guardrails"] + _metadata_fields = ["model_rpm_limit", "model_tpm_limit", "guardrails", "tags"] non_default_values = {} for k, v in data_json.items(): if k in _metadata_fields: @@ -280,7 +508,7 @@ def prepare_key_update_data( if "duration" in non_default_values: duration = non_default_values.pop("duration") if duration and (isinstance(duration, str)) and len(duration) > 0: - duration_s = _duration_in_seconds(duration=duration) + duration_s = duration_in_seconds(duration=duration) expires = datetime.now(timezone.utc) + timedelta(seconds=duration_s) non_default_values["expires"] = expires @@ -291,27 +519,16 @@ def prepare_key_update_data( and (isinstance(budget_duration, str)) and len(budget_duration) > 0 ): - duration_s = _duration_in_seconds(duration=budget_duration) + duration_s = duration_in_seconds(duration=budget_duration) key_reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) non_default_values["budget_reset_at"] = key_reset_at + non_default_values["budget_duration"] = budget_duration _metadata = existing_key_row.metadata or {} - if data.model_tpm_limit: - if "model_tpm_limit" not in _metadata: - _metadata["model_tpm_limit"] = {} - _metadata["model_tpm_limit"].update(data.model_tpm_limit) - non_default_values["metadata"] = _metadata - - if data.model_rpm_limit: - if "model_rpm_limit" not in _metadata: - _metadata["model_rpm_limit"] = {} - _metadata["model_rpm_limit"].update(data.model_rpm_limit) - non_default_values["metadata"] = _metadata - - if data.guardrails: - _metadata["guardrails"] = data.guardrails - non_default_values["metadata"] = _metadata + non_default_values = prepare_metadata_fields( + data=data, non_default_values=non_default_values, existing_metadata=_metadata + ) return non_default_values @@ -403,6 +620,12 @@ async def update_key_fn( data=data, existing_key_row=existing_key_row ) + await _enforce_unique_key_alias( + key_alias=non_default_values.get("key_alias", None), + prisma_client=prisma_client, + existing_key_token=existing_key_row.token, + ) + response = await prisma_client.update_data( token=key, data={**non_default_values, "token": key} ) @@ -730,11 +953,11 @@ async def generate_key_helper_fn( # noqa: PLR0915 request_type: Literal[ "user", "key" ], # identifies if this request is from /user/new or /key/generate - duration: Optional[str], - models: list, - aliases: dict, - config: dict, - spend: float, + duration: Optional[str] = None, + models: list = [], + aliases: dict = {}, + config: dict = {}, + spend: float = 0.0, key_max_budget: Optional[float] = None, # key_max_budget is used to Budget Per key key_budget_duration: Optional[str] = None, budget_id: Optional[float] = None, # budget id <-> LiteLLM_BudgetTable @@ -763,8 +986,8 @@ async def generate_key_helper_fn( # noqa: PLR0915 allowed_cache_controls: Optional[list] = [], permissions: Optional[dict] = {}, model_max_budget: Optional[dict] = {}, - model_rpm_limit: Optional[dict] = {}, - model_tpm_limit: Optional[dict] = {}, + model_rpm_limit: Optional[dict] = None, + model_tpm_limit: Optional[dict] = None, guardrails: Optional[list] = None, teams: Optional[list] = None, organization_id: Optional[str] = None, @@ -791,19 +1014,19 @@ async def generate_key_helper_fn( # noqa: PLR0915 if duration is None: # allow tokens that never expire expires = None else: - duration_s = _duration_in_seconds(duration=duration) + duration_s = duration_in_seconds(duration=duration) expires = datetime.now(timezone.utc) + timedelta(seconds=duration_s) if key_budget_duration is None: # one-time budget key_reset_at = None else: - duration_s = _duration_in_seconds(duration=key_budget_duration) + duration_s = duration_in_seconds(duration=key_budget_duration) key_reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) if budget_duration is None: # one-time budget reset_at = None else: - duration_s = _duration_in_seconds(duration=budget_duration) + duration_s = duration_in_seconds(duration=budget_duration) reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) aliases_json = json.dumps(aliases) @@ -1701,3 +1924,38 @@ async def test_key_logging( status="healthy", details=f"No logger exceptions triggered, system is healthy. Manually check if logs were sent to {logging_callbacks} ", ) + + +async def _enforce_unique_key_alias( + key_alias: Optional[str], + prisma_client: Any, + existing_key_token: Optional[str] = None, +) -> None: + """ + Helper to enforce unique key aliases across all keys. + + Args: + key_alias (Optional[str]): The key alias to check + prisma_client (Any): Prisma client instance + existing_key_token (Optional[str]): ID of existing key being updated, to exclude from uniqueness check + (The Admin UI passes key_alias, in all Edit key requests. So we need to be sure that if we find a key with the same alias, it's not the same key we're updating) + + Raises: + ProxyException: If key alias already exists on a different key + """ + if key_alias is not None and prisma_client is not None: + where_clause: dict[str, Any] = {"key_alias": key_alias} + if existing_key_token: + # Exclude the current key from the uniqueness check + where_clause["NOT"] = {"token": existing_key_token} + + existing_key = await prisma_client.db.litellm_verificationtoken.find_first( + where=where_clause + ) + if existing_key is not None: + raise ProxyException( + message=f"Key with alias '{key_alias}' already exists. Unique key aliases across all keys are required.", + type=ProxyErrorTypes.bad_request_error, + param="key_alias", + code=status.HTTP_400_BAD_REQUEST, + ) diff --git a/litellm/proxy/management_endpoints/organization_endpoints.py b/litellm/proxy/management_endpoints/organization_endpoints.py index 81d135097..363384375 100644 --- a/litellm/proxy/management_endpoints/organization_endpoints.py +++ b/litellm/proxy/management_endpoints/organization_endpoints.py @@ -352,7 +352,7 @@ async def organization_member_add( }, ) - members: List[Member] + members: List[OrgMember] if isinstance(data.member, List): members = data.member else: @@ -397,7 +397,7 @@ async def organization_member_add( async def add_member_to_organization( - member: Member, + member: OrgMember, organization_id: str, prisma_client: PrismaClient, ) -> Tuple[LiteLLM_UserTable, LiteLLM_OrganizationMembershipTable]: diff --git a/litellm/proxy/management_endpoints/team_callback_endpoints.py b/litellm/proxy/management_endpoints/team_callback_endpoints.py index b60ea3acf..6c5fa80a2 100644 --- a/litellm/proxy/management_endpoints/team_callback_endpoints.py +++ b/litellm/proxy/management_endpoints/team_callback_endpoints.py @@ -90,8 +90,8 @@ async def add_team_callbacks( """ try: from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index dc1ec444d..01d1a7ca4 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -169,8 +169,8 @@ async def new_team( # noqa: PLR0915 ``` """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -289,7 +289,7 @@ async def new_team( # noqa: PLR0915 # If budget_duration is set, set `budget_reset_at` if complete_team_data.budget_duration is not None: - duration_s = _duration_in_seconds(duration=complete_team_data.budget_duration) + duration_s = duration_in_seconds(duration=complete_team_data.budget_duration) reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) complete_team_data.budget_reset_at = reset_at @@ -396,8 +396,8 @@ async def update_team( """ from litellm.proxy.auth.auth_checks import _cache_team_object from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, proxy_logging_obj, @@ -425,7 +425,7 @@ async def update_team( # Check budget_duration and budget_reset_at if data.budget_duration is not None: - duration_s = _duration_in_seconds(duration=data.budget_duration) + duration_s = duration_in_seconds(duration=data.budget_duration) reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) # set the budget_reset_at in DB @@ -547,6 +547,7 @@ async def team_member_add( parent_otel_span=None, proxy_logging_obj=proxy_logging_obj, check_cache_only=False, + check_db_only=True, ) if existing_team_row is None: raise HTTPException( @@ -709,8 +710,8 @@ async def team_member_delete( ``` """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -829,8 +830,8 @@ async def team_member_update( Update team member budgets """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -965,8 +966,8 @@ async def delete_team( ``` """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -1054,8 +1055,8 @@ async def team_info( ``` """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -1203,8 +1204,8 @@ async def block_team( """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -1251,8 +1252,8 @@ async def unblock_team( ``` """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -1294,8 +1295,8 @@ async def list_team( - user_id: str - Optional. If passed will only return teams that the user_id is a member of. """ from litellm.proxy.proxy_server import ( - _duration_in_seconds, create_audit_log_for_update, + duration_in_seconds, litellm_proxy_admin_name, prisma_client, ) @@ -1366,6 +1367,7 @@ async def list_team( """.format( team.team_id, team.model_dump(), str(e) ) - raise HTTPException(status_code=400, detail={"error": team_exception}) + verbose_proxy_logger.exception(team_exception) + continue return returned_responses diff --git a/litellm/proxy/model_config.yaml b/litellm/proxy/model_config.yaml new file mode 100644 index 000000000..a0399c095 --- /dev/null +++ b/litellm/proxy/model_config.yaml @@ -0,0 +1,10 @@ +model_list: + - model_name: gpt-4o + litellm_params: + model: openai/gpt-4o + api_base: https://exampleopenaiendpoint-production.up.railway.app/ + - model_name: fake-anthropic-endpoint + litellm_params: + model: anthropic/fake + api_base: https://exampleanthropicendpoint-production.up.railway.app/ + diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index 0834102b3..cae211da7 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -54,17 +54,26 @@ def create_request_copy(request: Request): } -@router.api_route("/gemini/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"]) +@router.api_route( + "/gemini/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Google AI Studio Pass-through", "pass-through"], +) async def gemini_proxy_route( endpoint: str, request: Request, fastapi_response: Response, ): + """ + [Docs](https://docs.litellm.ai/docs/pass_through/google_ai_studio) + """ ## CHECK FOR LITELLM API KEY IN THE QUERY PARAMS - ?..key=LITELLM_API_KEY - api_key = request.query_params.get("key") + google_ai_studio_api_key = request.query_params.get("key") or request.headers.get( + "x-goog-api-key" + ) user_api_key_dict = await user_api_key_auth( - request=request, api_key="Bearer {}".format(api_key) + request=request, api_key=f"Bearer {google_ai_studio_api_key}" ) base_target_url = "https://generativelanguage.googleapis.com" @@ -111,13 +120,20 @@ async def gemini_proxy_route( return received_value -@router.api_route("/cohere/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"]) +@router.api_route( + "/cohere/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Cohere Pass-through", "pass-through"], +) async def cohere_proxy_route( endpoint: str, request: Request, fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): + """ + [Docs](https://docs.litellm.ai/docs/pass_through/cohere) + """ base_target_url = "https://api.cohere.com" encoded_endpoint = httpx.URL(endpoint).path @@ -154,7 +170,9 @@ async def cohere_proxy_route( @router.api_route( - "/anthropic/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"] + "/anthropic/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Anthropic Pass-through", "pass-through"], ) async def anthropic_proxy_route( endpoint: str, @@ -162,6 +180,9 @@ async def anthropic_proxy_route( fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): + """ + [Docs](https://docs.litellm.ai/docs/anthropic_completion) + """ base_target_url = "https://api.anthropic.com" encoded_endpoint = httpx.URL(endpoint).path @@ -178,8 +199,11 @@ async def anthropic_proxy_route( ## check for streaming is_streaming_request = False - if "stream" in str(updated_url): - is_streaming_request = True + # anthropic is streaming when 'stream' = True is in the body + if request.method == "POST": + _request_body = await request.json() + if _request_body.get("stream"): + is_streaming_request = True ## CREATE PASS-THROUGH endpoint_func = create_pass_through_route( @@ -198,13 +222,20 @@ async def anthropic_proxy_route( return received_value -@router.api_route("/bedrock/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"]) +@router.api_route( + "/bedrock/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Bedrock Pass-through", "pass-through"], +) async def bedrock_proxy_route( endpoint: str, request: Request, fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): + """ + [Docs](https://docs.litellm.ai/docs/pass_through/bedrock) + """ create_request_copy(request) try: @@ -272,13 +303,22 @@ async def bedrock_proxy_route( return received_value -@router.api_route("/azure/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"]) +@router.api_route( + "/azure/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Azure Pass-through", "pass-through"], +) async def azure_proxy_route( endpoint: str, request: Request, fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): + """ + Call any azure endpoint using the proxy. + + Just use `{PROXY_BASE_URL}/azure/{endpoint:path}` + """ base_target_url = get_secret_str(secret_name="AZURE_API_BASE") if base_target_url is None: raise Exception( diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py new file mode 100644 index 000000000..d155174a7 --- /dev/null +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py @@ -0,0 +1,208 @@ +import json +from datetime import datetime +from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union + +import httpx + +import litellm +from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.litellm_core_utils.litellm_logging import ( + get_standard_logging_object_payload, +) +from litellm.llms.anthropic.chat.handler import ( + ModelResponseIterator as AnthropicModelResponseIterator, +) +from litellm.llms.anthropic.chat.transformation import AnthropicConfig +from litellm.proxy._types import PassThroughEndpointLoggingTypedDict + +if TYPE_CHECKING: + from ..success_handler import PassThroughEndpointLogging + from ..types import EndpointType +else: + PassThroughEndpointLogging = Any + EndpointType = Any + + +class AnthropicPassthroughLoggingHandler: + + @staticmethod + def anthropic_passthrough_handler( + httpx_response: httpx.Response, + response_body: dict, + logging_obj: LiteLLMLoggingObj, + url_route: str, + result: str, + start_time: datetime, + end_time: datetime, + cache_hit: bool, + **kwargs, + ) -> PassThroughEndpointLoggingTypedDict: + """ + Transforms Anthropic response to OpenAI response, generates a standard logging object so downstream logging can be handled + """ + model = response_body.get("model", "") + litellm_model_response: litellm.ModelResponse = ( + AnthropicConfig._process_response( + response=httpx_response, + model_response=litellm.ModelResponse(), + model=model, + stream=False, + messages=[], + logging_obj=logging_obj, + optional_params={}, + api_key="", + data={}, + print_verbose=litellm.print_verbose, + encoding=None, + json_mode=False, + ) + ) + + kwargs = AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( + litellm_model_response=litellm_model_response, + model=model, + kwargs=kwargs, + start_time=start_time, + end_time=end_time, + logging_obj=logging_obj, + ) + + return { + "result": litellm_model_response, + "kwargs": kwargs, + } + + @staticmethod + def _create_anthropic_response_logging_payload( + litellm_model_response: Union[ + litellm.ModelResponse, litellm.TextCompletionResponse + ], + model: str, + kwargs: dict, + start_time: datetime, + end_time: datetime, + logging_obj: LiteLLMLoggingObj, + ): + """ + Create the standard logging object for Anthropic passthrough + + handles streaming and non-streaming responses + """ + response_cost = litellm.completion_cost( + completion_response=litellm_model_response, + model=model, + ) + kwargs["response_cost"] = response_cost + kwargs["model"] = model + + # Make standard logging object for Anthropic + standard_logging_object = get_standard_logging_object_payload( + kwargs=kwargs, + init_response_obj=litellm_model_response, + start_time=start_time, + end_time=end_time, + logging_obj=logging_obj, + status="success", + ) + + # pretty print standard logging object + verbose_proxy_logger.debug( + "standard_logging_object= %s", json.dumps(standard_logging_object, indent=4) + ) + kwargs["standard_logging_object"] = standard_logging_object + + # set litellm_call_id to logging response object + litellm_model_response.id = logging_obj.litellm_call_id + litellm_model_response.model = model + logging_obj.model_call_details["model"] = model + return kwargs + + @staticmethod + def _handle_logging_anthropic_collected_chunks( + litellm_logging_obj: LiteLLMLoggingObj, + passthrough_success_handler_obj: PassThroughEndpointLogging, + url_route: str, + request_body: dict, + endpoint_type: EndpointType, + start_time: datetime, + all_chunks: List[str], + end_time: datetime, + ) -> PassThroughEndpointLoggingTypedDict: + """ + Takes raw chunks from Anthropic passthrough endpoint and logs them in litellm callbacks + + - Builds complete response from chunks + - Creates standard logging object + - Logs in litellm callbacks + """ + model = request_body.get("model", "") + complete_streaming_response = ( + AnthropicPassthroughLoggingHandler._build_complete_streaming_response( + all_chunks=all_chunks, + litellm_logging_obj=litellm_logging_obj, + model=model, + ) + ) + if complete_streaming_response is None: + verbose_proxy_logger.error( + "Unable to build complete streaming response for Anthropic passthrough endpoint, not logging..." + ) + return { + "result": None, + "kwargs": {}, + } + kwargs = AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( + litellm_model_response=complete_streaming_response, + model=model, + kwargs={}, + start_time=start_time, + end_time=end_time, + logging_obj=litellm_logging_obj, + ) + + return { + "result": complete_streaming_response, + "kwargs": kwargs, + } + + @staticmethod + def _build_complete_streaming_response( + all_chunks: List[str], + litellm_logging_obj: LiteLLMLoggingObj, + model: str, + ) -> Optional[Union[litellm.ModelResponse, litellm.TextCompletionResponse]]: + """ + Builds complete response from raw Anthropic chunks + + - Converts str chunks to generic chunks + - Converts generic chunks to litellm chunks (OpenAI format) + - Builds complete response from litellm chunks + """ + anthropic_model_response_iterator = AnthropicModelResponseIterator( + streaming_response=None, + sync_stream=False, + ) + litellm_custom_stream_wrapper = litellm.CustomStreamWrapper( + completion_stream=anthropic_model_response_iterator, + model=model, + logging_obj=litellm_logging_obj, + custom_llm_provider="anthropic", + ) + all_openai_chunks = [] + for _chunk_str in all_chunks: + try: + generic_chunk = anthropic_model_response_iterator.convert_str_chunk_to_generic_chunk( + chunk=_chunk_str + ) + litellm_chunk = litellm_custom_stream_wrapper.chunk_creator( + chunk=generic_chunk + ) + if litellm_chunk is not None: + all_openai_chunks.append(litellm_chunk) + except (StopIteration, StopAsyncIteration): + break + complete_streaming_response = litellm.stream_chunk_builder( + chunks=all_openai_chunks + ) + return complete_streaming_response diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py new file mode 100644 index 000000000..2773979ad --- /dev/null +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py @@ -0,0 +1,256 @@ +import json +import re +from datetime import datetime +from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union + +import httpx + +import litellm +from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.litellm_core_utils.litellm_logging import ( + get_standard_logging_object_payload, +) +from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import ( + ModelResponseIterator as VertexModelResponseIterator, +) +from litellm.proxy._types import PassThroughEndpointLoggingTypedDict + +if TYPE_CHECKING: + from ..success_handler import PassThroughEndpointLogging + from ..types import EndpointType +else: + PassThroughEndpointLogging = Any + EndpointType = Any + + +class VertexPassthroughLoggingHandler: + @staticmethod + def vertex_passthrough_handler( + httpx_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + url_route: str, + result: str, + start_time: datetime, + end_time: datetime, + cache_hit: bool, + **kwargs, + ) -> PassThroughEndpointLoggingTypedDict: + if "generateContent" in url_route: + model = VertexPassthroughLoggingHandler.extract_model_from_url(url_route) + + instance_of_vertex_llm = litellm.VertexGeminiConfig() + litellm_model_response: litellm.ModelResponse = ( + instance_of_vertex_llm._transform_response( + model=model, + messages=[ + {"role": "user", "content": "no-message-pass-through-endpoint"} + ], + response=httpx_response, + model_response=litellm.ModelResponse(), + logging_obj=logging_obj, + optional_params={}, + litellm_params={}, + api_key="", + data={}, + print_verbose=litellm.print_verbose, + encoding=None, + ) + ) + kwargs = VertexPassthroughLoggingHandler._create_vertex_response_logging_payload_for_generate_content( + litellm_model_response=litellm_model_response, + model=model, + kwargs=kwargs, + start_time=start_time, + end_time=end_time, + logging_obj=logging_obj, + ) + + return { + "result": litellm_model_response, + "kwargs": kwargs, + } + + elif "predict" in url_route: + from litellm.llms.vertex_ai_and_google_ai_studio.image_generation.image_generation_handler import ( + VertexImageGeneration, + ) + from litellm.types.utils import PassthroughCallTypes + + vertex_image_generation_class = VertexImageGeneration() + + model = VertexPassthroughLoggingHandler.extract_model_from_url(url_route) + _json_response = httpx_response.json() + + litellm_prediction_response: Union[ + litellm.ModelResponse, litellm.EmbeddingResponse, litellm.ImageResponse + ] = litellm.ModelResponse() + if vertex_image_generation_class.is_image_generation_response( + _json_response + ): + litellm_prediction_response = ( + vertex_image_generation_class.process_image_generation_response( + _json_response, + model_response=litellm.ImageResponse(), + model=model, + ) + ) + + logging_obj.call_type = ( + PassthroughCallTypes.passthrough_image_generation.value + ) + else: + litellm_prediction_response = litellm.vertexAITextEmbeddingConfig.transform_vertex_response_to_openai( + response=_json_response, + model=model, + model_response=litellm.EmbeddingResponse(), + ) + if isinstance(litellm_prediction_response, litellm.EmbeddingResponse): + litellm_prediction_response.model = model + + logging_obj.model = model + logging_obj.model_call_details["model"] = logging_obj.model + + return { + "result": litellm_prediction_response, + "kwargs": kwargs, + } + else: + return { + "result": None, + "kwargs": kwargs, + } + + @staticmethod + def _handle_logging_vertex_collected_chunks( + litellm_logging_obj: LiteLLMLoggingObj, + passthrough_success_handler_obj: PassThroughEndpointLogging, + url_route: str, + request_body: dict, + endpoint_type: EndpointType, + start_time: datetime, + all_chunks: List[str], + end_time: datetime, + ) -> PassThroughEndpointLoggingTypedDict: + """ + Takes raw chunks from Vertex passthrough endpoint and logs them in litellm callbacks + + - Builds complete response from chunks + - Creates standard logging object + - Logs in litellm callbacks + """ + kwargs: Dict[str, Any] = {} + model = VertexPassthroughLoggingHandler.extract_model_from_url(url_route) + complete_streaming_response = ( + VertexPassthroughLoggingHandler._build_complete_streaming_response( + all_chunks=all_chunks, + litellm_logging_obj=litellm_logging_obj, + model=model, + ) + ) + + if complete_streaming_response is None: + verbose_proxy_logger.error( + "Unable to build complete streaming response for Vertex passthrough endpoint, not logging..." + ) + return { + "result": None, + "kwargs": kwargs, + } + + kwargs = VertexPassthroughLoggingHandler._create_vertex_response_logging_payload_for_generate_content( + litellm_model_response=complete_streaming_response, + model=model, + kwargs=kwargs, + start_time=start_time, + end_time=end_time, + logging_obj=litellm_logging_obj, + ) + + return { + "result": complete_streaming_response, + "kwargs": kwargs, + } + + @staticmethod + def _build_complete_streaming_response( + all_chunks: List[str], + litellm_logging_obj: LiteLLMLoggingObj, + model: str, + ) -> Optional[Union[litellm.ModelResponse, litellm.TextCompletionResponse]]: + vertex_iterator = VertexModelResponseIterator( + streaming_response=None, + sync_stream=False, + ) + litellm_custom_stream_wrapper = litellm.CustomStreamWrapper( + completion_stream=vertex_iterator, + model=model, + logging_obj=litellm_logging_obj, + custom_llm_provider="vertex_ai", + ) + all_openai_chunks = [] + for chunk in all_chunks: + generic_chunk = vertex_iterator._common_chunk_parsing_logic(chunk) + litellm_chunk = litellm_custom_stream_wrapper.chunk_creator( + chunk=generic_chunk + ) + if litellm_chunk is not None: + all_openai_chunks.append(litellm_chunk) + + complete_streaming_response = litellm.stream_chunk_builder( + chunks=all_openai_chunks + ) + + return complete_streaming_response + + @staticmethod + def extract_model_from_url(url: str) -> str: + pattern = r"/models/([^:]+)" + match = re.search(pattern, url) + if match: + return match.group(1) + return "unknown" + + @staticmethod + def _create_vertex_response_logging_payload_for_generate_content( + litellm_model_response: Union[ + litellm.ModelResponse, litellm.TextCompletionResponse + ], + model: str, + kwargs: dict, + start_time: datetime, + end_time: datetime, + logging_obj: LiteLLMLoggingObj, + ): + """ + Create the standard logging object for Vertex passthrough generateContent (streaming and non-streaming) + + """ + response_cost = litellm.completion_cost( + completion_response=litellm_model_response, + model=model, + ) + kwargs["response_cost"] = response_cost + kwargs["model"] = model + + # Make standard logging object for Vertex AI + standard_logging_object = get_standard_logging_object_payload( + kwargs=kwargs, + init_response_obj=litellm_model_response, + start_time=start_time, + end_time=end_time, + logging_obj=logging_obj, + status="success", + ) + + # pretty print standard logging object + verbose_proxy_logger.debug( + "standard_logging_object= %s", json.dumps(standard_logging_object, indent=4) + ) + kwargs["standard_logging_object"] = standard_logging_object + + # set litellm_call_id to logging response object + litellm_model_response.id = logging_obj.litellm_call_id + logging_obj.model = litellm_model_response.model or model + logging_obj.model_call_details["model"] = logging_obj.model + return kwargs diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index 6c9a93849..53c4a55c3 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -4,7 +4,7 @@ import json import traceback from base64 import b64encode from datetime import datetime -from typing import AsyncIterable, List, Optional +from typing import AsyncIterable, List, Optional, Union import httpx from fastapi import ( @@ -22,6 +22,7 @@ import litellm from litellm._logging import verbose_proxy_logger from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.custom_httpx.http_handler import get_async_httpx_client from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import ( ModelResponseIterator, ) @@ -35,8 +36,9 @@ from litellm.proxy._types import ( ) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.secret_managers.main import get_secret_str +from litellm.types.llms.custom_http import httpxSpecialProvider -from .streaming_handler import chunk_processor +from .streaming_handler import PassThroughStreamingHandler from .success_handler import PassThroughEndpointLogging from .types import EndpointType, PassthroughStandardLoggingPayload @@ -289,13 +291,18 @@ def forward_headers_from_request( return headers -def get_response_headers(headers: httpx.Headers) -> dict: +def get_response_headers( + headers: httpx.Headers, litellm_call_id: Optional[str] = None +) -> dict: excluded_headers = {"transfer-encoding", "content-encoding"} + return_headers = { key: value for key, value in headers.items() if key.lower() not in excluded_headers } + if litellm_call_id: + return_headers["x-litellm-call-id"] = litellm_call_id return return_headers @@ -308,24 +315,6 @@ def get_endpoint_type(url: str) -> EndpointType: return EndpointType.GENERIC -async def stream_response( - response: httpx.Response, - logging_obj: LiteLLMLoggingObj, - endpoint_type: EndpointType, - start_time: datetime, - url: str, -) -> AsyncIterable[bytes]: - async for chunk in chunk_processor( - response.aiter_bytes(), - litellm_logging_obj=logging_obj, - endpoint_type=endpoint_type, - start_time=start_time, - passthrough_success_handler_obj=pass_through_endpoint_logging, - url_route=str(url), - ): - yield chunk - - async def pass_through_request( # noqa: PLR0915 request: Request, target: str, @@ -376,8 +365,13 @@ async def pass_through_request( # noqa: PLR0915 data=_parsed_body, call_type="pass_through_endpoint", ) + async_client_obj = get_async_httpx_client( + llm_provider=httpxSpecialProvider.PassThroughEndpoint, + params={"timeout": 600}, + ) + async_client = async_client_obj.client - async_client = httpx.AsyncClient(timeout=600) + litellm_call_id = str(uuid.uuid4()) # create logging object start_time = datetime.now() @@ -387,27 +381,21 @@ async def pass_through_request( # noqa: PLR0915 stream=False, call_type="pass_through_endpoint", start_time=start_time, - litellm_call_id=str(uuid.uuid4()), + litellm_call_id=litellm_call_id, function_id="1245", ) passthrough_logging_payload = PassthroughStandardLoggingPayload( url=str(url), request_body=_parsed_body, ) - + kwargs = _init_kwargs_for_pass_through_endpoint( + user_api_key_dict=user_api_key_dict, + _parsed_body=_parsed_body, + passthrough_logging_payload=passthrough_logging_payload, + litellm_call_id=litellm_call_id, + request=request, + ) # done for supporting 'parallel_request_limiter.py' with pass-through endpoints - kwargs = { - "litellm_params": { - "metadata": { - "user_api_key": user_api_key_dict.api_key, - "user_api_key_user_id": user_api_key_dict.user_id, - "user_api_key_team_id": user_api_key_dict.team_id, - "user_api_key_end_user_id": user_api_key_dict.user_id, - } - }, - "call_type": "pass_through_endpoint", - "passthrough_logging_payload": passthrough_logging_payload, - } logging_obj.update_environment_variables( model="unknown", user="unknown", @@ -415,6 +403,7 @@ async def pass_through_request( # noqa: PLR0915 litellm_params=kwargs["litellm_params"], call_type="pass_through_endpoint", ) + logging_obj.model_call_details["litellm_call_id"] = litellm_call_id # combine url with query params for logging @@ -446,7 +435,6 @@ async def pass_through_request( # noqa: PLR0915 "headers": headers, }, ) - if stream: req = async_client.build_request( "POST", @@ -466,14 +454,19 @@ async def pass_through_request( # noqa: PLR0915 ) return StreamingResponse( - stream_response( + PassThroughStreamingHandler.chunk_processor( response=response, - logging_obj=logging_obj, + request_body=_parsed_body, + litellm_logging_obj=logging_obj, endpoint_type=endpoint_type, start_time=start_time, - url=str(url), + passthrough_success_handler_obj=pass_through_endpoint_logging, + url_route=str(url), + ), + headers=get_response_headers( + headers=response.headers, + litellm_call_id=litellm_call_id, ), - headers=get_response_headers(response.headers), status_code=response.status_code, ) @@ -504,14 +497,19 @@ async def pass_through_request( # noqa: PLR0915 ) return StreamingResponse( - stream_response( + PassThroughStreamingHandler.chunk_processor( response=response, - logging_obj=logging_obj, + request_body=_parsed_body, + litellm_logging_obj=logging_obj, endpoint_type=endpoint_type, start_time=start_time, - url=str(url), + passthrough_success_handler_obj=pass_through_endpoint_logging, + url_route=str(url), + ), + headers=get_response_headers( + headers=response.headers, + litellm_call_id=litellm_call_id, ), - headers=get_response_headers(response.headers), status_code=response.status_code, ) @@ -531,22 +529,27 @@ async def pass_through_request( # noqa: PLR0915 response_body: Optional[dict] = get_response_body(response) passthrough_logging_payload["response_body"] = response_body end_time = datetime.now() - await pass_through_endpoint_logging.pass_through_async_success_handler( - httpx_response=response, - response_body=response_body, - url_route=str(url), - result="", - start_time=start_time, - end_time=end_time, - logging_obj=logging_obj, - cache_hit=False, - **kwargs, + asyncio.create_task( + pass_through_endpoint_logging.pass_through_async_success_handler( + httpx_response=response, + response_body=response_body, + url_route=str(url), + result="", + start_time=start_time, + end_time=end_time, + logging_obj=logging_obj, + cache_hit=False, + **kwargs, + ) ) return Response( content=content, status_code=response.status_code, - headers=get_response_headers(response.headers), + headers=get_response_headers( + headers=response.headers, + litellm_call_id=litellm_call_id, + ), ) except Exception as e: verbose_proxy_logger.exception( @@ -571,6 +574,52 @@ async def pass_through_request( # noqa: PLR0915 ) +def _init_kwargs_for_pass_through_endpoint( + request: Request, + user_api_key_dict: UserAPIKeyAuth, + passthrough_logging_payload: PassthroughStandardLoggingPayload, + _parsed_body: Optional[dict] = None, + litellm_call_id: Optional[str] = None, +) -> dict: + _parsed_body = _parsed_body or {} + _litellm_metadata: Optional[dict] = _parsed_body.pop("litellm_metadata", None) + _metadata = { + "user_api_key": user_api_key_dict.api_key, + "user_api_key_user_id": user_api_key_dict.user_id, + "user_api_key_team_id": user_api_key_dict.team_id, + "user_api_key_end_user_id": user_api_key_dict.user_id, + } + if _litellm_metadata: + _metadata.update(_litellm_metadata) + + _metadata = _update_metadata_with_tags_in_header( + request=request, + metadata=_metadata, + ) + + kwargs = { + "litellm_params": { + "metadata": _metadata, + }, + "call_type": "pass_through_endpoint", + "litellm_call_id": litellm_call_id, + "passthrough_logging_payload": passthrough_logging_payload, + } + return kwargs + + +def _update_metadata_with_tags_in_header(request: Request, metadata: dict) -> dict: + """ + If tags are in the request headers, add them to the metadata + + Used for google and vertex JS SDKs + """ + _tags = request.headers.get("tags") + if _tags: + metadata["tags"] = _tags.split(",") + return metadata + + def create_pass_through_route( endpoint, target: str, diff --git a/litellm/proxy/pass_through_endpoints/streaming_handler.py b/litellm/proxy/pass_through_endpoints/streaming_handler.py index b7faa21e4..adfd49c78 100644 --- a/litellm/proxy/pass_through_endpoints/streaming_handler.py +++ b/litellm/proxy/pass_through_endpoints/streaming_handler.py @@ -1,117 +1,173 @@ import asyncio import json +import threading from datetime import datetime from enum import Enum from typing import AsyncIterable, Dict, List, Optional, Union +import httpx + import litellm +from litellm._logging import verbose_proxy_logger from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.anthropic.chat.handler import ( + ModelResponseIterator as AnthropicIterator, +) from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import ( ModelResponseIterator as VertexAIIterator, ) -from litellm.types.utils import GenericStreamingChunk +from litellm.proxy._types import PassThroughEndpointLoggingResultValues +from litellm.types.utils import ( + GenericStreamingChunk, + ModelResponse, + StandardPassThroughResponseObject, +) +from .llm_provider_handlers.anthropic_passthrough_logging_handler import ( + AnthropicPassthroughLoggingHandler, +) +from .llm_provider_handlers.vertex_passthrough_logging_handler import ( + VertexPassthroughLoggingHandler, +) from .success_handler import PassThroughEndpointLogging from .types import EndpointType -def get_litellm_chunk( - model_iterator: VertexAIIterator, - custom_stream_wrapper: litellm.utils.CustomStreamWrapper, - chunk_dict: Dict, -) -> Optional[Dict]: +class PassThroughStreamingHandler: - generic_chunk: GenericStreamingChunk = model_iterator.chunk_parser(chunk_dict) - if generic_chunk: - return custom_stream_wrapper.chunk_creator(chunk=generic_chunk) - return None + @staticmethod + async def chunk_processor( + response: httpx.Response, + request_body: Optional[dict], + litellm_logging_obj: LiteLLMLoggingObj, + endpoint_type: EndpointType, + start_time: datetime, + passthrough_success_handler_obj: PassThroughEndpointLogging, + url_route: str, + ): + """ + - Yields chunks from the response + - Collect non-empty chunks for post-processing (logging) + """ + try: + raw_bytes: List[bytes] = [] + async for chunk in response.aiter_bytes(): + raw_bytes.append(chunk) + yield chunk + # After all chunks are processed, handle post-processing + end_time = datetime.now() -def get_iterator_class_from_endpoint_type( - endpoint_type: EndpointType, -) -> Optional[type]: - if endpoint_type == EndpointType.VERTEX_AI: - return VertexAIIterator - return None - - -async def chunk_processor( - aiter_bytes: AsyncIterable[bytes], - litellm_logging_obj: LiteLLMLoggingObj, - endpoint_type: EndpointType, - start_time: datetime, - passthrough_success_handler_obj: PassThroughEndpointLogging, - url_route: str, -) -> AsyncIterable[bytes]: - - iteratorClass = get_iterator_class_from_endpoint_type(endpoint_type) - if iteratorClass is None: - # Generic endpoint - litellm does not do any tracking / logging for this - async for chunk in aiter_bytes: - yield chunk - else: - # known streaming endpoint - litellm will do tracking / logging for this - model_iterator = iteratorClass( - sync_stream=False, streaming_response=aiter_bytes - ) - custom_stream_wrapper = litellm.utils.CustomStreamWrapper( - completion_stream=aiter_bytes, model=None, logging_obj=litellm_logging_obj - ) - buffer = b"" - all_chunks = [] - async for chunk in aiter_bytes: - buffer += chunk - try: - _decoded_chunk = chunk.decode("utf-8") - _chunk_dict = json.loads(_decoded_chunk) - litellm_chunk = get_litellm_chunk( - model_iterator, custom_stream_wrapper, _chunk_dict + asyncio.create_task( + PassThroughStreamingHandler._route_streaming_logging_to_handler( + litellm_logging_obj=litellm_logging_obj, + passthrough_success_handler_obj=passthrough_success_handler_obj, + url_route=url_route, + request_body=request_body or {}, + endpoint_type=endpoint_type, + start_time=start_time, + raw_bytes=raw_bytes, + end_time=end_time, ) - if litellm_chunk: - all_chunks.append(litellm_chunk) - except json.JSONDecodeError: - pass - finally: - yield chunk # Yield the original bytes + ) + except Exception as e: + verbose_proxy_logger.error(f"Error in chunk_processor: {str(e)}") + raise - # Process any remaining data in the buffer - if buffer: - try: - _chunk_dict = json.loads(buffer.decode("utf-8")) + @staticmethod + async def _route_streaming_logging_to_handler( + litellm_logging_obj: LiteLLMLoggingObj, + passthrough_success_handler_obj: PassThroughEndpointLogging, + url_route: str, + request_body: dict, + endpoint_type: EndpointType, + start_time: datetime, + raw_bytes: List[bytes], + end_time: datetime, + ): + """ + Route the logging for the collected chunks to the appropriate handler - if isinstance(_chunk_dict, list): - for _chunk in _chunk_dict: - litellm_chunk = get_litellm_chunk( - model_iterator, custom_stream_wrapper, _chunk - ) - if litellm_chunk: - all_chunks.append(litellm_chunk) - elif isinstance(_chunk_dict, dict): - litellm_chunk = get_litellm_chunk( - model_iterator, custom_stream_wrapper, _chunk_dict - ) - if litellm_chunk: - all_chunks.append(litellm_chunk) - except json.JSONDecodeError: - pass - - complete_streaming_response: Optional[ - Union[litellm.ModelResponse, litellm.TextCompletionResponse] - ] = litellm.stream_chunk_builder(chunks=all_chunks) - if complete_streaming_response is None: - complete_streaming_response = litellm.ModelResponse() - end_time = datetime.now() - - if passthrough_success_handler_obj.is_vertex_route(url_route): - _model = passthrough_success_handler_obj.extract_model_from_url(url_route) - complete_streaming_response.model = _model - litellm_logging_obj.model = _model - litellm_logging_obj.model_call_details["model"] = _model - - asyncio.create_task( - litellm_logging_obj.async_success_handler( - result=complete_streaming_response, + Supported endpoint types: + - Anthropic + - Vertex AI + """ + all_chunks = PassThroughStreamingHandler._convert_raw_bytes_to_str_lines( + raw_bytes + ) + standard_logging_response_object: Optional[ + PassThroughEndpointLoggingResultValues + ] = None + kwargs: dict = {} + if endpoint_type == EndpointType.ANTHROPIC: + anthropic_passthrough_logging_handler_result = AnthropicPassthroughLoggingHandler._handle_logging_anthropic_collected_chunks( + litellm_logging_obj=litellm_logging_obj, + passthrough_success_handler_obj=passthrough_success_handler_obj, + url_route=url_route, + request_body=request_body, + endpoint_type=endpoint_type, start_time=start_time, + all_chunks=all_chunks, end_time=end_time, ) + standard_logging_response_object = ( + anthropic_passthrough_logging_handler_result["result"] + ) + kwargs = anthropic_passthrough_logging_handler_result["kwargs"] + elif endpoint_type == EndpointType.VERTEX_AI: + vertex_passthrough_logging_handler_result = ( + VertexPassthroughLoggingHandler._handle_logging_vertex_collected_chunks( + litellm_logging_obj=litellm_logging_obj, + passthrough_success_handler_obj=passthrough_success_handler_obj, + url_route=url_route, + request_body=request_body, + endpoint_type=endpoint_type, + start_time=start_time, + all_chunks=all_chunks, + end_time=end_time, + ) + ) + standard_logging_response_object = ( + vertex_passthrough_logging_handler_result["result"] + ) + kwargs = vertex_passthrough_logging_handler_result["kwargs"] + + if standard_logging_response_object is None: + standard_logging_response_object = StandardPassThroughResponseObject( + response=f"cannot parse chunks to standard response object. Chunks={all_chunks}" + ) + threading.Thread( + target=litellm_logging_obj.success_handler, + args=( + standard_logging_response_object, + start_time, + end_time, + False, + ), + ).start() + await litellm_logging_obj.async_success_handler( + result=standard_logging_response_object, + start_time=start_time, + end_time=end_time, + cache_hit=False, + **kwargs, ) + + @staticmethod + def _convert_raw_bytes_to_str_lines(raw_bytes: List[bytes]) -> List[str]: + """ + Converts a list of raw bytes into a list of string lines, similar to aiter_lines() + + Args: + raw_bytes: List of bytes chunks from aiter.bytes() + + Returns: + List of string lines, with each line being a complete data: {} chunk + """ + # Combine all bytes and decode to string + combined_str = b"".join(raw_bytes).decode("utf-8") + + # Split by newlines and filter out empty lines + lines = [line.strip() for line in combined_str.split("\n") if line.strip()] + + return lines diff --git a/litellm/proxy/pass_through_endpoints/success_handler.py b/litellm/proxy/pass_through_endpoints/success_handler.py index 05ba53fa0..b603510ff 100644 --- a/litellm/proxy/pass_through_endpoints/success_handler.py +++ b/litellm/proxy/pass_through_endpoints/success_handler.py @@ -12,12 +12,20 @@ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging from litellm.litellm_core_utils.litellm_logging import ( get_standard_logging_object_payload, ) -from litellm.llms.anthropic.chat.transformation import AnthropicConfig from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import ( VertexLLM, ) +from litellm.proxy._types import PassThroughEndpointLoggingResultValues from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.types.utils import StandardPassThroughResponseObject +from litellm.utils import executor as thread_pool_executor + +from .llm_provider_handlers.anthropic_passthrough_logging_handler import ( + AnthropicPassthroughLoggingHandler, +) +from .llm_provider_handlers.vertex_passthrough_logging_handler import ( + VertexPassthroughLoggingHandler, +) class PassThroughEndpointLogging: @@ -43,53 +51,70 @@ class PassThroughEndpointLogging: cache_hit: bool, **kwargs, ): + standard_logging_response_object: Optional[ + PassThroughEndpointLoggingResultValues + ] = None if self.is_vertex_route(url_route): - await self.vertex_passthrough_handler( - httpx_response=httpx_response, - logging_obj=logging_obj, - url_route=url_route, - result=result, - start_time=start_time, - end_time=end_time, - cache_hit=cache_hit, - **kwargs, + vertex_passthrough_logging_handler_result = ( + VertexPassthroughLoggingHandler.vertex_passthrough_handler( + httpx_response=httpx_response, + logging_obj=logging_obj, + url_route=url_route, + result=result, + start_time=start_time, + end_time=end_time, + cache_hit=cache_hit, + **kwargs, + ) ) + standard_logging_response_object = ( + vertex_passthrough_logging_handler_result["result"] + ) + kwargs = vertex_passthrough_logging_handler_result["kwargs"] elif self.is_anthropic_route(url_route): - await self.anthropic_passthrough_handler( - httpx_response=httpx_response, - response_body=response_body or {}, - logging_obj=logging_obj, - url_route=url_route, - result=result, - start_time=start_time, - end_time=end_time, - cache_hit=cache_hit, - **kwargs, + anthropic_passthrough_logging_handler_result = ( + AnthropicPassthroughLoggingHandler.anthropic_passthrough_handler( + httpx_response=httpx_response, + response_body=response_body or {}, + logging_obj=logging_obj, + url_route=url_route, + result=result, + start_time=start_time, + end_time=end_time, + cache_hit=cache_hit, + **kwargs, + ) ) - else: + + standard_logging_response_object = ( + anthropic_passthrough_logging_handler_result["result"] + ) + kwargs = anthropic_passthrough_logging_handler_result["kwargs"] + if standard_logging_response_object is None: standard_logging_response_object = StandardPassThroughResponseObject( response=httpx_response.text ) - threading.Thread( - target=logging_obj.success_handler, - args=( - standard_logging_response_object, - start_time, - end_time, - cache_hit, - ), - ).start() - await logging_obj.async_success_handler( - result=( - json.dumps(result) - if isinstance(result, dict) - else standard_logging_response_object - ), - start_time=start_time, - end_time=end_time, - cache_hit=False, - **kwargs, - ) + thread_pool_executor.submit( + logging_obj.success_handler, + args=( + standard_logging_response_object, + start_time, + end_time, + cache_hit, + ), + ) + + await logging_obj.async_success_handler( + result=( + json.dumps(result) + if isinstance(result, dict) + else standard_logging_response_object + ), + start_time=start_time, + end_time=end_time, + cache_hit=False, + **kwargs, + ) def is_vertex_route(self, url_route: str): for route in self.TRACKED_VERTEX_ROUTES: @@ -102,166 +127,3 @@ class PassThroughEndpointLogging: if route in url_route: return True return False - - def extract_model_from_url(self, url: str) -> str: - pattern = r"/models/([^:]+)" - match = re.search(pattern, url) - if match: - return match.group(1) - return "unknown" - - async def anthropic_passthrough_handler( - self, - httpx_response: httpx.Response, - response_body: dict, - logging_obj: LiteLLMLoggingObj, - url_route: str, - result: str, - start_time: datetime, - end_time: datetime, - cache_hit: bool, - **kwargs, - ): - """ - Transforms Anthropic response to OpenAI response, generates a standard logging object so downstream logging can be handled - """ - model = response_body.get("model", "") - litellm_model_response: litellm.ModelResponse = ( - AnthropicConfig._process_response( - response=httpx_response, - model_response=litellm.ModelResponse(), - model=model, - stream=False, - messages=[], - logging_obj=logging_obj, - optional_params={}, - api_key="", - data={}, - print_verbose=litellm.print_verbose, - encoding=None, - json_mode=False, - ) - ) - - response_cost = litellm.completion_cost( - completion_response=litellm_model_response, - model=model, - ) - kwargs["response_cost"] = response_cost - kwargs["model"] = model - - # Make standard logging object for Vertex AI - standard_logging_object = get_standard_logging_object_payload( - kwargs=kwargs, - init_response_obj=litellm_model_response, - start_time=start_time, - end_time=end_time, - logging_obj=logging_obj, - status="success", - ) - - # pretty print standard logging object - verbose_proxy_logger.debug( - "standard_logging_object= %s", json.dumps(standard_logging_object, indent=4) - ) - kwargs["standard_logging_object"] = standard_logging_object - - await logging_obj.async_success_handler( - result=litellm_model_response, - start_time=start_time, - end_time=end_time, - cache_hit=cache_hit, - **kwargs, - ) - - pass - - async def vertex_passthrough_handler( - self, - httpx_response: httpx.Response, - logging_obj: LiteLLMLoggingObj, - url_route: str, - result: str, - start_time: datetime, - end_time: datetime, - cache_hit: bool, - **kwargs, - ): - if "generateContent" in url_route: - model = self.extract_model_from_url(url_route) - - instance_of_vertex_llm = litellm.VertexGeminiConfig() - litellm_model_response: litellm.ModelResponse = ( - instance_of_vertex_llm._transform_response( - model=model, - messages=[ - {"role": "user", "content": "no-message-pass-through-endpoint"} - ], - response=httpx_response, - model_response=litellm.ModelResponse(), - logging_obj=logging_obj, - optional_params={}, - litellm_params={}, - api_key="", - data={}, - print_verbose=litellm.print_verbose, - encoding=None, - ) - ) - logging_obj.model = litellm_model_response.model or model - logging_obj.model_call_details["model"] = logging_obj.model - - await logging_obj.async_success_handler( - result=litellm_model_response, - start_time=start_time, - end_time=end_time, - cache_hit=cache_hit, - **kwargs, - ) - elif "predict" in url_route: - from litellm.llms.vertex_ai_and_google_ai_studio.image_generation.image_generation_handler import ( - VertexImageGeneration, - ) - from litellm.types.utils import PassthroughCallTypes - - vertex_image_generation_class = VertexImageGeneration() - - model = self.extract_model_from_url(url_route) - _json_response = httpx_response.json() - - litellm_prediction_response: Union[ - litellm.ModelResponse, litellm.EmbeddingResponse, litellm.ImageResponse - ] = litellm.ModelResponse() - if vertex_image_generation_class.is_image_generation_response( - _json_response - ): - litellm_prediction_response = ( - vertex_image_generation_class.process_image_generation_response( - _json_response, - model_response=litellm.ImageResponse(), - model=model, - ) - ) - - logging_obj.call_type = ( - PassthroughCallTypes.passthrough_image_generation.value - ) - else: - litellm_prediction_response = litellm.vertexAITextEmbeddingConfig.transform_vertex_response_to_openai( - response=_json_response, - model=model, - model_response=litellm.EmbeddingResponse(), - ) - if isinstance(litellm_prediction_response, litellm.EmbeddingResponse): - litellm_prediction_response.model = model - - logging_obj.model = model - logging_obj.model_call_details["model"] = logging_obj.model - - await logging_obj.async_success_handler( - result=litellm_prediction_response, - start_time=start_time, - end_time=end_time, - cache_hit=cache_hit, - **kwargs, - ) diff --git a/litellm/proxy/proxy_config.yaml b/litellm/proxy/proxy_config.yaml index 3fc7ecfe2..968cb8b39 100644 --- a/litellm/proxy/proxy_config.yaml +++ b/litellm/proxy/proxy_config.yaml @@ -1,18 +1,5 @@ -model_list: - - model_name: gpt-4o - litellm_params: - model: openai/gpt-4o - api_key: os.environ/OPENAI_API_KEY - - -router_settings: - provider_budget_config: - openai: - budget_limit: 0.000000000001 # float of $ value budget for time period - time_period: 1d # can be 1d, 2d, 30d - azure: - budget_limit: 100 - time_period: 1d +include: + - model_config.yaml litellm_settings: - callbacks: ["prometheus"] + callbacks: ["datadog"] diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 9d7c120a7..ca6d4f363 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -134,7 +134,10 @@ from litellm.proxy.auth.model_checks import ( get_key_models, get_team_models, ) -from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.auth.user_api_key_auth import ( + user_api_key_auth, + user_api_key_auth_websocket, +) ## Import All Misc routes here ## from litellm.proxy.caching_routes import router as caching_router @@ -173,6 +176,7 @@ from litellm.proxy.health_endpoints._health_endpoints import router as health_ro from litellm.proxy.hooks.prompt_injection_detection import ( _OPTIONAL_PromptInjectionDetection, ) +from litellm.proxy.hooks.proxy_failure_handler import _PROXY_failure_handler from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request from litellm.proxy.management_endpoints.customer_endpoints import ( router as customer_router, @@ -182,8 +186,8 @@ from litellm.proxy.management_endpoints.internal_user_endpoints import ( ) from litellm.proxy.management_endpoints.internal_user_endpoints import user_update from litellm.proxy.management_endpoints.key_management_endpoints import ( - _duration_in_seconds, delete_verification_token, + duration_in_seconds, generate_key_helper_fn, ) from litellm.proxy.management_endpoints.key_management_endpoints import ( @@ -268,6 +272,7 @@ from litellm.types.llms.anthropic import ( from litellm.types.llms.openai import HttpxBinaryResponseContent from litellm.types.router import RouterGeneralSettings from litellm.types.utils import StandardLoggingPayload +from litellm.utils import get_end_user_id_for_cost_tracking try: from litellm._version import version @@ -525,14 +530,6 @@ db_writer_client: Optional[HTTPHandler] = None ### logger ### -def _get_pydantic_json_dict(pydantic_obj: BaseModel) -> dict: - try: - return pydantic_obj.model_dump() # type: ignore - except Exception: - # if using pydantic v1 - return pydantic_obj.dict() - - def get_custom_headers( *, user_api_key_dict: UserAPIKeyAuth, @@ -686,68 +683,6 @@ def cost_tracking(): litellm._async_success_callback.append(_PROXY_track_cost_callback) # type: ignore -async def _PROXY_failure_handler( - kwargs, # kwargs to completion - completion_response: litellm.ModelResponse, # response from completion - start_time=None, - end_time=None, # start/end time for completion -): - global prisma_client - if prisma_client is not None: - verbose_proxy_logger.debug( - "inside _PROXY_failure_handler kwargs=", extra=kwargs - ) - - _exception = kwargs.get("exception") - _exception_type = _exception.__class__.__name__ - _model = kwargs.get("model", None) - - _optional_params = kwargs.get("optional_params", {}) - _optional_params = copy.deepcopy(_optional_params) - - for k, v in _optional_params.items(): - v = str(v) - v = v[:100] - - _status_code = "500" - try: - _status_code = str(_exception.status_code) - except Exception: - # Don't let this fail logging the exception to the dB - pass - - _litellm_params = kwargs.get("litellm_params", {}) or {} - _metadata = _litellm_params.get("metadata", {}) or {} - _model_id = _metadata.get("model_info", {}).get("id", "") - _model_group = _metadata.get("model_group", "") - api_base = litellm.get_api_base(model=_model, optional_params=_litellm_params) - _exception_string = str(_exception) - - error_log = LiteLLM_ErrorLogs( - request_id=str(uuid.uuid4()), - model_group=_model_group, - model_id=_model_id, - litellm_model_name=kwargs.get("model"), - request_kwargs=_optional_params, - api_base=api_base, - exception_type=_exception_type, - status_code=_status_code, - exception_string=_exception_string, - startTime=kwargs.get("start_time"), - endTime=kwargs.get("end_time"), - ) - - # helper function to convert to dict on pydantic v2 & v1 - error_log_dict = _get_pydantic_json_dict(error_log) - error_log_dict["request_kwargs"] = json.dumps(error_log_dict["request_kwargs"]) - - await prisma_client.db.litellm_errorlogs.create( - data=error_log_dict # type: ignore - ) - - pass - - @log_db_metrics async def _PROXY_track_cost_callback( kwargs, # kwargs to completion @@ -763,8 +698,7 @@ async def _PROXY_track_cost_callback( ) parent_otel_span = _get_parent_otel_span_from_kwargs(kwargs=kwargs) litellm_params = kwargs.get("litellm_params", {}) or {} - proxy_server_request = litellm_params.get("proxy_server_request") or {} - end_user_id = proxy_server_request.get("body", {}).get("user", None) + end_user_id = get_end_user_id_for_cost_tracking(litellm_params) metadata = get_litellm_metadata_from_kwargs(kwargs=kwargs) user_id = metadata.get("user_api_key_user_id", None) team_id = metadata.get("user_api_key_team_id", None) @@ -1377,6 +1311,16 @@ class ProxyConfig: _, file_extension = os.path.splitext(config_file_path) return file_extension.lower() == ".yaml" or file_extension.lower() == ".yml" + def _load_yaml_file(self, file_path: str) -> dict: + """ + Load and parse a YAML file + """ + try: + with open(file_path, "r") as file: + return yaml.safe_load(file) or {} + except Exception as e: + raise Exception(f"Error loading yaml file {file_path}: {str(e)}") + async def _get_config_from_file( self, config_file_path: Optional[str] = None ) -> dict: @@ -1407,6 +1351,51 @@ class ProxyConfig: "litellm_settings": {}, } + # Process includes + config = self._process_includes( + config=config, base_dir=os.path.dirname(os.path.abspath(file_path or "")) + ) + + verbose_proxy_logger.debug(f"loaded config={json.dumps(config, indent=4)}") + return config + + def _process_includes(self, config: dict, base_dir: str) -> dict: + """ + Process includes by appending their contents to the main config + + Handles nested config.yamls with `include` section + + Example config: This will get the contents from files in `include` and append it + ```yaml + include: + - model_config.yaml + + litellm_settings: + callbacks: ["prometheus"] + ``` + """ + if "include" not in config: + return config + + if not isinstance(config["include"], list): + raise ValueError("'include' must be a list of file paths") + + # Load and append all included files + for include_file in config["include"]: + file_path = os.path.join(base_dir, include_file) + if not os.path.exists(file_path): + raise FileNotFoundError(f"Included file not found: {file_path}") + + included_config = self._load_yaml_file(file_path) + # Simply update/extend the main config with included config + for key, value in included_config.items(): + if isinstance(value, list) and key in config: + config[key].extend(value) + else: + config[key] = value + + # Remove the include directive + del config["include"] return config async def save_config(self, new_config: dict): @@ -4339,7 +4328,11 @@ from litellm import _arealtime @app.websocket("/v1/realtime") -async def websocket_endpoint(websocket: WebSocket, model: str): +async def websocket_endpoint( + websocket: WebSocket, + model: str, + user_api_key_dict=Depends(user_api_key_auth_websocket), +): import websockets await websocket.accept() @@ -5663,11 +5656,11 @@ async def anthropic_response( # noqa: PLR0915 user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): """ - This is a BETA endpoint that calls 100+ LLMs in the anthropic format. + 🚨 DEPRECATED ENDPOINT🚨 - To do a simple pass-through for anthropic, do `{PROXY_BASE_URL}/anthropic/v1/messages` + Use `{PROXY_BASE_URL}/anthropic/v1/messages` instead - [Docs](https://docs.litellm.ai/docs/anthropic_completion). - Docs - https://docs.litellm.ai/docs/anthropic_completion + This was a BETA endpoint that calls 100+ LLMs in the anthropic format. """ from litellm import adapter_completion from litellm.adapters.anthropic_adapter import anthropic_adapter diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py index 3c5c8b3b4..ec9850eeb 100644 --- a/litellm/proxy/route_llm_request.py +++ b/litellm/proxy/route_llm_request.py @@ -86,7 +86,6 @@ async def route_request( else: models = [model.strip() for model in data.pop("model").split(",")] return llm_router.abatch_completion(models=models, **data) - elif llm_router is not None: if ( data["model"] in router_model_names @@ -113,6 +112,9 @@ async def route_request( or len(llm_router.pattern_router.patterns) > 0 ): return getattr(llm_router, f"{route_type}")(**data) + elif route_type == "amoderation": + # moderation endpoint does not require `model` parameter + return getattr(llm_router, f"{route_type}")(**data) elif user_model is not None: return getattr(litellm, f"{route_type}")(**data) diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index 74bf398e7..1fe944a72 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -26,6 +26,11 @@ from typing import ( overload, ) +from litellm.litellm_core_utils.duration_parser import ( + _extract_from_regex, + duration_in_seconds, + get_last_day_of_month, +) from litellm.proxy._types import ProxyErrorTypes, ProxyException try: @@ -337,14 +342,14 @@ class ProxyLogging: alert_to_webhook_url=self.alert_to_webhook_url, ) - if ( - self.alerting is not None - and "slack" in self.alerting - and "daily_reports" in self.alert_types - ): + if self.alerting is not None and "slack" in self.alerting: # NOTE: ENSURE we only add callbacks when alerting is on # We should NOT add callbacks when alerting is off - litellm.callbacks.append(self.slack_alerting_instance) # type: ignore + if "daily_reports" in self.alert_types: + litellm.callbacks.append(self.slack_alerting_instance) # type: ignore + litellm.success_callback.append( + self.slack_alerting_instance.response_taking_too_long_callback + ) if redis_cache is not None: self.internal_usage_cache.dual_cache.redis_cache = redis_cache @@ -354,9 +359,6 @@ class ProxyLogging: litellm.callbacks.append(self.max_budget_limiter) # type: ignore litellm.callbacks.append(self.cache_control_check) # type: ignore litellm.callbacks.append(self.service_logging_obj) # type: ignore - litellm.success_callback.append( - self.slack_alerting_instance.response_taking_too_long_callback - ) for callback in litellm.callbacks: if isinstance(callback, str): callback = litellm.litellm_core_utils.litellm_logging._init_custom_logger_compatible_class( # type: ignore @@ -852,6 +854,20 @@ class ProxyLogging: ), ).start() + await self._run_post_call_failure_hook_custom_loggers( + original_exception=original_exception, + request_data=request_data, + user_api_key_dict=user_api_key_dict, + ) + + return + + async def _run_post_call_failure_hook_custom_loggers( + self, + original_exception: Exception, + request_data: dict, + user_api_key_dict: UserAPIKeyAuth, + ): for callback in litellm.callbacks: try: _callback: Optional[CustomLogger] = None @@ -870,7 +886,38 @@ class ProxyLogging: except Exception as e: raise e - return + async def async_log_proxy_authentication_errors( + self, + original_exception: Exception, + request: Request, + parent_otel_span: Optional[Any], + api_key: Optional[str], + ): + """ + Handler for Logging Authentication Errors on LiteLLM Proxy + Why not use post_call_failure_hook? + - `post_call_failure_hook` calls `litellm_logging_obj.async_failure_handler`. This led to the Exception being logged twice + + What does this handler do? + - Logs Authentication Errors (like invalid API Key passed) to CustomLogger compatible classes (OTEL, Datadog etc) + - calls CustomLogger.async_post_call_failure_hook + """ + + user_api_key_dict = UserAPIKeyAuth( + parent_otel_span=parent_otel_span, + token=_hash_token_if_needed(token=api_key or ""), + ) + try: + request_data = await request.json() + except json.JSONDecodeError: + # For GET requests or requests without a JSON body + request_data = {} + await self._run_post_call_failure_hook_custom_loggers( + original_exception=original_exception, + request_data=request_data, + user_api_key_dict=user_api_key_dict, + ) + pass async def post_call_success_hook( self, @@ -2432,86 +2479,6 @@ def _hash_token_if_needed(token: str) -> str: return token -def _extract_from_regex(duration: str) -> Tuple[int, str]: - match = re.match(r"(\d+)(mo|[smhd]?)", duration) - - if not match: - raise ValueError("Invalid duration format") - - value, unit = match.groups() - value = int(value) - - return value, unit - - -def get_last_day_of_month(year, month): - # Handle December case - if month == 12: - return 31 - # Next month is January, so subtract a day from March 1st - next_month = datetime(year=year, month=month + 1, day=1) - last_day_of_month = (next_month - timedelta(days=1)).day - return last_day_of_month - - -def _duration_in_seconds(duration: str) -> int: - """ - Parameters: - - duration: - - "s" - seconds - - "m" - minutes - - "h" - hours - - "d" - days - - "mo" - months - - Returns time in seconds till when budget needs to be reset - """ - value, unit = _extract_from_regex(duration=duration) - - if unit == "s": - return value - elif unit == "m": - return value * 60 - elif unit == "h": - return value * 3600 - elif unit == "d": - return value * 86400 - elif unit == "mo": - now = time.time() - current_time = datetime.fromtimestamp(now) - - if current_time.month == 12: - target_year = current_time.year + 1 - target_month = 1 - else: - target_year = current_time.year - target_month = current_time.month + value - - # Determine the day to set for next month - target_day = current_time.day - last_day_of_target_month = get_last_day_of_month(target_year, target_month) - - if target_day > last_day_of_target_month: - target_day = last_day_of_target_month - - next_month = datetime( - year=target_year, - month=target_month, - day=target_day, - hour=current_time.hour, - minute=current_time.minute, - second=current_time.second, - microsecond=current_time.microsecond, - ) - - # Calculate the duration until the first day of the next month - duration_until_next_month = next_month - current_time - return int(duration_until_next_month.total_seconds()) - - else: - raise ValueError("Unsupported duration unit") - - async def reset_budget(prisma_client: PrismaClient): """ Gets all the non-expired keys for a db, which need spend to be reset @@ -2530,7 +2497,7 @@ async def reset_budget(prisma_client: PrismaClient): if keys_to_reset is not None and len(keys_to_reset) > 0: for key in keys_to_reset: key.spend = 0.0 - duration_s = _duration_in_seconds(duration=key.budget_duration) + duration_s = duration_in_seconds(duration=key.budget_duration) key.budget_reset_at = now + timedelta(seconds=duration_s) await prisma_client.update_data( @@ -2546,7 +2513,7 @@ async def reset_budget(prisma_client: PrismaClient): if users_to_reset is not None and len(users_to_reset) > 0: for user in users_to_reset: user.spend = 0.0 - duration_s = _duration_in_seconds(duration=user.budget_duration) + duration_s = duration_in_seconds(duration=user.budget_duration) user.budget_reset_at = now + timedelta(seconds=duration_s) await prisma_client.update_data( @@ -2564,7 +2531,7 @@ async def reset_budget(prisma_client: PrismaClient): if teams_to_reset is not None and len(teams_to_reset) > 0: team_reset_requests = [] for team in teams_to_reset: - duration_s = _duration_in_seconds(duration=team.budget_duration) + duration_s = duration_in_seconds(duration=team.budget_duration) reset_team_budget_request = ResetTeamBudgetRequest( team_id=team.team_id, spend=0.0, diff --git a/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py b/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py index ba8653d82..8992a7330 100644 --- a/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py +++ b/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py @@ -58,12 +58,21 @@ def create_request_copy(request: Request): } -@router.api_route("/langfuse/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"]) +@router.api_route( + "/langfuse/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Langfuse Pass-through", "pass-through"], +) async def langfuse_proxy_route( endpoint: str, request: Request, fastapi_response: Response, ): + """ + Call Langfuse via LiteLLM proxy. Works with Langfuse SDK. + + [Docs](https://docs.litellm.ai/docs/pass_through/langfuse) + """ ## CHECK FOR LITELLM API KEY IN THE QUERY PARAMS - ?..key=LITELLM_API_KEY api_key = request.headers.get("Authorization") or "" diff --git a/litellm/proxy/vertex_ai_endpoints/vertex_endpoints.py b/litellm/proxy/vertex_ai_endpoints/vertex_endpoints.py index 98e2a707d..03f4ac9cd 100644 --- a/litellm/proxy/vertex_ai_endpoints/vertex_endpoints.py +++ b/litellm/proxy/vertex_ai_endpoints/vertex_endpoints.py @@ -28,25 +28,54 @@ from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( create_pass_through_route, ) +from litellm.secret_managers.main import get_secret_str +from litellm.types.passthrough_endpoints.vertex_ai import * router = APIRouter() -default_vertex_config = None + +default_vertex_config: VertexPassThroughCredentials = VertexPassThroughCredentials() -def set_default_vertex_config(config): +def _get_vertex_env_vars() -> VertexPassThroughCredentials: + """ + Helper to get vertex pass through config from environment variables + + The following environment variables are used: + - DEFAULT_VERTEXAI_PROJECT (project id) + - DEFAULT_VERTEXAI_LOCATION (location) + - DEFAULT_GOOGLE_APPLICATION_CREDENTIALS (path to credentials file) + """ + return VertexPassThroughCredentials( + vertex_project=get_secret_str("DEFAULT_VERTEXAI_PROJECT"), + vertex_location=get_secret_str("DEFAULT_VERTEXAI_LOCATION"), + vertex_credentials=get_secret_str("DEFAULT_GOOGLE_APPLICATION_CREDENTIALS"), + ) + + +def set_default_vertex_config(config: Optional[dict] = None): + """Sets vertex configuration from provided config and/or environment variables + + Args: + config (Optional[dict]): Configuration dictionary + Example: { + "vertex_project": "my-project-123", + "vertex_location": "us-central1", + "vertex_credentials": "os.environ/GOOGLE_CREDS" + } + """ global default_vertex_config - if config is None: - return - if not isinstance(config, dict): - raise ValueError("invalid config, vertex default config must be a dictionary") + # Initialize config dictionary if None + if config is None: + default_vertex_config = _get_vertex_env_vars() + return if isinstance(config, dict): for key, value in config.items(): if isinstance(value, str) and value.startswith("os.environ/"): config[key] = litellm.get_secret(value) - default_vertex_config = config + default_vertex_config = VertexPassThroughCredentials(**config) def exception_handler(e: Exception): @@ -113,25 +142,42 @@ def construct_target_url( @router.api_route( - "/vertex-ai/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"] + "/vertex-ai/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Vertex AI Pass-through", "pass-through"], + include_in_schema=False, +) +@router.api_route( + "/vertex_ai/{endpoint:path}", + methods=["GET", "POST", "PUT", "DELETE", "PATCH"], + tags=["Vertex AI Pass-through", "pass-through"], ) async def vertex_proxy_route( endpoint: str, request: Request, fastapi_response: Response, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): + """ + Call LiteLLM proxy via Vertex AI SDK. + + [Docs](https://docs.litellm.ai/docs/pass_through/vertex_ai) + """ encoded_endpoint = httpx.URL(endpoint).path import re verbose_proxy_logger.debug("requested endpoint %s", endpoint) headers: dict = {} + api_key_to_use = get_litellm_virtual_key(request=request) + user_api_key_dict = await user_api_key_auth( + request=request, + api_key=api_key_to_use, + ) vertex_project = None vertex_location = None # Use headers from the incoming request if default_vertex_config is not set - if default_vertex_config is None: + if default_vertex_config.vertex_project is None: headers = dict(request.headers) or {} verbose_proxy_logger.debug( "default_vertex_config not set, incoming request headers %s", headers @@ -144,9 +190,9 @@ async def vertex_proxy_route( headers.pop("content-length", None) headers.pop("host", None) else: - vertex_project = default_vertex_config.get("vertex_project") - vertex_location = default_vertex_config.get("vertex_location") - vertex_credentials = default_vertex_config.get("vertex_credentials") + vertex_project = default_vertex_config.vertex_project + vertex_location = default_vertex_config.vertex_location + vertex_credentials = default_vertex_config.vertex_credentials base_target_url = f"https://{vertex_location}-aiplatform.googleapis.com/" @@ -194,14 +240,16 @@ async def vertex_proxy_route( verbose_proxy_logger.debug("updated url %s", updated_url) ## check for streaming + target = str(updated_url) is_streaming_request = False if "stream" in str(updated_url): is_streaming_request = True + target += "?alt=sse" ## CREATE PASS-THROUGH endpoint_func = create_pass_through_route( endpoint=endpoint, - target=str(updated_url), + target=target, custom_headers=headers, ) # dynamically construct pass-through endpoint based on incoming path received_value = await endpoint_func( @@ -212,3 +260,18 @@ async def vertex_proxy_route( ) return received_value + + +def get_litellm_virtual_key(request: Request) -> str: + """ + Extract and format API key from request headers. + Prioritizes x-litellm-api-key over Authorization header. + + + Vertex JS SDK uses `Authorization` header, we use `x-litellm-api-key` to pass litellm virtual key + + """ + litellm_api_key = request.headers.get("x-litellm-api-key") + if litellm_api_key: + return f"Bearer {litellm_api_key}" + return request.headers.get("Authorization", "") diff --git a/litellm/rerank_api/main.py b/litellm/rerank_api/main.py index 9cc8a8c1d..7e6dc7503 100644 --- a/litellm/rerank_api/main.py +++ b/litellm/rerank_api/main.py @@ -91,6 +91,7 @@ def rerank( model_info = kwargs.get("model_info", None) metadata = kwargs.get("metadata", {}) user = kwargs.get("user", None) + client = kwargs.get("client", None) try: _is_async = kwargs.pop("arerank", False) is True optional_params = GenericLiteLLMParams(**kwargs) @@ -150,7 +151,7 @@ def rerank( or optional_params.api_base or litellm.api_base or get_secret("COHERE_API_BASE") # type: ignore - or "https://api.cohere.com/v1/rerank" + or "https://api.cohere.com" ) if api_base is None: @@ -173,6 +174,7 @@ def rerank( _is_async=_is_async, headers=headers, litellm_logging_obj=litellm_logging_obj, + client=client, ) elif _custom_llm_provider == "azure_ai": api_base = ( diff --git a/litellm/router.py b/litellm/router.py index f724c96c4..89e7e8321 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -41,6 +41,7 @@ from typing import ( import httpx import openai from openai import AsyncOpenAI +from pydantic import BaseModel from typing_extensions import overload import litellm @@ -122,6 +123,7 @@ from litellm.types.router import ( ModelInfo, ProviderBudgetConfigType, RetryPolicy, + RouterCacheEnum, RouterErrors, RouterGeneralSettings, RouterModelGroupAliasItem, @@ -239,7 +241,6 @@ class Router: ] = "simple-shuffle", routing_strategy_args: dict = {}, # just for latency-based provider_budget_config: Optional[ProviderBudgetConfigType] = None, - semaphore: Optional[asyncio.Semaphore] = None, alerting_config: Optional[AlertingConfig] = None, router_general_settings: Optional[ RouterGeneralSettings @@ -315,8 +316,6 @@ class Router: from litellm._service_logger import ServiceLogging - if semaphore: - self.semaphore = semaphore self.set_verbose = set_verbose self.debug_level = debug_level self.enable_pre_call_checks = enable_pre_call_checks @@ -506,6 +505,14 @@ class Router: litellm.success_callback.append(self.sync_deployment_callback_on_success) else: litellm.success_callback = [self.sync_deployment_callback_on_success] + if isinstance(litellm._async_failure_callback, list): + litellm._async_failure_callback.append( + self.async_deployment_callback_on_failure + ) + else: + litellm._async_failure_callback = [ + self.async_deployment_callback_on_failure + ] ## COOLDOWNS ## if isinstance(litellm.failure_callback, list): litellm.failure_callback.append(self.deployment_callback_on_failure) @@ -2556,10 +2563,7 @@ class Router: original_function: Callable, **kwargs, ): - if ( - "model" in kwargs - and self.get_model_list(model_name=kwargs["model"]) is not None - ): + if kwargs.get("model") and self.get_model_list(model_name=kwargs["model"]): deployment = await self.async_get_available_deployment( model=kwargs["model"] ) @@ -3291,13 +3295,14 @@ class Router: ): """ Track remaining tpm/rpm quota for model in model_list - - Currently, only updates TPM usage. """ try: if kwargs["litellm_params"].get("metadata") is None: pass else: + deployment_name = kwargs["litellm_params"]["metadata"].get( + "deployment", None + ) # stable name - works for wildcard routes as well model_group = kwargs["litellm_params"]["metadata"].get( "model_group", None ) @@ -3308,6 +3313,8 @@ class Router: elif isinstance(id, int): id = str(id) + parent_otel_span = _get_parent_otel_span_from_kwargs(kwargs) + _usage_obj = completion_response.get("usage") total_tokens = _usage_obj.get("total_tokens", 0) if _usage_obj else 0 @@ -3319,13 +3326,14 @@ class Router: "%H-%M" ) # use the same timezone regardless of system clock - tpm_key = f"global_router:{id}:tpm:{current_minute}" + tpm_key = RouterCacheEnum.TPM.value.format( + id=id, current_minute=current_minute, model=deployment_name + ) # ------------ # Update usage # ------------ # update cache - parent_otel_span = _get_parent_otel_span_from_kwargs(kwargs) ## TPM await self.cache.async_increment_cache( key=tpm_key, @@ -3334,6 +3342,17 @@ class Router: ttl=RoutingArgs.ttl.value, ) + ## RPM + rpm_key = RouterCacheEnum.RPM.value.format( + id=id, current_minute=current_minute, model=deployment_name + ) + await self.cache.async_increment_cache( + key=rpm_key, + value=1, + parent_otel_span=parent_otel_span, + ttl=RoutingArgs.ttl.value, + ) + increment_deployment_successes_for_current_minute( litellm_router_instance=self, deployment_id=id, @@ -3446,6 +3465,40 @@ class Router: except Exception as e: raise e + async def async_deployment_callback_on_failure( + self, kwargs, completion_response: Optional[Any], start_time, end_time + ): + """ + Update RPM usage for a deployment + """ + deployment_name = kwargs["litellm_params"]["metadata"].get( + "deployment", None + ) # handles wildcard routes - by giving the original name sent to `litellm.completion` + model_group = kwargs["litellm_params"]["metadata"].get("model_group", None) + model_info = kwargs["litellm_params"].get("model_info", {}) or {} + id = model_info.get("id", None) + if model_group is None or id is None: + return + elif isinstance(id, int): + id = str(id) + parent_otel_span = _get_parent_otel_span_from_kwargs(kwargs) + + dt = get_utc_datetime() + current_minute = dt.strftime( + "%H-%M" + ) # use the same timezone regardless of system clock + + ## RPM + rpm_key = RouterCacheEnum.RPM.value.format( + id=id, current_minute=current_minute, model=deployment_name + ) + await self.cache.async_increment_cache( + key=rpm_key, + value=1, + parent_otel_span=parent_otel_span, + ttl=RoutingArgs.ttl.value, + ) + def log_retry(self, kwargs: dict, e: Exception) -> dict: """ When a retry or fallback happens, log the details of the just failed model call - similar to Sentry breadcrumbing @@ -4123,7 +4176,24 @@ class Router: raise Exception("Model Name invalid - {}".format(type(model))) return None - def get_router_model_info(self, deployment: dict) -> ModelMapInfo: + @overload + def get_router_model_info( + self, deployment: dict, received_model_name: str, id: None = None + ) -> ModelMapInfo: + pass + + @overload + def get_router_model_info( + self, deployment: None, received_model_name: str, id: str + ) -> ModelMapInfo: + pass + + def get_router_model_info( + self, + deployment: Optional[dict], + received_model_name: str, + id: Optional[str] = None, + ) -> ModelMapInfo: """ For a given model id, return the model info (max tokens, input cost, output cost, etc.). @@ -4137,6 +4207,14 @@ class Router: Raises: - ValueError -> If model is not mapped yet """ + if id is not None: + _deployment = self.get_deployment(model_id=id) + if _deployment is not None: + deployment = _deployment.model_dump(exclude_none=True) + + if deployment is None: + raise ValueError("Deployment not found") + ## GET BASE MODEL base_model = deployment.get("model_info", {}).get("base_model", None) if base_model is None: @@ -4158,10 +4236,27 @@ class Router: elif custom_llm_provider != "azure": model = _model + potential_models = self.pattern_router.route(received_model_name) + if "*" in model and potential_models is not None: # if wildcard route + for potential_model in potential_models: + try: + if potential_model.get("model_info", {}).get( + "id" + ) == deployment.get("model_info", {}).get("id"): + model = potential_model.get("litellm_params", {}).get( + "model" + ) + break + except Exception: + pass + ## GET LITELLM MODEL INFO - raises exception, if model is not mapped - model_info = litellm.get_model_info( - model="{}/{}".format(custom_llm_provider, model) - ) + if not model.startswith(custom_llm_provider): + model_info_name = "{}/{}".format(custom_llm_provider, model) + else: + model_info_name = model + + model_info = litellm.get_model_info(model=model_info_name) ## CHECK USER SET MODEL INFO user_model_info = deployment.get("model_info", {}) @@ -4211,8 +4306,10 @@ class Router: total_tpm: Optional[int] = None total_rpm: Optional[int] = None configurable_clientside_auth_params: CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS = None - - for model in self.model_list: + model_list = self.get_model_list(model_name=model_group) + if model_list is None: + return None + for model in model_list: is_match = False if ( "model_name" in model and model["model_name"] == model_group @@ -4227,7 +4324,7 @@ class Router: if not is_match: continue # model in model group found # - litellm_params = LiteLLM_Params(**model["litellm_params"]) + litellm_params = LiteLLM_Params(**model["litellm_params"]) # type: ignore # get configurable clientside auth params configurable_clientside_auth_params = ( litellm_params.configurable_clientside_auth_params @@ -4235,38 +4332,30 @@ class Router: # get model tpm _deployment_tpm: Optional[int] = None if _deployment_tpm is None: - _deployment_tpm = model.get("tpm", None) + _deployment_tpm = model.get("tpm", None) # type: ignore if _deployment_tpm is None: - _deployment_tpm = model.get("litellm_params", {}).get("tpm", None) + _deployment_tpm = model.get("litellm_params", {}).get("tpm", None) # type: ignore if _deployment_tpm is None: - _deployment_tpm = model.get("model_info", {}).get("tpm", None) + _deployment_tpm = model.get("model_info", {}).get("tpm", None) # type: ignore - if _deployment_tpm is not None: - if total_tpm is None: - total_tpm = 0 - total_tpm += _deployment_tpm # type: ignore # get model rpm _deployment_rpm: Optional[int] = None if _deployment_rpm is None: - _deployment_rpm = model.get("rpm", None) + _deployment_rpm = model.get("rpm", None) # type: ignore if _deployment_rpm is None: - _deployment_rpm = model.get("litellm_params", {}).get("rpm", None) + _deployment_rpm = model.get("litellm_params", {}).get("rpm", None) # type: ignore if _deployment_rpm is None: - _deployment_rpm = model.get("model_info", {}).get("rpm", None) + _deployment_rpm = model.get("model_info", {}).get("rpm", None) # type: ignore - if _deployment_rpm is not None: - if total_rpm is None: - total_rpm = 0 - total_rpm += _deployment_rpm # type: ignore # get model info try: model_info = litellm.get_model_info(model=litellm_params.model) except Exception: model_info = None # get llm provider - model, llm_provider = "", "" + litellm_model, llm_provider = "", "" try: - model, llm_provider, _, _ = litellm.get_llm_provider( + litellm_model, llm_provider, _, _ = litellm.get_llm_provider( model=litellm_params.model, custom_llm_provider=litellm_params.custom_llm_provider, ) @@ -4277,7 +4366,7 @@ class Router: if model_info is None: supported_openai_params = litellm.get_supported_openai_params( - model=model, custom_llm_provider=llm_provider + model=litellm_model, custom_llm_provider=llm_provider ) if supported_openai_params is None: supported_openai_params = [] @@ -4367,7 +4456,20 @@ class Router: model_group_info.supported_openai_params = model_info[ "supported_openai_params" ] + if model_info.get("tpm", None) is not None and _deployment_tpm is None: + _deployment_tpm = model_info.get("tpm") + if model_info.get("rpm", None) is not None and _deployment_rpm is None: + _deployment_rpm = model_info.get("rpm") + if _deployment_tpm is not None: + if total_tpm is None: + total_tpm = 0 + total_tpm += _deployment_tpm # type: ignore + + if _deployment_rpm is not None: + if total_rpm is None: + total_rpm = 0 + total_rpm += _deployment_rpm # type: ignore if model_group_info is not None: ## UPDATE WITH TOTAL TPM/RPM FOR MODEL GROUP if total_tpm is not None: @@ -4419,7 +4521,10 @@ class Router: self, model_group: str ) -> Tuple[Optional[int], Optional[int]]: """ - Returns remaining tpm/rpm quota for model group + Returns current tpm/rpm usage for model group + + Parameters: + - model_group: str - the received model name from the user (can be a wildcard route). Returns: - usage: Tuple[tpm, rpm] @@ -4430,20 +4535,37 @@ class Router: ) # use the same timezone regardless of system clock tpm_keys: List[str] = [] rpm_keys: List[str] = [] - for model in self.model_list: - if "model_name" in model and model["model_name"] == model_group: - tpm_keys.append( - f"global_router:{model['model_info']['id']}:tpm:{current_minute}" + + model_list = self.get_model_list(model_name=model_group) + if model_list is None: # no matching deployments + return None, None + + for model in model_list: + id: Optional[str] = model.get("model_info", {}).get("id") # type: ignore + litellm_model: Optional[str] = model["litellm_params"].get( + "model" + ) # USE THE MODEL SENT TO litellm.completion() - consistent with how global_router cache is written. + if id is None or litellm_model is None: + continue + tpm_keys.append( + RouterCacheEnum.TPM.value.format( + id=id, + model=litellm_model, + current_minute=current_minute, ) - rpm_keys.append( - f"global_router:{model['model_info']['id']}:rpm:{current_minute}" + ) + rpm_keys.append( + RouterCacheEnum.RPM.value.format( + id=id, + model=litellm_model, + current_minute=current_minute, ) + ) combined_tpm_rpm_keys = tpm_keys + rpm_keys combined_tpm_rpm_values = await self.cache.async_batch_get_cache( keys=combined_tpm_rpm_keys ) - if combined_tpm_rpm_values is None: return None, None @@ -4468,6 +4590,32 @@ class Router: rpm_usage += t return tpm_usage, rpm_usage + async def get_remaining_model_group_usage(self, model_group: str) -> Dict[str, int]: + + current_tpm, current_rpm = await self.get_model_group_usage(model_group) + + model_group_info = self.get_model_group_info(model_group) + + if model_group_info is not None and model_group_info.tpm is not None: + tpm_limit = model_group_info.tpm + else: + tpm_limit = None + + if model_group_info is not None and model_group_info.rpm is not None: + rpm_limit = model_group_info.rpm + else: + rpm_limit = None + + returned_dict = {} + if tpm_limit is not None and current_tpm is not None: + returned_dict["x-ratelimit-remaining-tokens"] = tpm_limit - current_tpm + returned_dict["x-ratelimit-limit-tokens"] = tpm_limit + if rpm_limit is not None and current_rpm is not None: + returned_dict["x-ratelimit-remaining-requests"] = rpm_limit - current_rpm + returned_dict["x-ratelimit-limit-requests"] = rpm_limit + + return returned_dict + async def set_response_headers( self, response: Any, model_group: Optional[str] = None ) -> Any: @@ -4478,6 +4626,30 @@ class Router: # - if healthy_deployments > 1, return model group rate limit headers # - else return the model's rate limit headers """ + if ( + isinstance(response, BaseModel) + and hasattr(response, "_hidden_params") + and isinstance(response._hidden_params, dict) # type: ignore + ): + response._hidden_params.setdefault("additional_headers", {}) # type: ignore + response._hidden_params["additional_headers"][ # type: ignore + "x-litellm-model-group" + ] = model_group + + additional_headers = response._hidden_params["additional_headers"] # type: ignore + + if ( + "x-ratelimit-remaining-tokens" not in additional_headers + and "x-ratelimit-remaining-requests" not in additional_headers + and model_group is not None + ): + remaining_usage = await self.get_remaining_model_group_usage( + model_group + ) + + for header, value in remaining_usage.items(): + if value is not None: + additional_headers[header] = value return response def get_model_ids(self, model_name: Optional[str] = None) -> List[str]: @@ -4540,6 +4712,9 @@ class Router: if hasattr(self, "model_list"): returned_models: List[DeploymentTypedDict] = [] + if model_name is not None: + returned_models.extend(self._get_all_deployments(model_name=model_name)) + if hasattr(self, "model_group_alias"): for model_alias, model_value in self.model_group_alias.items(): @@ -4560,21 +4735,32 @@ class Router: ) ) + if len(returned_models) == 0: # check if wildcard route + potential_wildcard_models = self.pattern_router.route(model_name) + if potential_wildcard_models is not None: + returned_models.extend( + [DeploymentTypedDict(**m) for m in potential_wildcard_models] # type: ignore + ) + if model_name is None: returned_models += self.model_list return returned_models - returned_models.extend(self._get_all_deployments(model_name=model_name)) + return returned_models return None - def get_model_access_groups(self): + def get_model_access_groups(self, model_name: Optional[str] = None): + """ + If model_name is provided, only return access groups for that model. + """ from collections import defaultdict access_groups = defaultdict(list) - if self.model_list: - for m in self.model_list: + model_list = self.get_model_list(model_name=model_name) + if model_list: + for m in model_list: for group in m.get("model_info", {}).get("access_groups", []): model_name = m["model_name"] access_groups[group].append(model_name) @@ -4810,10 +4996,12 @@ class Router: base_model = deployment.get("litellm_params", {}).get( "base_model", None ) + model_info = self.get_router_model_info( + deployment=deployment, received_model_name=model + ) model = base_model or deployment.get("litellm_params", {}).get( "model", None ) - model_info = self.get_router_model_info(deployment=deployment) if ( isinstance(model_info, dict) diff --git a/litellm/router_strategy/provider_budgets.py b/litellm/router_strategy/provider_budgets.py index 23d8b6c39..f4dc1ba94 100644 --- a/litellm/router_strategy/provider_budgets.py +++ b/litellm/router_strategy/provider_budgets.py @@ -18,13 +18,17 @@ anthropic: ``` """ +import asyncio +from datetime import datetime, timezone from typing import TYPE_CHECKING, Any, Dict, List, Optional, TypedDict, Union import litellm from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache +from litellm.caching.redis_cache import RedisPipelineIncrementOperation from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.core_helpers import _get_parent_otel_span_from_kwargs +from litellm.litellm_core_utils.duration_parser import duration_in_seconds from litellm.router_utils.cooldown_callbacks import ( _get_prometheus_logger_from_callbacks, ) @@ -43,10 +47,14 @@ if TYPE_CHECKING: else: Span = Any +DEFAULT_REDIS_SYNC_INTERVAL = 1 + class ProviderBudgetLimiting(CustomLogger): def __init__(self, router_cache: DualCache, provider_budget_config: dict): self.router_cache = router_cache + self.redis_increment_operation_queue: List[RedisPipelineIncrementOperation] = [] + asyncio.create_task(self.periodic_sync_in_memory_spend_with_redis()) # cast elements of provider_budget_config to ProviderBudgetInfo for provider, config in provider_budget_config.items(): @@ -172,19 +180,76 @@ class ProviderBudgetLimiting(CustomLogger): return potential_deployments + async def _get_or_set_budget_start_time( + self, start_time_key: str, current_time: float, ttl_seconds: int + ) -> float: + """ + Checks if the key = `provider_budget_start_time:{provider}` exists in cache. + + If it does, return the value. + If it does not, set the key to `current_time` and return the value. + """ + budget_start = await self.router_cache.async_get_cache(start_time_key) + if budget_start is None: + await self.router_cache.async_set_cache( + key=start_time_key, value=current_time, ttl=ttl_seconds + ) + return current_time + return float(budget_start) + + async def _handle_new_budget_window( + self, + spend_key: str, + start_time_key: str, + current_time: float, + response_cost: float, + ttl_seconds: int, + ) -> float: + """ + Handle start of new budget window by resetting spend and start time + + Enters this when: + - The budget does not exist in cache, so we need to set it + - The budget window has expired, so we need to reset everything + + Does 2 things: + - stores key: `provider_spend:{provider}:1d`, value: response_cost + - stores key: `provider_budget_start_time:{provider}`, value: current_time. + This stores the start time of the new budget window + """ + await self.router_cache.async_set_cache( + key=spend_key, value=response_cost, ttl=ttl_seconds + ) + await self.router_cache.async_set_cache( + key=start_time_key, value=current_time, ttl=ttl_seconds + ) + return current_time + + async def _increment_spend_in_current_window( + self, spend_key: str, response_cost: float, ttl: int + ): + """ + Increment spend within existing budget window + + Runs once the budget start time exists in Redis Cache (on the 2nd and subsequent requests to the same provider) + + - Increments the spend in memory cache (so spend instantly updated in memory) + - Queues the increment operation to Redis Pipeline (using batched pipeline to optimize performance. Using Redis for multi instance environment of LiteLLM) + """ + await self.router_cache.in_memory_cache.async_increment( + key=spend_key, + value=response_cost, + ttl=ttl, + ) + increment_op = RedisPipelineIncrementOperation( + key=spend_key, + increment_value=response_cost, + ttl=ttl, + ) + self.redis_increment_operation_queue.append(increment_op) + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): - """ - Increment provider spend in DualCache (InMemory + Redis) - - Handles saving current provider spend to Redis. - - Spend is stored as: - provider_spend:{provider}:{time_period} - ex. provider_spend:openai:1d - ex. provider_spend:anthropic:7d - - The time period is tracked for time_periods set in the provider budget config. - """ + """Original method now uses helper functions""" verbose_router_logger.debug("in ProviderBudgetLimiting.async_log_success_event") standard_logging_payload: Optional[StandardLoggingPayload] = kwargs.get( "standard_logging_object", None @@ -207,20 +272,146 @@ class ProviderBudgetLimiting(CustomLogger): ) spend_key = f"provider_spend:{custom_llm_provider}:{budget_config.time_period}" - ttl_seconds = self.get_ttl_seconds(budget_config.time_period) + start_time_key = f"provider_budget_start_time:{custom_llm_provider}" + + current_time = datetime.now(timezone.utc).timestamp() + ttl_seconds = duration_in_seconds(budget_config.time_period) + + budget_start = await self._get_or_set_budget_start_time( + start_time_key=start_time_key, + current_time=current_time, + ttl_seconds=ttl_seconds, + ) + + if budget_start is None: + # First spend for this provider + budget_start = await self._handle_new_budget_window( + spend_key=spend_key, + start_time_key=start_time_key, + current_time=current_time, + response_cost=response_cost, + ttl_seconds=ttl_seconds, + ) + elif (current_time - budget_start) > ttl_seconds: + # Budget window expired - reset everything + verbose_router_logger.debug("Budget window expired - resetting everything") + budget_start = await self._handle_new_budget_window( + spend_key=spend_key, + start_time_key=start_time_key, + current_time=current_time, + response_cost=response_cost, + ttl_seconds=ttl_seconds, + ) + else: + # Within existing window - increment spend + remaining_time = ttl_seconds - (current_time - budget_start) + ttl_for_increment = int(remaining_time) + + await self._increment_spend_in_current_window( + spend_key=spend_key, response_cost=response_cost, ttl=ttl_for_increment + ) + verbose_router_logger.debug( - f"Incrementing spend for {spend_key} by {response_cost}, ttl: {ttl_seconds}" - ) - # Increment the spend in Redis and set TTL - await self.router_cache.async_increment_cache( - key=spend_key, - value=response_cost, - ttl=ttl_seconds, - ) - verbose_router_logger.debug( - f"Incremented spend for {spend_key} by {response_cost}, ttl: {ttl_seconds}" + f"Incremented spend for {spend_key} by {response_cost}" ) + async def periodic_sync_in_memory_spend_with_redis(self): + """ + Handler that triggers sync_in_memory_spend_with_redis every DEFAULT_REDIS_SYNC_INTERVAL seconds + + Required for multi-instance environment usage of provider budgets + """ + while True: + try: + await self._sync_in_memory_spend_with_redis() + await asyncio.sleep( + DEFAULT_REDIS_SYNC_INTERVAL + ) # Wait for DEFAULT_REDIS_SYNC_INTERVAL seconds before next sync + except Exception as e: + verbose_router_logger.error(f"Error in periodic sync task: {str(e)}") + await asyncio.sleep( + DEFAULT_REDIS_SYNC_INTERVAL + ) # Still wait DEFAULT_REDIS_SYNC_INTERVAL seconds on error before retrying + + async def _push_in_memory_increments_to_redis(self): + """ + How this works: + - async_log_success_event collects all provider spend increments in `redis_increment_operation_queue` + - This function pushes all increments to Redis in a batched pipeline to optimize performance + + Only runs if Redis is initialized + """ + try: + if not self.router_cache.redis_cache: + return # Redis is not initialized + + verbose_router_logger.debug( + "Pushing Redis Increment Pipeline for queue: %s", + self.redis_increment_operation_queue, + ) + if len(self.redis_increment_operation_queue) > 0: + asyncio.create_task( + self.router_cache.redis_cache.async_increment_pipeline( + increment_list=self.redis_increment_operation_queue, + ) + ) + + self.redis_increment_operation_queue = [] + + except Exception as e: + verbose_router_logger.error( + f"Error syncing in-memory cache with Redis: {str(e)}" + ) + + async def _sync_in_memory_spend_with_redis(self): + """ + Ensures in-memory cache is updated with latest Redis values for all provider spends. + + Why Do we need this? + - Optimization to hit sub 100ms latency. Performance was impacted when redis was used for read/write per request + - Use provider budgets in multi-instance environment, we use Redis to sync spend across all instances + + What this does: + 1. Push all provider spend increments to Redis + 2. Fetch all current provider spend from Redis to update in-memory cache + """ + + try: + # No need to sync if Redis cache is not initialized + if self.router_cache.redis_cache is None: + return + + # 1. Push all provider spend increments to Redis + await self._push_in_memory_increments_to_redis() + + # 2. Fetch all current provider spend from Redis to update in-memory cache + cache_keys = [] + for provider, config in self.provider_budget_config.items(): + if config is None: + continue + cache_keys.append(f"provider_spend:{provider}:{config.time_period}") + + # Batch fetch current spend values from Redis + redis_values = await self.router_cache.redis_cache.async_batch_get_cache( + key_list=cache_keys + ) + + # Update in-memory cache with Redis values + if isinstance(redis_values, dict): # Check if redis_values is a dictionary + for key, value in redis_values.items(): + if value is not None: + await self.router_cache.in_memory_cache.async_set_cache( + key=key, value=float(value) + ) + verbose_router_logger.debug( + f"Updated in-memory cache for {key}: {value}" + ) + + except Exception as e: + verbose_router_logger.error( + f"Error syncing in-memory cache with Redis: {str(e)}" + ) + def _get_budget_config_for_provider( self, provider: str ) -> Optional[ProviderBudgetInfo]: @@ -242,15 +433,6 @@ class ProviderBudgetLimiting(CustomLogger): return None return custom_llm_provider - def get_ttl_seconds(self, time_period: str) -> int: - """ - Convert time period (e.g., '1d', '30d') to seconds for Redis TTL - """ - if time_period.endswith("d"): - days = int(time_period[:-1]) - return days * 24 * 60 * 60 - raise ValueError(f"Unsupported time period format: {time_period}") - def _track_provider_remaining_budget_prometheus( self, provider: str, spend: float, budget_limit: float ): diff --git a/litellm/router_utils/pattern_match_deployments.py b/litellm/router_utils/pattern_match_deployments.py index 3896c3a95..a369100eb 100644 --- a/litellm/router_utils/pattern_match_deployments.py +++ b/litellm/router_utils/pattern_match_deployments.py @@ -79,7 +79,9 @@ class PatternMatchRouter: return new_deployments - def route(self, request: Optional[str]) -> Optional[List[Dict]]: + def route( + self, request: Optional[str], filtered_model_names: Optional[List[str]] = None + ) -> Optional[List[Dict]]: """ Route a requested model to the corresponding llm deployments based on the regex pattern @@ -89,14 +91,26 @@ class PatternMatchRouter: Args: request: Optional[str] - + filtered_model_names: Optional[List[str]] - if provided, only return deployments that match the filtered_model_names Returns: Optional[List[Deployment]]: llm deployments """ try: if request is None: return None + + regex_filtered_model_names = ( + [self._pattern_to_regex(m) for m in filtered_model_names] + if filtered_model_names is not None + else [] + ) + for pattern, llm_deployments in self.patterns.items(): + if ( + filtered_model_names is not None + and pattern not in regex_filtered_model_names + ): + continue pattern_match = re.match(pattern, request) if pattern_match: return self._return_pattern_matched_deployments( diff --git a/litellm/router_utils/response_headers.py b/litellm/router_utils/response_headers.py new file mode 100644 index 000000000..e69de29bb diff --git a/litellm/secret_managers/aws_secret_manager_v2.py b/litellm/secret_managers/aws_secret_manager_v2.py index 69add6f23..32653f57d 100644 --- a/litellm/secret_managers/aws_secret_manager_v2.py +++ b/litellm/secret_managers/aws_secret_manager_v2.py @@ -31,8 +31,8 @@ from litellm.llms.custom_httpx.http_handler import ( _get_httpx_client, get_async_httpx_client, ) -from litellm.llms.custom_httpx.types import httpxSpecialProvider from litellm.proxy._types import KeyManagementSystem +from litellm.types.llms.custom_http import httpxSpecialProvider class AWSSecretsManagerV2(BaseAWSLLM): diff --git a/litellm/tests/test_mlflow.py b/litellm/tests/test_mlflow.py deleted file mode 100644 index ec23875ea..000000000 --- a/litellm/tests/test_mlflow.py +++ /dev/null @@ -1,29 +0,0 @@ -import pytest - -import litellm - - -def test_mlflow_logging(): - litellm.success_callback = ["mlflow"] - litellm.failure_callback = ["mlflow"] - - litellm.completion( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "what llm are u"}], - max_tokens=10, - temperature=0.2, - user="test-user", - ) - -@pytest.mark.asyncio() -async def test_async_mlflow_logging(): - litellm.success_callback = ["mlflow"] - litellm.failure_callback = ["mlflow"] - - await litellm.acompletion( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "hi test from local arize"}], - mock_response="hello", - temperature=0.1, - user="OTEL_USER", - ) diff --git a/litellm/types/caching.py b/litellm/types/caching.py index 7fca4c041..a6f9de308 100644 --- a/litellm/types/caching.py +++ b/litellm/types/caching.py @@ -1,5 +1,5 @@ from enum import Enum -from typing import Literal +from typing import Literal, Optional, TypedDict class LiteLLMCacheType(str, Enum): @@ -23,3 +23,13 @@ CachingSupportedCallTypes = Literal[ "arerank", "rerank", ] + + +class RedisPipelineIncrementOperation(TypedDict): + """ + TypeDict for 1 Redis Pipeline Increment Operation + """ + + key: str + increment_value: float + ttl: Optional[int] diff --git a/litellm/integrations/datadog/types.py b/litellm/types/integrations/datadog.py similarity index 68% rename from litellm/integrations/datadog/types.py rename to litellm/types/integrations/datadog.py index 87aa3ce17..79d4eded4 100644 --- a/litellm/integrations/datadog/types.py +++ b/litellm/types/integrations/datadog.py @@ -1,5 +1,5 @@ from enum import Enum -from typing import TypedDict +from typing import Optional, TypedDict class DataDogStatus(str, Enum): @@ -19,3 +19,11 @@ class DatadogPayload(TypedDict, total=False): class DD_ERRORS(Enum): DATADOG_413_ERROR = "Datadog API Error - Payload too large (batch is above 5MB uncompressed). If you want this logged either disable request/response logging or set `DD_BATCH_SIZE=50`" + + +class DatadogProxyFailureHookJsonMessage(TypedDict, total=False): + exception: str + error_class: str + status_code: Optional[int] + traceback: str + user_api_key_dict: dict diff --git a/litellm/types/llms/custom_http.py b/litellm/types/llms/custom_http.py new file mode 100644 index 000000000..f43daff2a --- /dev/null +++ b/litellm/types/llms/custom_http.py @@ -0,0 +1,20 @@ +from enum import Enum + +import litellm + + +class httpxSpecialProvider(str, Enum): + """ + Httpx Clients can be created for these litellm internal providers + + Example: + - langsmith logging would need a custom async httpx client + - pass through endpoint would need a custom async httpx client + """ + + LoggingCallback = "logging_callback" + GuardrailCallback = "guardrail_callback" + Caching = "caching" + Oauth2Check = "oauth2_check" + SecretManager = "secret_manager" + PassThroughEndpoint = "pass_through_endpoint" diff --git a/litellm/types/passthrough_endpoints/vertex_ai.py b/litellm/types/passthrough_endpoints/vertex_ai.py new file mode 100644 index 000000000..3933aadcd --- /dev/null +++ b/litellm/types/passthrough_endpoints/vertex_ai.py @@ -0,0 +1,18 @@ +""" +Used for /vertex_ai/ pass through endpoints +""" + +from typing import Optional + +from pydantic import BaseModel + + +class VertexPassThroughCredentials(BaseModel): + # Example: vertex_project = "my-project-123" + vertex_project: Optional[str] = None + + # Example: vertex_location = "us-central1" + vertex_location: Optional[str] = None + + # Example: vertex_credentials = "/path/to/credentials.json" or "os.environ/GOOGLE_CREDS" + vertex_credentials: Optional[str] = None diff --git a/litellm/types/router.py b/litellm/types/router.py index f91155a22..99d981e4d 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -9,7 +9,7 @@ from typing import Any, Dict, List, Literal, Optional, Tuple, Union import httpx from pydantic import BaseModel, ConfigDict, Field -from typing_extensions import TypedDict +from typing_extensions import Required, TypedDict from ..exceptions import RateLimitError from .completion import CompletionRequest @@ -352,9 +352,10 @@ class LiteLLMParamsTypedDict(TypedDict, total=False): tags: Optional[List[str]] -class DeploymentTypedDict(TypedDict): - model_name: str - litellm_params: LiteLLMParamsTypedDict +class DeploymentTypedDict(TypedDict, total=False): + model_name: Required[str] + litellm_params: Required[LiteLLMParamsTypedDict] + model_info: dict SPECIAL_MODEL_INFO_PARAMS = [ @@ -640,3 +641,8 @@ class ProviderBudgetInfo(BaseModel): ProviderBudgetConfigType = Dict[str, ProviderBudgetInfo] + + +class RouterCacheEnum(enum.Enum): + TPM = "global_router:{id}:{model}:tpm:{current_minute}" + RPM = "global_router:{id}:{model}:rpm:{current_minute}" diff --git a/litellm/types/utils.py b/litellm/types/utils.py index d02129681..93b4a39d3 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -106,6 +106,8 @@ class ModelInfo(TypedDict, total=False): supports_prompt_caching: Optional[bool] supports_audio_input: Optional[bool] supports_audio_output: Optional[bool] + tpm: Optional[int] + rpm: Optional[int] class GenericStreamingChunk(TypedDict, total=False): @@ -1602,3 +1604,22 @@ class StandardCallbackDynamicParams(TypedDict, total=False): langsmith_api_key: Optional[str] langsmith_project: Optional[str] langsmith_base_url: Optional[str] + + +class KeyGenerationConfig(TypedDict, total=False): + required_params: List[ + str + ] # specify params that must be present in the key generation request + + +class TeamUIKeyGenerationConfig(KeyGenerationConfig): + allowed_team_member_roles: List[str] + + +class PersonalUIKeyGenerationConfig(KeyGenerationConfig): + allowed_user_roles: List[str] + + +class StandardKeyGenerationConfig(TypedDict, total=False): + team_key_generation: TeamUIKeyGenerationConfig + personal_key_generation: PersonalUIKeyGenerationConfig diff --git a/litellm/utils.py b/litellm/utils.py index 003971142..b925fbf5b 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -4656,6 +4656,8 @@ def get_model_info( # noqa: PLR0915 ), supports_audio_input=_model_info.get("supports_audio_input", False), supports_audio_output=_model_info.get("supports_audio_output", False), + tpm=_model_info.get("tpm", None), + rpm=_model_info.get("rpm", None), ) except Exception as e: if "OllamaError" in str(e): @@ -6170,3 +6172,13 @@ class ProviderConfigManager: return litellm.GroqChatConfig() return OpenAIGPTConfig() + + +def get_end_user_id_for_cost_tracking(litellm_params: dict) -> Optional[str]: + """ + Used for enforcing `disable_end_user_cost_tracking` param. + """ + proxy_server_request = litellm_params.get("proxy_server_request") or {} + if litellm.disable_end_user_cost_tracking: + return None + return proxy_server_request.get("body", {}).get("user", None) diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index a56472f7f..ac22871bc 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -2032,7 +2032,6 @@ "tool_use_system_prompt_tokens": 264, "supports_assistant_prefill": true, "supports_prompt_caching": true, - "supports_pdf_input": true, "supports_response_schema": true }, "claude-3-opus-20240229": { @@ -2098,6 +2097,7 @@ "supports_vision": true, "tool_use_system_prompt_tokens": 159, "supports_assistant_prefill": true, + "supports_pdf_input": true, "supports_prompt_caching": true, "supports_response_schema": true }, @@ -3383,6 +3383,8 @@ "supports_vision": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-001": { @@ -3406,6 +3408,8 @@ "supports_vision": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash": { @@ -3428,6 +3432,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-latest": { @@ -3450,6 +3456,32 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 2000, + "source": "https://ai.google.dev/pricing" + }, + "gemini/gemini-1.5-flash-8b": { + "max_tokens": 8192, + "max_input_tokens": 1048576, + "max_output_tokens": 8192, + "max_images_per_prompt": 3000, + "max_videos_per_prompt": 10, + "max_video_length": 1, + "max_audio_length_hours": 8.4, + "max_audio_per_prompt": 1, + "max_pdf_size_mb": 30, + "input_cost_per_token": 0, + "input_cost_per_token_above_128k_tokens": 0, + "output_cost_per_token": 0, + "output_cost_per_token_above_128k_tokens": 0, + "litellm_provider": "gemini", + "mode": "chat", + "supports_system_messages": true, + "supports_function_calling": true, + "supports_vision": true, + "supports_response_schema": true, + "tpm": 4000000, + "rpm": 4000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-8b-exp-0924": { @@ -3472,6 +3504,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 4000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-exp-1114": { @@ -3494,7 +3528,12 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, - "source": "https://ai.google.dev/pricing" + "tpm": 4000000, + "rpm": 1000, + "source": "https://ai.google.dev/pricing", + "metadata": { + "notes": "Rate limits not documented for gemini-exp-1114. Assuming same as gemini-1.5-pro." + } }, "gemini/gemini-1.5-flash-exp-0827": { "max_tokens": 8192, @@ -3516,6 +3555,8 @@ "supports_function_calling": true, "supports_vision": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 2000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-flash-8b-exp-0827": { @@ -3537,6 +3578,9 @@ "supports_system_messages": true, "supports_function_calling": true, "supports_vision": true, + "supports_response_schema": true, + "tpm": 4000000, + "rpm": 4000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-pro": { @@ -3550,7 +3594,10 @@ "litellm_provider": "gemini", "mode": "chat", "supports_function_calling": true, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" + "rpd": 30000, + "tpm": 120000, + "rpm": 360, + "source": "https://ai.google.dev/gemini-api/docs/models/gemini" }, "gemini/gemini-1.5-pro": { "max_tokens": 8192, @@ -3567,6 +3614,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-002": { @@ -3585,6 +3634,8 @@ "supports_tool_choice": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-001": { @@ -3603,6 +3654,8 @@ "supports_tool_choice": true, "supports_response_schema": true, "supports_prompt_caching": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-exp-0801": { @@ -3620,6 +3673,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-exp-0827": { @@ -3637,6 +3692,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-1.5-pro-latest": { @@ -3654,6 +3711,8 @@ "supports_vision": true, "supports_tool_choice": true, "supports_response_schema": true, + "tpm": 4000000, + "rpm": 1000, "source": "https://ai.google.dev/pricing" }, "gemini/gemini-pro-vision": { @@ -3668,6 +3727,9 @@ "mode": "chat", "supports_function_calling": true, "supports_vision": true, + "rpd": 30000, + "tpm": 120000, + "rpm": 360, "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models" }, "gemini/gemini-gemma-2-27b-it": { diff --git a/pyproject.toml b/pyproject.toml index d5cf3fb92..156e9ed4e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm" -version = "1.52.13" +version = "1.53.2" description = "Library to easily interface with LLM API providers" authors = ["BerriAI"] license = "MIT" @@ -91,7 +91,7 @@ requires = ["poetry-core", "wheel"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "1.52.13" +version = "1.53.2" version_files = [ "pyproject.toml:^version" ] diff --git a/requirements.txt b/requirements.txt index 0ac95fc96..b22edea09 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,6 @@ # LITELLM PROXY DEPENDENCIES # anyio==4.4.0 # openai + http req. -openai==1.54.0 # openai req. +openai==1.55.3 # openai req. fastapi==0.111.0 # server dep backoff==2.2.1 # server dep pyyaml==6.0.0 # server dep diff --git a/tests/code_coverage_tests/ensure_async_clients_test.py b/tests/code_coverage_tests/ensure_async_clients_test.py new file mode 100644 index 000000000..0565de9b3 --- /dev/null +++ b/tests/code_coverage_tests/ensure_async_clients_test.py @@ -0,0 +1,111 @@ +import ast +import os + +ALLOWED_FILES = [ + # local files + "../../litellm/__init__.py", + "../../litellm/llms/custom_httpx/http_handler.py", + "../../litellm/router_utils/client_initalization_utils.py", + "../../litellm/llms/custom_httpx/http_handler.py", + "../../litellm/llms/huggingface_restapi.py", + "../../litellm/llms/base.py", + "../../litellm/llms/custom_httpx/httpx_handler.py", + # when running on ci/cd + "./litellm/__init__.py", + "./litellm/llms/custom_httpx/http_handler.py", + "./litellm/router_utils/client_initalization_utils.py", + "./litellm/llms/custom_httpx/http_handler.py", + "./litellm/llms/huggingface_restapi.py", + "./litellm/llms/base.py", + "./litellm/llms/custom_httpx/httpx_handler.py", +] + +warning_msg = "this is a serious violation that can impact latency. Creating Async clients per request can add +500ms per request" + + +def check_for_async_http_handler(file_path): + """ + Checks if AsyncHttpHandler is instantiated in the given file. + Returns a list of line numbers where AsyncHttpHandler is used. + """ + print("..checking file=", file_path) + if file_path in ALLOWED_FILES: + return [] + with open(file_path, "r") as file: + try: + tree = ast.parse(file.read()) + except SyntaxError: + print(f"Warning: Syntax error in file {file_path}") + return [] + + violations = [] + target_names = [ + "AsyncHttpHandler", + "AsyncHTTPHandler", + "AsyncClient", + "httpx.AsyncClient", + ] # Add variations here + for node in ast.walk(tree): + if isinstance(node, ast.Call): + if isinstance(node.func, ast.Name) and node.func.id.lower() in [ + name.lower() for name in target_names + ]: + raise ValueError( + f"found violation in file {file_path} line: {node.lineno}. Please use `get_async_httpx_client` instead. {warning_msg}" + ) + # Check for attribute calls like httpx.AsyncClient() + elif isinstance(node.func, ast.Attribute): + full_name = "" + current = node.func + while isinstance(current, ast.Attribute): + full_name = "." + current.attr + full_name + current = current.value + if isinstance(current, ast.Name): + full_name = current.id + full_name + if full_name.lower() in [name.lower() for name in target_names]: + raise ValueError( + f"found violation in file {file_path} line: {node.lineno}. Please use `get_async_httpx_client` instead. {warning_msg}" + ) + return violations + + +def scan_directory_for_async_handler(base_dir): + """ + Scans all Python files in the directory tree for AsyncHttpHandler usage. + Returns a dict of files and line numbers where violations were found. + """ + violations = {} + + for root, _, files in os.walk(base_dir): + for file in files: + if file.endswith(".py"): + file_path = os.path.join(root, file) + file_violations = check_for_async_http_handler(file_path) + if file_violations: + violations[file_path] = file_violations + + return violations + + +def test_no_async_http_handler_usage(): + """ + Test to ensure AsyncHttpHandler is not used anywhere in the codebase. + """ + base_dir = "./litellm" # Adjust this path as needed + + # base_dir = "../../litellm" # LOCAL TESTING + violations = scan_directory_for_async_handler(base_dir) + + if violations: + violation_messages = [] + for file_path, line_numbers in violations.items(): + violation_messages.append( + f"Found AsyncHttpHandler in {file_path} at lines: {line_numbers}" + ) + raise AssertionError( + "AsyncHttpHandler usage detected:\n" + "\n".join(violation_messages) + ) + + +if __name__ == "__main__": + test_no_async_http_handler_usage() diff --git a/tests/documentation_tests/test_env_keys.py b/tests/documentation_tests/test_env_keys.py index 2c81788ff..6b7c15e2b 100644 --- a/tests/documentation_tests/test_env_keys.py +++ b/tests/documentation_tests/test_env_keys.py @@ -45,16 +45,23 @@ print(env_keys) # Parse the documentation to extract documented keys repo_base = "./" print(os.listdir(repo_base)) -docs_path = "./docs/my-website/docs/proxy/configs.md" # Path to the documentation +docs_path = ( + "./docs/my-website/docs/proxy/config_settings.md" # Path to the documentation +) documented_keys = set() try: with open(docs_path, "r", encoding="utf-8") as docs_file: content = docs_file.read() + print(f"content: {content}") + # Find the section titled "general_settings - Reference" general_settings_section = re.search( - r"### environment variables - Reference(.*?)###", content, re.DOTALL + r"### environment variables - Reference(.*?)(?=\n###|\Z)", + content, + re.DOTALL | re.MULTILINE, ) + print(f"general_settings_section: {general_settings_section}") if general_settings_section: # Extract the table rows, which contain the documented keys table_content = general_settings_section.group(1) @@ -68,6 +75,7 @@ except Exception as e: ) +print(f"documented_keys: {documented_keys}") # Compare and find undocumented keys undocumented_keys = env_keys - documented_keys diff --git a/tests/documentation_tests/test_general_setting_keys.py b/tests/documentation_tests/test_general_setting_keys.py index 296c5c403..c207de675 100644 --- a/tests/documentation_tests/test_general_setting_keys.py +++ b/tests/documentation_tests/test_general_setting_keys.py @@ -34,7 +34,9 @@ for root, dirs, files in os.walk(repo_base): # Parse the documentation to extract documented keys repo_base = "./" print(os.listdir(repo_base)) -docs_path = "./docs/my-website/docs/proxy/configs.md" # Path to the documentation +docs_path = ( + "./docs/my-website/docs/proxy/config_settings.md" # Path to the documentation +) documented_keys = set() try: with open(docs_path, "r", encoding="utf-8") as docs_file: diff --git a/tests/documentation_tests/test_router_settings.py b/tests/documentation_tests/test_router_settings.py new file mode 100644 index 000000000..c66a02d68 --- /dev/null +++ b/tests/documentation_tests/test_router_settings.py @@ -0,0 +1,87 @@ +import os +import re +import inspect +from typing import Type +import sys + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path +import litellm + + +def get_init_params(cls: Type) -> list[str]: + """ + Retrieve all parameters supported by the `__init__` method of a given class. + + Args: + cls: The class to inspect. + + Returns: + A list of parameter names. + """ + if not hasattr(cls, "__init__"): + raise ValueError( + f"The provided class {cls.__name__} does not have an __init__ method." + ) + + init_method = cls.__init__ + argspec = inspect.getfullargspec(init_method) + + # The first argument is usually 'self', so we exclude it + return argspec.args[1:] # Exclude 'self' + + +router_init_params = set(get_init_params(litellm.router.Router)) +print(router_init_params) +router_init_params.remove("model_list") + +# Parse the documentation to extract documented keys +repo_base = "./" +print(os.listdir(repo_base)) +docs_path = ( + "./docs/my-website/docs/proxy/config_settings.md" # Path to the documentation +) +# docs_path = ( +# "../../docs/my-website/docs/proxy/config_settings.md" # Path to the documentation +# ) +documented_keys = set() +try: + with open(docs_path, "r", encoding="utf-8") as docs_file: + content = docs_file.read() + + # Find the section titled "general_settings - Reference" + general_settings_section = re.search( + r"### router_settings - Reference(.*?)###", content, re.DOTALL + ) + if general_settings_section: + # Extract the table rows, which contain the documented keys + table_content = general_settings_section.group(1) + doc_key_pattern = re.compile( + r"\|\s*([^\|]+?)\s*\|" + ) # Capture the key from each row of the table + documented_keys.update(doc_key_pattern.findall(table_content)) +except Exception as e: + raise Exception( + f"Error reading documentation: {e}, \n repo base - {os.listdir(repo_base)}" + ) + + +# Compare and find undocumented keys +undocumented_keys = router_init_params - documented_keys + +# Print results +print("Keys expected in 'router settings' (found in code):") +for key in sorted(router_init_params): + print(key) + +if undocumented_keys: + raise Exception( + f"\nKeys not documented in 'router settings - Reference': {undocumented_keys}" + ) +else: + print( + "\nAll keys are documented in 'router settings - Reference'. - {}".format( + router_init_params + ) + ) diff --git a/tests/image_gen_tests/test_image_generation.py b/tests/image_gen_tests/test_image_generation.py index 692a0e4e9..6605b3e3d 100644 --- a/tests/image_gen_tests/test_image_generation.py +++ b/tests/image_gen_tests/test_image_generation.py @@ -8,6 +8,7 @@ import traceback from dotenv import load_dotenv from openai.types.image import Image +from litellm.caching import InMemoryCache logging.basicConfig(level=logging.DEBUG) load_dotenv() @@ -107,7 +108,7 @@ class TestVertexImageGeneration(BaseImageGenTest): # comment this when running locally load_vertex_ai_credentials() - litellm.in_memory_llm_clients_cache = {} + litellm.in_memory_llm_clients_cache = InMemoryCache() return { "model": "vertex_ai/imagegeneration@006", "vertex_ai_project": "adroit-crow-413218", @@ -118,13 +119,13 @@ class TestVertexImageGeneration(BaseImageGenTest): class TestBedrockSd3(BaseImageGenTest): def get_base_image_generation_call_args(self) -> dict: - litellm.in_memory_llm_clients_cache = {} + litellm.in_memory_llm_clients_cache = InMemoryCache() return {"model": "bedrock/stability.sd3-large-v1:0"} class TestBedrockSd1(BaseImageGenTest): def get_base_image_generation_call_args(self) -> dict: - litellm.in_memory_llm_clients_cache = {} + litellm.in_memory_llm_clients_cache = InMemoryCache() return {"model": "bedrock/stability.sd3-large-v1:0"} @@ -181,7 +182,7 @@ def test_image_generation_azure_dall_e_3(): @pytest.mark.asyncio async def test_aimage_generation_bedrock_with_optional_params(): try: - litellm.in_memory_llm_clients_cache = {} + litellm.in_memory_llm_clients_cache = InMemoryCache() response = await litellm.aimage_generation( prompt="A cute baby sea otter", model="bedrock/stability.stable-diffusion-xl-v1", diff --git a/tests/llm_translation/Readme.md b/tests/llm_translation/Readme.md index 174c81b4e..db84e7c33 100644 --- a/tests/llm_translation/Readme.md +++ b/tests/llm_translation/Readme.md @@ -1 +1,3 @@ -More tests under `litellm/litellm/tests/*`. \ No newline at end of file +Unit tests for individual LLM providers. + +Name of the test file is the name of the LLM provider - e.g. `test_openai.py` is for OpenAI. \ No newline at end of file diff --git a/tests/llm_translation/base_llm_unit_tests.py b/tests/llm_translation/base_llm_unit_tests.py index 88fce6dac..d4c277744 100644 --- a/tests/llm_translation/base_llm_unit_tests.py +++ b/tests/llm_translation/base_llm_unit_tests.py @@ -62,7 +62,14 @@ class BaseLLMChatTest(ABC): response = litellm.completion(**base_completion_call_args, messages=messages) assert response is not None - def test_json_response_format(self): + @pytest.mark.parametrize( + "response_format", + [ + {"type": "json_object"}, + {"type": "text"}, + ], + ) + def test_json_response_format(self, response_format): """ Test that the JSON response format is supported by the LLM API """ @@ -83,7 +90,7 @@ class BaseLLMChatTest(ABC): response = litellm.completion( **base_completion_call_args, messages=messages, - response_format={"type": "json_object"}, + response_format=response_format, ) print(response) @@ -190,6 +197,35 @@ class BaseLLMChatTest(ABC): """Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833""" pass + def test_image_url(self): + litellm.set_verbose = True + from litellm.utils import supports_vision + + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + + base_completion_call_args = self.get_base_completion_call_args() + if not supports_vision(base_completion_call_args["model"], None): + pytest.skip("Model does not support image input") + + messages = [ + { + "role": "user", + "content": [ + {"type": "text", "text": "What's in this image?"}, + { + "type": "image_url", + "image_url": { + "url": "https://i.pinimg.com/736x/b4/b1/be/b4b1becad04d03a9071db2817fc9fe77.jpg" + }, + }, + ], + } + ] + + response = litellm.completion(**base_completion_call_args, messages=messages) + assert response is not None + @pytest.fixture def pdf_messages(self): import base64 diff --git a/tests/llm_translation/test_anthropic_completion.py b/tests/llm_translation/test_anthropic_completion.py index 812291767..076219961 100644 --- a/tests/llm_translation/test_anthropic_completion.py +++ b/tests/llm_translation/test_anthropic_completion.py @@ -785,3 +785,68 @@ def test_convert_tool_response_to_message_no_arguments(): message = AnthropicConfig._convert_tool_response_to_message(tool_calls=tool_calls) assert message is None + + +def test_anthropic_tool_with_image(): + from litellm.llms.prompt_templates.factory import prompt_factory + import json + + b64_data = "iVBORw0KGgoAAAANSUhEu6U3//C9t/fKv5wDgpP1r5796XwC4zyH1D565bHGDqbY85AMb0nIQe+u3J390Xbtb9XgXxcK0/aqRXpdYcwgARbCN03FJk" + image_url = f"data:image/png;base64,{b64_data}" + messages = [ + { + "content": [ + {"type": "text", "text": "go to github ryanhoangt by browser"}, + { + "type": "text", + "text": '\nThe following information has been included based on a keyword match for "github". It may or may not be relevant to the user\'s request.\n\nYou have access to an environment variable, `GITHUB_TOKEN`, which allows you to interact with\nthe GitHub API.\n\nYou can use `curl` with the `GITHUB_TOKEN` to interact with GitHub\'s API.\nALWAYS use the GitHub API for operations instead of a web browser.\n\nHere are some instructions for pushing, but ONLY do this if the user asks you to:\n* NEVER push directly to the `main` or `master` branch\n* Git config (username and email) is pre-set. Do not modify.\n* You may already be on a branch called `openhands-workspace`. Create a new branch with a better name before pushing.\n* Use the GitHub API to create a pull request, if you haven\'t already\n* Use the main branch as the base branch, unless the user requests otherwise\n* After opening or updating a pull request, send the user a short message with a link to the pull request.\n* Do all of the above in as few steps as possible. E.g. you could open a PR with one step by running the following bash commands:\n```bash\ngit remote -v && git branch # to find the current org, repo and branch\ngit checkout -b create-widget && git add . && git commit -m "Create widget" && git push -u origin create-widget\ncurl -X POST "https://api.github.com/repos/$ORG_NAME/$REPO_NAME/pulls" \\\n -H "Authorization: Bearer $GITHUB_TOKEN" \\\n -d \'{"title":"Create widget","head":"create-widget","base":"openhands-workspace"}\'\n```\n', + "cache_control": {"type": "ephemeral"}, + }, + ], + "role": "user", + }, + { + "content": [ + { + "type": "text", + "text": "I'll help you navigate to the GitHub profile of ryanhoangt using the browser.", + } + ], + "role": "assistant", + "tool_calls": [ + { + "index": 1, + "function": { + "arguments": '{"code": "goto(\'https://github.com/ryanhoangt\')"}', + "name": "browser", + }, + "id": "tooluse_UxfOQT6jRq-SvoQ9La_1sA", + "type": "function", + } + ], + }, + { + "content": [ + { + "type": "text", + "text": "[Current URL: https://github.com/ryanhoangt]\n[Focused element bid: 119]\n\n[Action executed successfully.]\n============== BEGIN accessibility tree ==============\nRootWebArea 'ryanhoangt (Ryan H. Tran) · GitHub', focused\n\t[119] generic\n\t\t[120] generic\n\t\t\t[121] generic\n\t\t\t\t[122] link 'Skip to content', clickable\n\t\t\t\t[123] generic\n\t\t\t\t\t[124] generic\n\t\t\t\t[135] generic\n\t\t\t\t\t[137] generic, clickable\n\t\t\t\t[142] banner ''\n\t\t\t\t\t[143] heading 'Navigation Menu'\n\t\t\t\t\t[146] generic\n\t\t\t\t\t\t[147] generic\n\t\t\t\t\t\t\t[148] generic\n\t\t\t\t\t\t\t[155] link 'Homepage', clickable\n\t\t\t\t\t\t\t[158] generic\n\t\t\t\t\t\t[160] generic\n\t\t\t\t\t\t\t[161] generic\n\t\t\t\t\t\t\t\t[162] navigation 'Global'\n\t\t\t\t\t\t\t\t\t[163] list ''\n\t\t\t\t\t\t\t\t\t\t[164] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t[165] button 'Product', expanded=False\n\t\t\t\t\t\t\t\t\t\t[244] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t[245] button 'Solutions', expanded=False\n\t\t\t\t\t\t\t\t\t\t[288] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t[289] button 'Resources', expanded=False\n\t\t\t\t\t\t\t\t\t\t[325] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t[326] button 'Open Source', expanded=False\n\t\t\t\t\t\t\t\t\t\t[352] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t[353] button 'Enterprise', expanded=False\n\t\t\t\t\t\t\t\t\t\t[392] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t[393] link 'Pricing', clickable\n\t\t\t\t\t\t\t\t[394] generic\n\t\t\t\t\t\t\t\t\t[395] generic\n\t\t\t\t\t\t\t\t\t\t[396] generic, clickable\n\t\t\t\t\t\t\t\t\t\t\t[397] button 'Search or jump to…', clickable, hasPopup='dialog'\n\t\t\t\t\t\t\t\t\t\t\t\t[398] generic\n\t\t\t\t\t\t\t\t\t\t[477] generic\n\t\t\t\t\t\t\t\t\t\t\t[478] generic\n\t\t\t\t\t\t\t\t\t\t\t[499] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[500] generic\n\t\t\t\t\t\t\t\t\t[534] generic\n\t\t\t\t\t\t\t\t\t\t[535] link 'Sign in', clickable\n\t\t\t\t\t\t\t\t\t[536] link 'Sign up', clickable\n\t\t\t[553] generic\n\t\t\t[554] generic\n\t\t\t[556] generic\n\t\t\t\t[557] main ''\n\t\t\t\t\t[558] generic\n\t\t\t\t\t[566] generic\n\t\t\t\t\t\t[567] generic\n\t\t\t\t\t\t\t[568] generic\n\t\t\t\t\t\t\t\t[569] generic\n\t\t\t\t\t\t\t\t\t[570] generic\n\t\t\t\t\t\t\t\t\t\t[571] LayoutTable ''\n\t\t\t\t\t\t\t\t\t\t\t[572] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[573] image '@ryanhoangt'\n\t\t\t\t\t\t\t\t\t\t\t[574] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[575] strong ''\n\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'ryanhoangt'\n\t\t\t\t\t\t\t\t\t\t\t\t[576] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[577] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[578] link 'Follow', clickable\n\t\t\t\t\t\t\t\t[579] generic\n\t\t\t\t\t\t\t\t\t[580] generic\n\t\t\t\t\t\t\t\t\t\t[581] navigation 'User profile'\n\t\t\t\t\t\t\t\t\t\t\t[582] link 'Overview', clickable\n\t\t\t\t\t\t\t\t\t\t\t[585] link 'Repositories 136', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t[588] generic '136'\n\t\t\t\t\t\t\t\t\t\t\t[589] link 'Projects', clickable\n\t\t\t\t\t\t\t\t\t\t\t[593] link 'Packages', clickable\n\t\t\t\t\t\t\t\t\t\t\t[597] link 'Stars 311', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t[600] generic '311'\n\t\t\t\t\t[621] generic\n\t\t\t\t\t\t[622] generic\n\t\t\t\t\t\t\t[623] generic\n\t\t\t\t\t\t\t\t[624] generic\n\t\t\t\t\t\t\t\t\t[625] generic\n\t\t\t\t\t\t\t\t\t\t[626] LayoutTable ''\n\t\t\t\t\t\t\t\t\t\t\t[627] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[628] image '@ryanhoangt'\n\t\t\t\t\t\t\t\t\t\t\t[629] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[630] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[631] strong ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'ryanhoangt'\n\t\t\t\t\t\t\t\t\t\t\t[632] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[633] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[634] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[635] link 'Follow', clickable\n\t\t\t\t\t\t\t\t\t[636] generic\n\t\t\t\t\t\t\t\t\t\t[637] generic\n\t\t\t\t\t\t\t\t\t\t\t[638] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[639] link \"View ryanhoangt's full-sized avatar\", clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t[640] image \"View ryanhoangt's full-sized avatar\"\n\t\t\t\t\t\t\t\t\t\t\t\t[641] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[642] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[643] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[644] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[645] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[646] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '🎯'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[647] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[648] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Focusing'\n\t\t\t\t\t\t\t\t\t\t\t[649] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[650] heading 'Ryan H. Tran ryanhoangt'\n\t\t\t\t\t\t\t\t\t\t\t\t\t[651] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Ryan H. Tran'\n\t\t\t\t\t\t\t\t\t\t\t\t\t[652] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'ryanhoangt'\n\t\t\t\t\t\t\t\t\t\t[660] generic\n\t\t\t\t\t\t\t\t\t\t\t[661] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[662] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[663] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[665] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[666] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[667] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[668] link 'Follow', clickable\n\t\t\t\t\t\t\t\t\t\t\t[669] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[670] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[671] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText \"Working with Attention. It's all we need\"\n\t\t\t\t\t\t\t\t\t\t\t\t[672] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[673] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[674] link '11 followers', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[677] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '11'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '·'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[678] link '30 following', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[679] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '30'\n\t\t\t\t\t\t\t\t\t\t\t\t[680] list ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[681] listitem 'Home location: Earth'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[684] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Earth'\n\t\t\t\t\t\t\t\t\t\t\t\t\t[685] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[688] link 'hoangt.dev', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t[689] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[692] link 'https://orcid.org/0009-0000-3619-0932', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t[693] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[694] image 'X'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[696] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[697] link '@ryanhoangt', clickable\n\t\t\t\t\t\t\t\t\t\t[698] generic\n\t\t\t\t\t\t\t\t\t\t\t[699] heading 'Achievements'\n\t\t\t\t\t\t\t\t\t\t\t\t[700] link 'Achievements', clickable\n\t\t\t\t\t\t\t\t\t\t\t[701] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[702] link 'Achievement: Pair Extraordinaire', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t[703] image 'Achievement: Pair Extraordinaire'\n\t\t\t\t\t\t\t\t\t\t\t\t[704] link 'Achievement: Pull Shark x2', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t[705] image 'Achievement: Pull Shark'\n\t\t\t\t\t\t\t\t\t\t\t\t\t[706] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'x2'\n\t\t\t\t\t\t\t\t\t\t\t\t[707] link 'Achievement: YOLO', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t[708] image 'Achievement: YOLO'\n\t\t\t\t\t\t\t\t\t\t[720] generic\n\t\t\t\t\t\t\t\t\t\t\t[721] heading 'Highlights'\n\t\t\t\t\t\t\t\t\t\t\t[722] list ''\n\t\t\t\t\t\t\t\t\t\t\t\t[723] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[724] link 'Developer Program Member', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t[727] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[730] generic 'Label: Pro'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'PRO'\n\t\t\t\t\t\t\t\t\t\t[731] button 'Block or Report'\n\t\t\t\t\t\t\t\t\t\t\t[732] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[733] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Block or Report'\n\t\t\t\t\t\t\t\t\t\t[734] generic\n\t\t\t\t\t\t\t[775] generic\n\t\t\t\t\t\t\t\t[817] generic, clickable\n\t\t\t\t\t\t\t\t\t[818] generic\n\t\t\t\t\t\t\t\t\t\t[819] generic\n\t\t\t\t\t\t\t\t\t\t\t[820] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[821] heading 'PinnedLoading'\n\t\t\t\t\t\t\t\t\t\t\t\t\t[822] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[826] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Loading'\n\t\t\t\t\t\t\t\t\t\t\t\t\t[827] status '', live='polite', atomic, relevant='additions text'\n\t\t\t\t\t\t\t\t\t\t\t\t[828] list '', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t[829] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[830] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[831] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[832] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[833] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[836] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[837] link 'All-Hands-AI/OpenHands', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[838] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'All-Hands-AI/'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[839] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'OpenHands'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[843] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[844] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Public'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[845] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '🙌 OpenHands: Code Less, Make More'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[846] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[847] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[848] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[849] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Python'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[850] link 'stars 37.5k', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[851] image 'stars'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[852] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[853] link 'forks 4.2k', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[854] image 'forks'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[855] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[856] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[857] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[858] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[859] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[860] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[863] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[864] link 'nus-apr/auto-code-rover', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[865] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'nus-apr/'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[866] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'auto-code-rover'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[870] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[871] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Public'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[872] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 37.3% tasks (pass@1) in SWE-bench lite and 46.2% tasks (pass@1) in SWE-bench verified with…'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[873] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[874] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[875] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[876] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Python'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[877] link 'stars 2.7k', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[878] image 'stars'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[879] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[880] link 'forks 288', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[881] image 'forks'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[882] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[883] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[884] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[885] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[886] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[887] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[890] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[891] link 'TransformerLensOrg/TransformerLens', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[892] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'TransformerLensOrg/'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[893] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'TransformerLens'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[897] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[898] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Public'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[899] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'A library for mechanistic interpretability of GPT-style language models'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[900] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[901] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[902] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[903] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Python'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[904] link 'stars 1.6k', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[905] image 'stars'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[906] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[907] link 'forks 308', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[908] image 'forks'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[909] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[910] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[911] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[912] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[913] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[914] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[917] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[918] link 'danbraunai/simple_stories_train', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[919] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'danbraunai/'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[920] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'simple_stories_train'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[924] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[925] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Public'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[926] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Trains small LMs. Designed for training on SimpleStories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[927] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[928] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[929] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[930] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Python'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[931] link 'stars 3', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[932] image 'stars'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[933] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[934] link 'fork 1', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[935] image 'fork'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[936] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[937] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[938] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[939] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[940] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[941] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[944] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[945] link 'locify', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[946] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'locify'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[950] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[951] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Public'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[952] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'A library for LLM-based agents to navigate large codebases efficiently.'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[953] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[954] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[955] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[956] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Python'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[957] link 'stars 6', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[958] image 'stars'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[959] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t[960] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[961] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[962] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[963] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[964] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[967] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[968] link 'iDunno', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[969] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'iDunno'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[973] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[974] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Public'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[975] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'A Distributed ML Cluster'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[976] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[977] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[978] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[979] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Java'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[980] link 'stars 3', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[981] image 'stars'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[982] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t[983] generic\n\t\t\t\t\t\t\t\t\t\t\t[984] generic\n\t\t\t\t\t\t\t\t\t\t\t\t[985] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[986] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[987] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[988] heading '481 contributions in the last year'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[989] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[990] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[991] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2099] grid 'Contribution Graph', clickable, multiselectable=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2100] caption ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Contribution Graph'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2101] rowgroup ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2102] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2103] gridcell 'Day of Week'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2104] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Day of Week'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2105] gridcell 'December'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2106] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'December'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2108] gridcell 'January'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2109] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'January'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2111] gridcell 'February'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2112] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'February'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2114] gridcell 'March'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2115] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'March'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2117] gridcell 'April'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2118] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'April'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2120] gridcell 'May'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2121] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'May'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2123] gridcell 'June'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2124] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'June'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2126] gridcell 'July'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2127] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'July'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2129] gridcell 'August'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2130] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'August'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2132] gridcell 'September'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2133] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'September'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2135] gridcell 'October'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2136] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'October'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2138] gridcell 'November'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2139] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'November'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2141] rowgroup ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2142] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2143] gridcell 'Sunday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2144] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Sunday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2146] gridcell '14 contributions on November 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-4'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2147] gridcell '3 contributions on December 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2148] gridcell '5 contributions on December 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2149] gridcell 'No contributions on December 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2150] gridcell '5 contributions on December 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2151] gridcell 'No contributions on December 31st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2152] gridcell '1 contribution on January 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2153] gridcell '2 contributions on January 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2154] gridcell '2 contributions on January 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2155] gridcell '2 contributions on January 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2156] gridcell 'No contributions on February 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2157] gridcell '1 contribution on February 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2158] gridcell 'No contributions on February 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2159] gridcell 'No contributions on February 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2160] gridcell 'No contributions on March 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2161] gridcell 'No contributions on March 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2162] gridcell 'No contributions on March 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2163] gridcell '2 contributions on March 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2164] gridcell '3 contributions on March 31st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2165] gridcell 'No contributions on April 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2166] gridcell '5 contributions on April 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2167] gridcell '2 contributions on April 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2168] gridcell 'No contributions on April 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2169] gridcell 'No contributions on May 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2170] gridcell 'No contributions on May 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2171] gridcell '1 contribution on May 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2172] gridcell '1 contribution on May 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2173] gridcell '2 contributions on June 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2174] gridcell '5 contributions on June 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2175] gridcell '1 contribution on June 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2176] gridcell 'No contributions on June 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2177] gridcell 'No contributions on June 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2178] gridcell 'No contributions on July 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2179] gridcell 'No contributions on July 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2180] gridcell '5 contributions on July 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2181] gridcell 'No contributions on July 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2182] gridcell '3 contributions on August 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2183] gridcell '1 contribution on August 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2184] gridcell '1 contribution on August 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2185] gridcell '1 contribution on August 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2186] gridcell '1 contribution on September 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2187] gridcell 'No contributions on September 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2188] gridcell '1 contribution on September 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2189] gridcell '2 contributions on September 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2190] gridcell '1 contribution on September 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2191] gridcell '2 contributions on October 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2192] gridcell '2 contributions on October 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2193] gridcell '4 contributions on October 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2194] gridcell '1 contribution on October 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2195] gridcell '14 contributions on November 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-4'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2196] gridcell '10 contributions on November 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-3'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2197] gridcell '2 contributions on November 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2198] gridcell '1 contribution on November 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2199] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2200] gridcell 'Monday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2201] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Monday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2203] gridcell 'No contributions on November 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2204] gridcell 'No contributions on December 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2205] gridcell '2 contributions on December 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2206] gridcell '2 contributions on December 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2207] gridcell '3 contributions on December 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2208] gridcell '2 contributions on January 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2209] gridcell '1 contribution on January 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2210] gridcell 'No contributions on January 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2211] gridcell '3 contributions on January 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2212] gridcell '3 contributions on January 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2213] gridcell 'No contributions on February 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2214] gridcell '2 contributions on February 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2215] gridcell '1 contribution on February 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2216] gridcell 'No contributions on February 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2217] gridcell 'No contributions on March 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2218] gridcell '1 contribution on March 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2219] gridcell '1 contribution on March 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2220] gridcell 'No contributions on March 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2221] gridcell '1 contribution on April 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2222] gridcell '1 contribution on April 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2223] gridcell '1 contribution on April 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2224] gridcell '1 contribution on April 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2225] gridcell '1 contribution on April 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2226] gridcell '2 contributions on May 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2227] gridcell 'No contributions on May 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2228] gridcell 'No contributions on May 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2229] gridcell '1 contribution on May 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2230] gridcell 'No contributions on June 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2231] gridcell '3 contributions on June 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2232] gridcell 'No contributions on June 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2233] gridcell 'No contributions on June 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2234] gridcell '1 contribution on July 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2235] gridcell 'No contributions on July 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2236] gridcell 'No contributions on July 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2237] gridcell 'No contributions on July 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2238] gridcell '1 contribution on July 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2239] gridcell '1 contribution on August 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2240] gridcell 'No contributions on August 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2241] gridcell '2 contributions on August 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2242] gridcell '1 contribution on August 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2243] gridcell 'No contributions on September 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2244] gridcell 'No contributions on September 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2245] gridcell '1 contribution on September 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2246] gridcell '2 contributions on September 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2247] gridcell '1 contribution on September 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2248] gridcell '1 contribution on October 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2249] gridcell '1 contribution on October 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2250] gridcell '7 contributions on October 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2251] gridcell '1 contribution on October 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2252] gridcell '4 contributions on November 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2253] gridcell '2 contributions on November 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2254] gridcell '1 contribution on November 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2255] gridcell '1 contribution on November 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2256] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2257] gridcell 'Tuesday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2258] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Tuesday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2260] gridcell 'No contributions on November 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2261] gridcell '3 contributions on December 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2262] gridcell '1 contribution on December 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2263] gridcell 'No contributions on December 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2264] gridcell '2 contributions on December 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2265] gridcell '2 contributions on January 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2266] gridcell 'No contributions on January 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2267] gridcell 'No contributions on January 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2268] gridcell 'No contributions on January 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2269] gridcell 'No contributions on January 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2270] gridcell 'No contributions on February 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2271] gridcell 'No contributions on February 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2272] gridcell 'No contributions on February 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2273] gridcell 'No contributions on February 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2274] gridcell 'No contributions on March 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2275] gridcell 'No contributions on March 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2276] gridcell 'No contributions on March 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2277] gridcell 'No contributions on March 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2278] gridcell '1 contribution on April 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2279] gridcell '1 contribution on April 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2280] gridcell '1 contribution on April 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2281] gridcell '2 contributions on April 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2282] gridcell '1 contribution on April 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2283] gridcell 'No contributions on May 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2284] gridcell '1 contribution on May 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2285] gridcell '2 contributions on May 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2286] gridcell '2 contributions on May 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2287] gridcell '1 contribution on June 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2288] gridcell '1 contribution on June 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2289] gridcell 'No contributions on June 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2290] gridcell 'No contributions on June 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2291] gridcell '1 contribution on July 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2292] gridcell '1 contribution on July 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2293] gridcell '1 contribution on July 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2294] gridcell '1 contribution on July 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2295] gridcell 'No contributions on July 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2296] gridcell 'No contributions on August 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2297] gridcell 'No contributions on August 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2298] gridcell 'No contributions on August 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2299] gridcell 'No contributions on August 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2300] gridcell '1 contribution on September 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2301] gridcell 'No contributions on September 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2302] gridcell 'No contributions on September 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2303] gridcell '2 contributions on September 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2304] gridcell '1 contribution on October 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2305] gridcell '1 contribution on October 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2306] gridcell '1 contribution on October 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2307] gridcell '3 contributions on October 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2308] gridcell '2 contributions on October 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2309] gridcell '3 contributions on November 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2310] gridcell '3 contributions on November 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2311] gridcell '2 contributions on November 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2312] gridcell 'No contributions on November 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2313] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2314] gridcell 'Wednesday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2315] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Wednesday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2317] gridcell '1 contribution on November 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2318] gridcell '3 contributions on December 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2319] gridcell '1 contribution on December 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2320] gridcell '4 contributions on December 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2321] gridcell '2 contributions on December 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2322] gridcell '1 contribution on January 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2323] gridcell 'No contributions on January 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2324] gridcell 'No contributions on January 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2325] gridcell 'No contributions on January 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2326] gridcell 'No contributions on January 31st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2327] gridcell 'No contributions on February 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2328] gridcell '1 contribution on February 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2329] gridcell '1 contribution on February 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2330] gridcell '1 contribution on February 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2331] gridcell 'No contributions on March 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2332] gridcell 'No contributions on March 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2333] gridcell 'No contributions on March 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2334] gridcell 'No contributions on March 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2335] gridcell '3 contributions on April 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2336] gridcell 'No contributions on April 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2337] gridcell '1 contribution on April 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2338] gridcell 'No contributions on April 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2339] gridcell 'No contributions on May 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2340] gridcell '1 contribution on May 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2341] gridcell '2 contributions on May 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2342] gridcell '1 contribution on May 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2343] gridcell 'No contributions on May 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2344] gridcell '3 contributions on June 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2345] gridcell '1 contribution on June 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2346] gridcell '1 contribution on June 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2347] gridcell '1 contribution on June 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2348] gridcell 'No contributions on July 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2349] gridcell '1 contribution on July 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2350] gridcell 'No contributions on July 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2351] gridcell '1 contribution on July 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2352] gridcell '2 contributions on July 31st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2353] gridcell '1 contribution on August 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2354] gridcell '1 contribution on August 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2355] gridcell '2 contributions on August 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2356] gridcell '1 contribution on August 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2357] gridcell 'No contributions on September 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2358] gridcell 'No contributions on September 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2359] gridcell '1 contribution on September 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2360] gridcell '1 contribution on September 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2361] gridcell '1 contribution on October 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2362] gridcell '1 contribution on October 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2363] gridcell '3 contributions on October 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2364] gridcell '4 contributions on October 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2365] gridcell '1 contribution on October 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2366] gridcell '2 contributions on November 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2367] gridcell '1 contribution on November 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2368] gridcell 'No contributions on November 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2369] gridcell '1 contribution on November 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2370] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2371] gridcell 'Thursday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2372] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Thursday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2374] gridcell 'No contributions on November 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2375] gridcell 'No contributions on December 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2376] gridcell '2 contributions on December 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2377] gridcell '3 contributions on December 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2378] gridcell 'No contributions on December 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2379] gridcell 'No contributions on January 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2380] gridcell 'No contributions on January 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2381] gridcell 'No contributions on January 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2382] gridcell '1 contribution on January 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2383] gridcell 'No contributions on February 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2384] gridcell 'No contributions on February 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2385] gridcell 'No contributions on February 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2386] gridcell '1 contribution on February 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2387] gridcell '1 contribution on February 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2388] gridcell '6 contributions on March 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2389] gridcell 'No contributions on March 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2390] gridcell 'No contributions on March 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2391] gridcell '1 contribution on March 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2392] gridcell '3 contributions on April 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2393] gridcell '1 contribution on April 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2394] gridcell '1 contribution on April 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2395] gridcell 'No contributions on April 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2396] gridcell '1 contribution on May 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2397] gridcell '1 contribution on May 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2398] gridcell 'No contributions on May 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2399] gridcell 'No contributions on May 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2400] gridcell '2 contributions on May 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2401] gridcell '1 contribution on June 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2402] gridcell 'No contributions on June 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2403] gridcell 'No contributions on June 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2404] gridcell '1 contribution on June 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2405] gridcell '3 contributions on July 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2406] gridcell '1 contribution on July 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2407] gridcell '1 contribution on July 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2408] gridcell '1 contribution on July 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2409] gridcell 'No contributions on August 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2410] gridcell '1 contribution on August 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2411] gridcell 'No contributions on August 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2412] gridcell '1 contribution on August 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2413] gridcell '1 contribution on August 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2414] gridcell '1 contribution on September 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2415] gridcell '1 contribution on September 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2416] gridcell '1 contribution on September 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2417] gridcell '1 contribution on September 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2418] gridcell '1 contribution on October 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2419] gridcell '2 contributions on October 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2420] gridcell '8 contributions on October 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2421] gridcell '1 contribution on October 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2422] gridcell '2 contributions on October 31st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2423] gridcell '1 contribution on November 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2424] gridcell '3 contributions on November 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2425] gridcell '2 contributions on November 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2426] gridcell '3 contributions on November 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2427] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2428] gridcell 'Friday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2429] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Friday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2431] gridcell 'No contributions on December 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2432] gridcell '1 contribution on December 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2433] gridcell '2 contributions on December 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2434] gridcell '1 contribution on December 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2435] gridcell '1 contribution on December 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2436] gridcell 'No contributions on January 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2437] gridcell '1 contribution on January 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2438] gridcell '1 contribution on January 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2439] gridcell 'No contributions on January 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2440] gridcell '1 contribution on February 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2441] gridcell 'No contributions on February 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2442] gridcell '1 contribution on February 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2443] gridcell 'No contributions on February 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2444] gridcell 'No contributions on March 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2445] gridcell 'No contributions on March 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2446] gridcell 'No contributions on March 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2447] gridcell 'No contributions on March 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2448] gridcell '1 contribution on March 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2449] gridcell 'No contributions on April 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2450] gridcell '2 contributions on April 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2451] gridcell 'No contributions on April 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2452] gridcell 'No contributions on April 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2453] gridcell 'No contributions on May 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2454] gridcell '1 contribution on May 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2455] gridcell '1 contribution on May 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2456] gridcell 'No contributions on May 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2457] gridcell 'No contributions on May 31st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2458] gridcell 'No contributions on June 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2459] gridcell 'No contributions on June 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2460] gridcell 'No contributions on June 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2461] gridcell '1 contribution on June 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2462] gridcell '1 contribution on July 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2463] gridcell '2 contributions on July 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2464] gridcell 'No contributions on July 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2465] gridcell '1 contribution on July 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2466] gridcell 'No contributions on August 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2467] gridcell '2 contributions on August 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2468] gridcell '2 contributions on August 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2469] gridcell 'No contributions on August 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2470] gridcell '1 contribution on August 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2471] gridcell 'No contributions on September 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2472] gridcell '1 contribution on September 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2473] gridcell '3 contributions on September 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2474] gridcell '1 contribution on September 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2475] gridcell 'No contributions on October 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2476] gridcell '3 contributions on October 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2477] gridcell '5 contributions on October 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2478] gridcell '3 contributions on October 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2479] gridcell '1 contribution on November 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2480] gridcell '1 contribution on November 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2481] gridcell '3 contributions on November 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2482] gridcell '1 contribution on November 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2483] gridcell ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2484] row ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2485] gridcell 'Saturday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2486] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Saturday'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2488] gridcell '10 contributions on December 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-3'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2489] gridcell '13 contributions on December 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-4'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2490] gridcell 'No contributions on December 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2491] gridcell '1 contribution on December 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2492] gridcell '10 contributions on December 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-3'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2493] gridcell '3 contributions on January 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2494] gridcell '1 contribution on January 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2495] gridcell '1 contribution on January 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2496] gridcell '3 contributions on January 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2497] gridcell 'No contributions on February 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2498] gridcell '1 contribution on February 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2499] gridcell 'No contributions on February 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2500] gridcell '1 contribution on February 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2501] gridcell 'No contributions on March 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2502] gridcell 'No contributions on March 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2503] gridcell 'No contributions on March 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2504] gridcell 'No contributions on March 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2505] gridcell '2 contributions on March 30th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2506] gridcell '1 contribution on April 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2507] gridcell '5 contributions on April 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2508] gridcell '1 contribution on April 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2509] gridcell 'No contributions on April 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2510] gridcell 'No contributions on May 4th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2511] gridcell '1 contribution on May 11th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2512] gridcell '1 contribution on May 18th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2513] gridcell 'No contributions on May 25th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2514] gridcell '2 contributions on June 1st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2515] gridcell 'No contributions on June 8th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2516] gridcell 'No contributions on June 15th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2517] gridcell 'No contributions on June 22nd.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2518] gridcell 'No contributions on June 29th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2519] gridcell '1 contribution on July 6th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2520] gridcell 'No contributions on July 13th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2521] gridcell '1 contribution on July 20th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2522] gridcell 'No contributions on July 27th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2523] gridcell '1 contribution on August 3rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2524] gridcell 'No contributions on August 10th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2525] gridcell 'No contributions on August 17th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2526] gridcell 'No contributions on August 24th.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2527] gridcell 'No contributions on August 31st.', clickable, selected=False, describedby='contribution-graph-legend-level-0'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2528] gridcell '1 contribution on September 7th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2529] gridcell '1 contribution on September 14th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2530] gridcell '1 contribution on September 21st.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2531] gridcell '1 contribution on September 28th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2532] gridcell '1 contribution on October 5th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2533] gridcell '5 contributions on October 12th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2534] gridcell '5 contributions on October 19th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2535] gridcell '7 contributions on October 26th.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2536] gridcell '5 contributions on November 2nd.', clickable, selected=False, describedby='contribution-graph-legend-level-2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2537] gridcell '17 contributions on November 9th.', clickable, selected=False, describedby='contribution-graph-legend-level-4'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2538] gridcell '1 contribution on November 16th.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2539] gridcell '1 contribution on November 23rd.', clickable, selected=False, describedby='contribution-graph-legend-level-1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2540] gridcell ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2541] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2542] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2543] link 'Learn how we count contributions', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2544] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2545] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Less'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2546] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2547] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'No contributions.'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2548] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2549] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Low contributions.'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2550] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2551] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Medium-low contributions.'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2552] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2553] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Medium-high contributions.'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2554] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2555] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'High contributions.'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2556] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'More'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2557] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2558] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2559] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2560] navigation 'Organizations'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2561] link '@All-Hands-AI', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2562] image ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2563] link '@Globe-NLP-Lab', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2564] image ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2565] link '@TransformerLensOrg', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2566] image ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2567] Details '', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2568] button 'More', clickable, hasPopup='menu', expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2569] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2591] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2592] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2593] heading 'Activity overview'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2594] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2597] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Contributed to'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2598] link 'All-Hands-AI/OpenHands', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText ','\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2599] link 'All-Hands-AI/openhands-aci', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText ','\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2600] link 'ryanhoangt/locify', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2601] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'and 36 other repositories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2602] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2603] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2604] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2608] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Loading'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2609] SvgRoot \"A graph representing ryanhoangt's contributions from November 26, 2023 to November 28, 2024. The contributions are 77% commits, 15% pull requests, 4% code review, 4% issues.\"\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2611] group ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2612] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2613] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2614] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2615] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2616] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2617] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2618] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2619] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '4%'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2620] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Code review'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2621] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '4%'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2622] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Issues'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2623] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '15%'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2624] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Pull requests'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2625] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '77%'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2626] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Commits'\n\t\t\t\t\t\t\t\t\t\t\t\t\t[2627] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2629] heading 'Contribution activity'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2630] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2631] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2632] heading 'November 2024'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2633] generic 'November 2024'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2634] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '2024'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2635] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2636] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2639] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2640] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2641] button 'Created 24 commits in 3 repositories', clickable, expanded=True\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2642] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Created 24 commits in 3 repositories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2643] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2644] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2650] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2651] list ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2652] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2653] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2654] link 'All-Hands-AI/openhands-aci', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2655] link '16 commits', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2656] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2657] image '67% of commits in November were made to All-Hands-AI/openhands-aci'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2658] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2659] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2660] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2661] link 'All-Hands-AI/OpenHands', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2662] link '4 commits', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2663] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2664] image '17% of commits in November were made to All-Hands-AI/OpenHands'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2665] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2666] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2667] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2668] link 'ryanhoangt/p4cm4n', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2669] link '4 commits', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2670] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2671] image '17% of commits in November were made to ryanhoangt/p4cm4n'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2672] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2673] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2674] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2677] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2678] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2679] button 'Created 3 repositories', clickable, expanded=True\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2680] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Created 3 repositories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2681] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2682] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2688] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2689] list ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2690] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2691] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2692] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2695] link 'ryanhoangt/TapeAgents', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2696] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2697] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2698] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2699] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Python'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2700] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2701] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'This contribution was made on Nov 21'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2703] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2704] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2705] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2708] link 'ryanhoangt/multilspy', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2709] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2710] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2711] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2712] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Python'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2713] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2714] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'This contribution was made on Nov 8'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2716] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2717] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2718] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2721] link 'ryanhoangt/anthropic-quickstarts', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2722] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2723] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2724] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2725] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'TypeScript'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2726] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2727] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'This contribution was made on Nov 3'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2729] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2730] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2733] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2734] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2735] heading 'Created a pull request in All-Hands-AI/OpenHands that received 20 comments'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2736] link 'All-Hands-AI/OpenHands', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2737] link 'Nov 17', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2738] time ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Nov 17'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2739] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2742] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2743] heading '[Experiment] Add symbol navigation commands into the editor'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2744] link '[Experiment] Add symbol navigation commands into the editor', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2745] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2746] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2747] strong ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'End-user friendly description of the problem this fixes or functionality that this introduces'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Include this change in the Release Notes. If checke…'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2748] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2749] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2750] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '+311'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2751] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '−105'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2752] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2753] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2754] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2755] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2756] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2757] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'lines changed'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2758] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '•'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '20 comments'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2759] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2760] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2763] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2764] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2765] button 'Opened 17 other pull requests in 5 repositories', clickable, expanded=True\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2766] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Opened 17 other pull requests in 5 repositories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2767] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2768] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2774] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2775] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2776] button 'All-Hands-AI/openhands-aci 2 open 8 merged', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2777] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2778] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'All-Hands-AI/openhands-aci'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2779] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2780] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'open'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2781] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '8'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'merged'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2782] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2786] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2896] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2897] button 'All-Hands-AI/OpenHands 4 merged', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2898] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2899] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'All-Hands-AI/OpenHands'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2900] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2901] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '4'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'merged'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2902] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2906] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2951] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2952] button 'ryanhoangt/multilspy 1 open', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2953] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2954] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'ryanhoangt/multilspy'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2955] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2956] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'open'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2957] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2961] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2976] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2977] button 'anthropics/anthropic-quickstarts 1 closed', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2978] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2979] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'anthropics/anthropic-quickstarts'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2980] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2981] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'closed'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2982] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[2986] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3001] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3002] button 'danbraunai/simple_stories_train 1 open', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3003] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3004] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'danbraunai/simple_stories_train'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3005] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3006] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'open'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3007] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3011] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3026] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3027] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3030] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3031] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3032] button 'Reviewed 6 pull requests in 2 repositories', clickable, expanded=True\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3033] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Reviewed 6 pull requests in 2 repositories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3034] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3035] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3041] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3042] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3043] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3044] button 'All-Hands-AI/openhands-aci 3 pull requests', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3045] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3046] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'All-Hands-AI/openhands-aci'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3047] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '3 pull requests'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3048] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3052] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3087] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3088] button 'All-Hands-AI/OpenHands 3 pull requests', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3089] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3090] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'All-Hands-AI/OpenHands'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3091] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '3 pull requests'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3092] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3096] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3131] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3132] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3135] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3136] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3137] heading 'Created an issue in All-Hands-AI/OpenHands that received 1 comment'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3138] link 'All-Hands-AI/OpenHands', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3139] link 'Nov 7', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3140] time ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Nov 7'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3141] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3145] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3146] heading '[Bug]: Patch collection after eval was empty although the agent did make changes'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3147] link '[Bug]: Patch collection after eval was empty although the agent did make changes', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3148] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3149] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText \"Is there an existing issue for the same bug? I have checked the existing issues. Describe the bug and reproduction steps I'm running eval for\"\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3150] link '#4782', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3151] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3152] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3153] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3154] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3158] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3159] SvgRoot ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3160] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3161] graphics-symbol ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3162] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '1 task done'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3163] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '•'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '1 comment'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3164] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3165] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3169] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3170] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3171] button 'Opened 3 other issues in 2 repositories', clickable, expanded=True\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3172] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Opened 3 other issues in 2 repositories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3173] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3174] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3180] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3181] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3182] button 'ryanhoangt/locify 2 open', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3183] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3184] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'ryanhoangt/locify'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3185] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3186] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '2'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'open'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3187] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3191] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3218] Details ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3219] button 'All-Hands-AI/openhands-aci 1 closed', clickable, expanded=False\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3220] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3221] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'All-Hands-AI/openhands-aci'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3222] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3223] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '1'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'closed'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3224] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3228] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3244] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3245] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3248] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3249] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '31 contributions in private repositories'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3250] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Nov 5 – Nov 25'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3251] Section ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3252] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3256] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Loading'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3257] button 'Show more activity', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3258] paragraph ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText 'Seeing something unexpected? Take a look at the'\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3259] link 'GitHub profile guide', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tStaticText '.'\n\t\t\t\t\t\t\t\t\t\t\t\t[3260] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t[3261] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3263] generic\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3264] list ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3265] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3266] link 'Contribution activity in 2024', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3267] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3268] link 'Contribution activity in 2023', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3269] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3270] link 'Contribution activity in 2022', clickable\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3271] listitem ''\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t[3272] link 'Contribution activity in 2021', clickable\n\t\t\t[3273] contentinfo ''\n\t\t\t\t[3274] heading 'Footer'\n\t\t\t\t[3275] generic\n\t\t\t\t\t[3276] generic\n\t\t\t\t\t\t[3277] link 'Homepage', clickable\n\t\t\t\t\t\t[3280] generic\n\t\t\t\t\t\t\tStaticText '© 2024 GitHub,\\xa0Inc.'\n\t\t\t\t\t[3281] navigation 'Footer'\n\t\t\t\t\t\t[3282] heading 'Footer navigation'\n\t\t\t\t\t\t[3283] list 'Footer navigation'\n\t\t\t\t\t\t\t[3284] listitem ''\n\t\t\t\t\t\t\t\t[3285] link 'Terms', clickable\n\t\t\t\t\t\t\t[3286] listitem ''\n\t\t\t\t\t\t\t\t[3287] link 'Privacy', clickable\n\t\t\t\t\t\t\t[3288] listitem ''\n\t\t\t\t\t\t\t\t[3289] link 'Security', clickable\n\t\t\t\t\t\t\t[3290] listitem ''\n\t\t\t\t\t\t\t\t[3291] link 'Status', clickable\n\t\t\t\t\t\t\t[3292] listitem ''\n\t\t\t\t\t\t\t\t[3293] link 'Docs', clickable\n\t\t\t\t\t\t\t[3294] listitem ''\n\t\t\t\t\t\t\t\t[3295] link 'Contact', clickable\n\t\t\t\t\t\t\t[3296] listitem ''\n\t\t\t\t\t\t\t\t[3297] generic\n\t\t\t\t\t\t\t\t\t[3298] button 'Manage cookies', clickable\n\t\t\t\t\t\t\t[3299] listitem ''\n\t\t\t\t\t\t\t\t[3300] generic\n\t\t\t\t\t\t\t\t\t[3301] button 'Do not share my personal information', clickable\n\t\t\t[3302] generic\n\t\t[3314] generic, live='polite', atomic, relevant='additions text'\n\t\t[3315] generic, live='assertive', atomic, relevant='additions text'\n============== END accessibility tree ==============\nThe screenshot of the current page is shown below.\n", + }, + { + "type": "image_url", + "image_url": {"url": image_url}, + }, + ], + "role": "tool", + "cache_control": {"type": "ephemeral"}, + "tool_call_id": "tooluse_UxfOQT6jRq-SvoQ9La_1sA", + "name": "browser", + }, + ] + + result = prompt_factory( + model="claude-3-5-sonnet-20240620", + messages=messages, + custom_llm_provider="anthropic", + ) + + assert b64_data in json.dumps(result) diff --git a/tests/llm_translation/test_azure_ai.py b/tests/llm_translation/test_azure_ai.py index 944e20148..f765a368f 100644 --- a/tests/llm_translation/test_azure_ai.py +++ b/tests/llm_translation/test_azure_ai.py @@ -45,81 +45,59 @@ def test_map_azure_model_group(model_group_header, expected_model): @pytest.mark.asyncio -@pytest.mark.respx -async def test_azure_ai_with_image_url(respx_mock: MockRouter): +async def test_azure_ai_with_image_url(): """ Important test: Test that Azure AI studio can handle image_url passed when content is a list containing both text and image_url """ + from openai import AsyncOpenAI + litellm.set_verbose = True - # Mock response based on the actual API response - mock_response = { - "id": "cmpl-53860ea1efa24d2883555bfec13d2254", - "choices": [ - { - "finish_reason": "stop", - "index": 0, - "logprobs": None, - "message": { - "content": "The image displays a graphic with the text 'LiteLLM' in black", - "role": "assistant", - "refusal": None, - "audio": None, - "function_call": None, - "tool_calls": None, - }, - } - ], - "created": 1731801937, - "model": "phi35-vision-instruct", - "object": "chat.completion", - "usage": { - "completion_tokens": 69, - "prompt_tokens": 617, - "total_tokens": 686, - "completion_tokens_details": None, - "prompt_tokens_details": None, - }, - } - - # Mock the API request - mock_request = respx_mock.post( - "https://Phi-3-5-vision-instruct-dcvov.eastus2.models.ai.azure.com" - ).mock(return_value=httpx.Response(200, json=mock_response)) - - response = await litellm.acompletion( - model="azure_ai/Phi-3-5-vision-instruct-dcvov", - api_base="https://Phi-3-5-vision-instruct-dcvov.eastus2.models.ai.azure.com", - messages=[ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "What is in this image?", - }, - { - "type": "image_url", - "image_url": { - "url": "https://litellm-listing.s3.amazonaws.com/litellm_logo.png" - }, - }, - ], - }, - ], + client = AsyncOpenAI( api_key="fake-api-key", + base_url="https://Phi-3-5-vision-instruct-dcvov.eastus2.models.ai.azure.com", ) - # Verify the request was made - assert mock_request.called + with patch.object( + client.chat.completions.with_raw_response, "create" + ) as mock_client: + try: + await litellm.acompletion( + model="azure_ai/Phi-3-5-vision-instruct-dcvov", + api_base="https://Phi-3-5-vision-instruct-dcvov.eastus2.models.ai.azure.com", + messages=[ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "What is in this image?", + }, + { + "type": "image_url", + "image_url": { + "url": "https://litellm-listing.s3.amazonaws.com/litellm_logo.png" + }, + }, + ], + }, + ], + api_key="fake-api-key", + client=client, + ) + except Exception as e: + traceback.print_exc() + print(f"Error: {e}") - # Check the request body - request_body = json.loads(mock_request.calls[0].request.content) - assert request_body == { - "model": "Phi-3-5-vision-instruct-dcvov", - "messages": [ + # Verify the request was made + mock_client.assert_called_once() + + # Check the request body + request_body = mock_client.call_args.kwargs + assert request_body["model"] == "Phi-3-5-vision-instruct-dcvov" + assert request_body["messages"] == [ { "role": "user", "content": [ @@ -132,7 +110,4 @@ async def test_azure_ai_with_image_url(respx_mock: MockRouter): }, ], } - ], - } - - print(f"response: {response}") + ] diff --git a/tests/llm_translation/test_bedrock_completion.py b/tests/llm_translation/test_bedrock_completion.py index 35a9fc276..e1bd7a9ab 100644 --- a/tests/llm_translation/test_bedrock_completion.py +++ b/tests/llm_translation/test_bedrock_completion.py @@ -1243,6 +1243,19 @@ def test_bedrock_cross_region_inference(model): ) +@pytest.mark.parametrize( + "model, expected_base_model", + [ + ( + "apac.anthropic.claude-3-5-sonnet-20240620-v1:0", + "anthropic.claude-3-5-sonnet-20240620-v1:0", + ), + ], +) +def test_bedrock_get_base_model(model, expected_base_model): + assert litellm.AmazonConverseConfig()._get_base_model(model) == expected_base_model + + from litellm.llms.prompt_templates.factory import _bedrock_converse_messages_pt diff --git a/tests/llm_translation/test_gemini.py b/tests/llm_translation/test_gemini.py new file mode 100644 index 000000000..4e6c5118d --- /dev/null +++ b/tests/llm_translation/test_gemini.py @@ -0,0 +1,15 @@ +from base_llm_unit_tests import BaseLLMChatTest + + +class TestGoogleAIStudioGemini(BaseLLMChatTest): + def get_base_completion_call_args(self) -> dict: + return {"model": "gemini/gemini-1.5-flash"} + + def test_tool_call_no_arguments(self, tool_call_no_arguments): + """Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833""" + from litellm.llms.prompt_templates.factory import ( + convert_to_gemini_tool_call_invoke, + ) + + result = convert_to_gemini_tool_call_invoke(tool_call_no_arguments) + print(result) diff --git a/tests/llm_translation/test_max_completion_tokens.py b/tests/llm_translation/test_max_completion_tokens.py index de335a3c5..6ac681b80 100644 --- a/tests/llm_translation/test_max_completion_tokens.py +++ b/tests/llm_translation/test_max_completion_tokens.py @@ -13,6 +13,7 @@ load_dotenv() import httpx import pytest from respx import MockRouter +from unittest.mock import patch, MagicMock, AsyncMock import litellm from litellm import Choices, Message, ModelResponse @@ -41,56 +42,58 @@ def return_mocked_response(model: str): "bedrock/mistral.mistral-large-2407-v1:0", ], ) -@pytest.mark.respx @pytest.mark.asyncio() -async def test_bedrock_max_completion_tokens(model: str, respx_mock: MockRouter): +async def test_bedrock_max_completion_tokens(model: str): """ Tests that: - max_completion_tokens is passed as max_tokens to bedrock models """ + from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler + litellm.set_verbose = True + client = AsyncHTTPHandler() + mock_response = return_mocked_response(model) _model = model.split("/")[1] print("\n\nmock_response: ", mock_response) - url = f"https://bedrock-runtime.us-west-2.amazonaws.com/model/{_model}/converse" - mock_request = respx_mock.post(url).mock( - return_value=httpx.Response(200, json=mock_response) - ) - response = await litellm.acompletion( - model=model, - max_completion_tokens=10, - messages=[{"role": "user", "content": "Hello!"}], - ) + with patch.object(client, "post") as mock_client: + try: + response = await litellm.acompletion( + model=model, + max_completion_tokens=10, + messages=[{"role": "user", "content": "Hello!"}], + client=client, + ) + except Exception as e: + print(f"Error: {e}") - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) + mock_client.assert_called_once() + request_body = json.loads(mock_client.call_args.kwargs["data"]) - print("request_body: ", request_body) + print("request_body: ", request_body) - assert request_body == { - "messages": [{"role": "user", "content": [{"text": "Hello!"}]}], - "additionalModelRequestFields": {}, - "system": [], - "inferenceConfig": {"maxTokens": 10}, - } - print(f"response: {response}") - assert isinstance(response, ModelResponse) + assert request_body == { + "messages": [{"role": "user", "content": [{"text": "Hello!"}]}], + "additionalModelRequestFields": {}, + "system": [], + "inferenceConfig": {"maxTokens": 10}, + } @pytest.mark.parametrize( "model", - ["anthropic/claude-3-sonnet-20240229", "anthropic/claude-3-opus-20240229,"], + ["anthropic/claude-3-sonnet-20240229", "anthropic/claude-3-opus-20240229"], ) -@pytest.mark.respx @pytest.mark.asyncio() -async def test_anthropic_api_max_completion_tokens(model: str, respx_mock: MockRouter): +async def test_anthropic_api_max_completion_tokens(model: str): """ Tests that: - max_completion_tokens is passed as max_tokens to anthropic models """ litellm.set_verbose = True + from litellm.llms.custom_httpx.http_handler import HTTPHandler mock_response = { "content": [{"text": "Hi! My name is Claude.", "type": "text"}], @@ -103,30 +106,32 @@ async def test_anthropic_api_max_completion_tokens(model: str, respx_mock: MockR "usage": {"input_tokens": 2095, "output_tokens": 503}, } + client = HTTPHandler() + print("\n\nmock_response: ", mock_response) - url = f"https://api.anthropic.com/v1/messages" - mock_request = respx_mock.post(url).mock( - return_value=httpx.Response(200, json=mock_response) - ) - response = await litellm.acompletion( - model=model, - max_completion_tokens=10, - messages=[{"role": "user", "content": "Hello!"}], - ) + with patch.object(client, "post") as mock_client: + try: + response = await litellm.acompletion( + model=model, + max_completion_tokens=10, + messages=[{"role": "user", "content": "Hello!"}], + client=client, + ) + except Exception as e: + print(f"Error: {e}") + mock_client.assert_called_once() + request_body = mock_client.call_args.kwargs["json"] - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) + print("request_body: ", request_body) - print("request_body: ", request_body) - - assert request_body == { - "messages": [{"role": "user", "content": [{"type": "text", "text": "Hello!"}]}], - "max_tokens": 10, - "model": model.split("/")[-1], - } - print(f"response: {response}") - assert isinstance(response, ModelResponse) + assert request_body == { + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Hello!"}]} + ], + "max_tokens": 10, + "model": model.split("/")[-1], + } def test_all_model_configs(): diff --git a/tests/llm_translation/test_nvidia_nim.py b/tests/llm_translation/test_nvidia_nim.py index 76cb5764c..ca0374d45 100644 --- a/tests/llm_translation/test_nvidia_nim.py +++ b/tests/llm_translation/test_nvidia_nim.py @@ -12,95 +12,78 @@ sys.path.insert( import httpx import pytest from respx import MockRouter +from unittest.mock import patch, MagicMock, AsyncMock import litellm from litellm import Choices, Message, ModelResponse, EmbeddingResponse, Usage from litellm import completion -@pytest.mark.respx -def test_completion_nvidia_nim(respx_mock: MockRouter): +def test_completion_nvidia_nim(): + from openai import OpenAI + litellm.set_verbose = True - mock_response = ModelResponse( - id="cmpl-mock", - choices=[Choices(message=Message(content="Mocked response", role="assistant"))], - created=int(datetime.now().timestamp()), - model="databricks/dbrx-instruct", - ) model_name = "nvidia_nim/databricks/dbrx-instruct" + client = OpenAI( + api_key="fake-api-key", + ) - mock_request = respx_mock.post( - "https://integrate.api.nvidia.com/v1/chat/completions" - ).mock(return_value=httpx.Response(200, json=mock_response.dict())) - try: - response = completion( - model=model_name, - messages=[ - { - "role": "user", - "content": "What's the weather like in Boston today in Fahrenheit?", - } - ], - presence_penalty=0.5, - frequency_penalty=0.1, - ) + with patch.object( + client.chat.completions.with_raw_response, "create" + ) as mock_client: + try: + completion( + model=model_name, + messages=[ + { + "role": "user", + "content": "What's the weather like in Boston today in Fahrenheit?", + } + ], + presence_penalty=0.5, + frequency_penalty=0.1, + client=client, + ) + except Exception as e: + print(e) # Add any assertions here to check the response - print(response) - assert response.choices[0].message.content is not None - assert len(response.choices[0].message.content) > 0 - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) + mock_client.assert_called_once() + request_body = mock_client.call_args.kwargs print("request_body: ", request_body) - assert request_body == { - "messages": [ - { - "role": "user", - "content": "What's the weather like in Boston today in Fahrenheit?", - } - ], - "model": "databricks/dbrx-instruct", - "frequency_penalty": 0.1, - "presence_penalty": 0.5, - } - except litellm.exceptions.Timeout as e: - pass - except Exception as e: - pytest.fail(f"Error occurred: {e}") - - -def test_embedding_nvidia_nim(respx_mock: MockRouter): - litellm.set_verbose = True - mock_response = EmbeddingResponse( - model="nvidia_nim/databricks/dbrx-instruct", - data=[ + assert request_body["messages"] == [ { - "embedding": [0.1, 0.2, 0.3], - "index": 0, - } - ], - usage=Usage( - prompt_tokens=10, - completion_tokens=0, - total_tokens=10, - ), + "role": "user", + "content": "What's the weather like in Boston today in Fahrenheit?", + }, + ] + assert request_body["model"] == "databricks/dbrx-instruct" + assert request_body["frequency_penalty"] == 0.1 + assert request_body["presence_penalty"] == 0.5 + + +def test_embedding_nvidia_nim(): + litellm.set_verbose = True + from openai import OpenAI + + client = OpenAI( + api_key="fake-api-key", ) - mock_request = respx_mock.post( - "https://integrate.api.nvidia.com/v1/embeddings" - ).mock(return_value=httpx.Response(200, json=mock_response.dict())) - response = litellm.embedding( - model="nvidia_nim/nvidia/nv-embedqa-e5-v5", - input="What is the meaning of life?", - input_type="passage", - ) - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) - print("request_body: ", request_body) - assert request_body == { - "input": "What is the meaning of life?", - "model": "nvidia/nv-embedqa-e5-v5", - "input_type": "passage", - "encoding_format": "base64", - } + with patch.object(client.embeddings.with_raw_response, "create") as mock_client: + try: + litellm.embedding( + model="nvidia_nim/nvidia/nv-embedqa-e5-v5", + input="What is the meaning of life?", + input_type="passage", + client=client, + ) + except Exception as e: + print(e) + mock_client.assert_called_once() + request_body = mock_client.call_args.kwargs + print("request_body: ", request_body) + assert request_body["input"] == "What is the meaning of life?" + assert request_body["model"] == "nvidia/nv-embedqa-e5-v5" + assert request_body["extra_body"]["input_type"] == "passage" diff --git a/tests/llm_translation/test_openai_prediction_param.py b/tests/llm_translation/test_openai.py similarity index 54% rename from tests/llm_translation/test_openai_prediction_param.py rename to tests/llm_translation/test_openai.py index ebfdf061f..b07f4c5d2 100644 --- a/tests/llm_translation/test_openai_prediction_param.py +++ b/tests/llm_translation/test_openai.py @@ -2,7 +2,7 @@ import json import os import sys from datetime import datetime -from unittest.mock import AsyncMock +from unittest.mock import AsyncMock, patch sys.path.insert( 0, os.path.abspath("../..") @@ -63,8 +63,7 @@ def test_openai_prediction_param(): @pytest.mark.asyncio -@pytest.mark.respx -async def test_openai_prediction_param_mock(respx_mock: MockRouter): +async def test_openai_prediction_param_mock(): """ Tests that prediction parameter is correctly passed to the API """ @@ -92,60 +91,36 @@ async def test_openai_prediction_param_mock(respx_mock: MockRouter): public string Username { get; set; } } """ + from openai import AsyncOpenAI - mock_response = ModelResponse( - id="chatcmpl-AQ5RmV8GvVSRxEcDxnuXlQnsibiY9", - choices=[ - Choices( - message=Message( - content=code.replace("Username", "Email").replace( - "username", "email" - ), - role="assistant", - ) + client = AsyncOpenAI(api_key="fake-api-key") + + with patch.object( + client.chat.completions.with_raw_response, "create" + ) as mock_client: + try: + await litellm.acompletion( + model="gpt-4o-mini", + messages=[ + { + "role": "user", + "content": "Replace the Username property with an Email property. Respond only with code, and with no markdown formatting.", + }, + {"role": "user", "content": code}, + ], + prediction={"type": "content", "content": code}, + client=client, ) - ], - created=int(datetime.now().timestamp()), - model="gpt-4o-mini-2024-07-18", - usage={ - "completion_tokens": 207, - "prompt_tokens": 175, - "total_tokens": 382, - "completion_tokens_details": { - "accepted_prediction_tokens": 0, - "reasoning_tokens": 0, - "rejected_prediction_tokens": 80, - }, - }, - ) + except Exception as e: + print(f"Error: {e}") - mock_request = respx_mock.post("https://api.openai.com/v1/chat/completions").mock( - return_value=httpx.Response(200, json=mock_response.dict()) - ) + mock_client.assert_called_once() + request_body = mock_client.call_args.kwargs - completion = await litellm.acompletion( - model="gpt-4o-mini", - messages=[ - { - "role": "user", - "content": "Replace the Username property with an Email property. Respond only with code, and with no markdown formatting.", - }, - {"role": "user", "content": code}, - ], - prediction={"type": "content", "content": code}, - ) - - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) - - # Verify the request contains the prediction parameter - assert "prediction" in request_body - # verify prediction is correctly sent to the API - assert request_body["prediction"] == {"type": "content", "content": code} - - # Verify the completion tokens details - assert completion.usage.completion_tokens_details.accepted_prediction_tokens == 0 - assert completion.usage.completion_tokens_details.rejected_prediction_tokens == 80 + # Verify the request contains the prediction parameter + assert "prediction" in request_body + # verify prediction is correctly sent to the API + assert request_body["prediction"] == {"type": "content", "content": code} @pytest.mark.asyncio @@ -223,3 +198,73 @@ async def test_openai_prediction_param_with_caching(): ) assert completion_response_3.id != completion_response_1.id + + +@pytest.mark.asyncio() +async def test_vision_with_custom_model(): + """ + Tests that an OpenAI compatible endpoint when sent an image will receive the image in the request + + """ + import base64 + import requests + from openai import AsyncOpenAI + + client = AsyncOpenAI(api_key="fake-api-key") + + litellm.set_verbose = True + api_base = "https://my-custom.api.openai.com" + + # Fetch and encode a test image + url = "https://dummyimage.com/100/100/fff&text=Test+image" + response = requests.get(url) + file_data = response.content + encoded_file = base64.b64encode(file_data).decode("utf-8") + base64_image = f"data:image/png;base64,{encoded_file}" + + with patch.object( + client.chat.completions.with_raw_response, "create" + ) as mock_client: + try: + response = await litellm.acompletion( + model="openai/my-custom-model", + max_tokens=10, + api_base=api_base, # use the mock api + messages=[ + { + "role": "user", + "content": [ + {"type": "text", "text": "What's in this image?"}, + { + "type": "image_url", + "image_url": {"url": base64_image}, + }, + ], + } + ], + client=client, + ) + except Exception as e: + print(f"Error: {e}") + + mock_client.assert_called_once() + request_body = mock_client.call_args.kwargs + + print("request_body: ", request_body) + + assert request_body["messages"] == [ + { + "role": "user", + "content": [ + {"type": "text", "text": "What's in this image?"}, + { + "type": "image_url", + "image_url": { + "url": "data:image/png;base64,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" + }, + }, + ], + }, + ] + assert request_body["model"] == "my-custom-model" + assert request_body["max_tokens"] == 10 diff --git a/tests/llm_translation/test_openai_o1.py b/tests/llm_translation/test_openai_o1.py index fd4b1ea5a..2bb82c6a2 100644 --- a/tests/llm_translation/test_openai_o1.py +++ b/tests/llm_translation/test_openai_o1.py @@ -2,7 +2,7 @@ import json import os import sys from datetime import datetime -from unittest.mock import AsyncMock +from unittest.mock import AsyncMock, patch, MagicMock sys.path.insert( 0, os.path.abspath("../..") @@ -18,87 +18,75 @@ from litellm import Choices, Message, ModelResponse @pytest.mark.asyncio -@pytest.mark.respx -async def test_o1_handle_system_role(respx_mock: MockRouter): +async def test_o1_handle_system_role(): """ Tests that: - max_tokens is translated to 'max_completion_tokens' - role 'system' is translated to 'user' """ + from openai import AsyncOpenAI + litellm.set_verbose = True - mock_response = ModelResponse( - id="cmpl-mock", - choices=[Choices(message=Message(content="Mocked response", role="assistant"))], - created=int(datetime.now().timestamp()), - model="o1-preview", - ) + client = AsyncOpenAI(api_key="fake-api-key") - mock_request = respx_mock.post("https://api.openai.com/v1/chat/completions").mock( - return_value=httpx.Response(200, json=mock_response.dict()) - ) + with patch.object( + client.chat.completions.with_raw_response, "create" + ) as mock_client: + try: + await litellm.acompletion( + model="o1-preview", + max_tokens=10, + messages=[{"role": "system", "content": "Hello!"}], + client=client, + ) + except Exception as e: + print(f"Error: {e}") - response = await litellm.acompletion( - model="o1-preview", - max_tokens=10, - messages=[{"role": "system", "content": "Hello!"}], - ) + mock_client.assert_called_once() + request_body = mock_client.call_args.kwargs - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) + print("request_body: ", request_body) - print("request_body: ", request_body) - - assert request_body == { - "model": "o1-preview", - "max_completion_tokens": 10, - "messages": [{"role": "user", "content": "Hello!"}], - } - - print(f"response: {response}") - assert isinstance(response, ModelResponse) + assert request_body["model"] == "o1-preview" + assert request_body["max_completion_tokens"] == 10 + assert request_body["messages"] == [{"role": "user", "content": "Hello!"}] @pytest.mark.asyncio -@pytest.mark.respx @pytest.mark.parametrize("model", ["gpt-4", "gpt-4-0314", "gpt-4-32k", "o1-preview"]) -async def test_o1_max_completion_tokens(respx_mock: MockRouter, model: str): +async def test_o1_max_completion_tokens(model: str): """ Tests that: - max_completion_tokens is passed directly to OpenAI chat completion models """ + from openai import AsyncOpenAI + litellm.set_verbose = True - mock_response = ModelResponse( - id="cmpl-mock", - choices=[Choices(message=Message(content="Mocked response", role="assistant"))], - created=int(datetime.now().timestamp()), - model=model, - ) + client = AsyncOpenAI(api_key="fake-api-key") - mock_request = respx_mock.post("https://api.openai.com/v1/chat/completions").mock( - return_value=httpx.Response(200, json=mock_response.dict()) - ) + with patch.object( + client.chat.completions.with_raw_response, "create" + ) as mock_client: + try: + await litellm.acompletion( + model=model, + max_completion_tokens=10, + messages=[{"role": "user", "content": "Hello!"}], + client=client, + ) + except Exception as e: + print(f"Error: {e}") - response = await litellm.acompletion( - model=model, - max_completion_tokens=10, - messages=[{"role": "user", "content": "Hello!"}], - ) + mock_client.assert_called_once() + request_body = mock_client.call_args.kwargs - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) + print("request_body: ", request_body) - print("request_body: ", request_body) - - assert request_body == { - "model": model, - "max_completion_tokens": 10, - "messages": [{"role": "user", "content": "Hello!"}], - } - - print(f"response: {response}") - assert isinstance(response, ModelResponse) + assert request_body["model"] == model + assert request_body["max_completion_tokens"] == 10 + assert request_body["messages"] == [{"role": "user", "content": "Hello!"}] def test_litellm_responses(): diff --git a/tests/llm_translation/test_prompt_factory.py b/tests/llm_translation/test_prompt_factory.py index 104997563..d8cf191f6 100644 --- a/tests/llm_translation/test_prompt_factory.py +++ b/tests/llm_translation/test_prompt_factory.py @@ -687,3 +687,16 @@ def test_just_system_message(): llm_provider="bedrock", ) assert "bedrock requires at least one non-system message" in str(e.value) + + +def test_convert_generic_image_chunk_to_openai_image_obj(): + from litellm.llms.prompt_templates.factory import ( + convert_generic_image_chunk_to_openai_image_obj, + convert_to_anthropic_image_obj, + ) + + url = "https://i.pinimg.com/736x/b4/b1/be/b4b1becad04d03a9071db2817fc9fe77.jpg" + image_obj = convert_to_anthropic_image_obj(url) + url_str = convert_generic_image_chunk_to_openai_image_obj(image_obj) + image_obj = convert_to_anthropic_image_obj(url_str) + print(image_obj) diff --git a/tests/llm_translation/test_supports_vision.py b/tests/llm_translation/test_supports_vision.py deleted file mode 100644 index 01188d3b9..000000000 --- a/tests/llm_translation/test_supports_vision.py +++ /dev/null @@ -1,94 +0,0 @@ -import json -import os -import sys -from datetime import datetime -from unittest.mock import AsyncMock - -sys.path.insert( - 0, os.path.abspath("../..") -) # Adds the parent directory to the system path - - -import httpx -import pytest -from respx import MockRouter - -import litellm -from litellm import Choices, Message, ModelResponse - - -@pytest.mark.asyncio() -@pytest.mark.respx -async def test_vision_with_custom_model(respx_mock: MockRouter): - """ - Tests that an OpenAI compatible endpoint when sent an image will receive the image in the request - - """ - import base64 - import requests - - litellm.set_verbose = True - api_base = "https://my-custom.api.openai.com" - - # Fetch and encode a test image - url = "https://dummyimage.com/100/100/fff&text=Test+image" - response = requests.get(url) - file_data = response.content - encoded_file = base64.b64encode(file_data).decode("utf-8") - base64_image = f"data:image/png;base64,{encoded_file}" - - mock_response = ModelResponse( - id="cmpl-mock", - choices=[Choices(message=Message(content="Mocked response", role="assistant"))], - created=int(datetime.now().timestamp()), - model="my-custom-model", - ) - - mock_request = respx_mock.post(f"{api_base}/chat/completions").mock( - return_value=httpx.Response(200, json=mock_response.dict()) - ) - - response = await litellm.acompletion( - model="openai/my-custom-model", - max_tokens=10, - api_base=api_base, # use the mock api - messages=[ - { - "role": "user", - "content": [ - {"type": "text", "text": "What's in this image?"}, - { - "type": "image_url", - "image_url": {"url": base64_image}, - }, - ], - } - ], - ) - - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) - - print("request_body: ", request_body) - - assert request_body == { - "messages": [ - { - "role": "user", - "content": [ - {"type": "text", "text": "What's in this image?"}, - { - "type": "image_url", - "image_url": { - "url": "data:image/png;base64,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" - }, - }, - ], - } - ], - "model": "my-custom-model", - "max_tokens": 10, - } - - print(f"response: {response}") - assert isinstance(response, ModelResponse) diff --git a/tests/llm_translation/test_text_completion_unit_tests.py b/tests/llm_translation/test_text_completion_unit_tests.py index 9d5359a4a..ca239ebd4 100644 --- a/tests/llm_translation/test_text_completion_unit_tests.py +++ b/tests/llm_translation/test_text_completion_unit_tests.py @@ -6,6 +6,7 @@ from unittest.mock import AsyncMock import pytest import httpx from respx import MockRouter +from unittest.mock import patch, MagicMock, AsyncMock sys.path.insert( 0, os.path.abspath("../..") @@ -68,13 +69,16 @@ def test_convert_dict_to_text_completion_response(): assert response.choices[0].logprobs.top_logprobs == [None, {",": -2.1568563}] +@pytest.mark.skip( + reason="need to migrate huggingface to support httpx client being passed in" +) @pytest.mark.asyncio @pytest.mark.respx -async def test_huggingface_text_completion_logprobs(respx_mock: MockRouter): +async def test_huggingface_text_completion_logprobs(): """Test text completion with Hugging Face, focusing on logprobs structure""" litellm.set_verbose = True + from litellm.llms.custom_httpx.http_handler import HTTPHandler, AsyncHTTPHandler - # Mock the raw response from Hugging Face mock_response = [ { "generated_text": ",\n\nI have a question...", # truncated for brevity @@ -91,46 +95,48 @@ async def test_huggingface_text_completion_logprobs(respx_mock: MockRouter): } ] - # Mock the API request - mock_request = respx_mock.post( - "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-v0.1" - ).mock(return_value=httpx.Response(200, json=mock_response)) + return_val = AsyncMock() - response = await litellm.atext_completion( - model="huggingface/mistralai/Mistral-7B-v0.1", - prompt="good morning", - ) + return_val.json.return_value = mock_response - # Verify the request - assert mock_request.called - request_body = json.loads(mock_request.calls[0].request.content) - assert request_body == { - "inputs": "good morning", - "parameters": {"details": True, "return_full_text": False}, - "stream": False, - } + client = AsyncHTTPHandler() + with patch.object(client, "post", return_value=return_val) as mock_post: + response = await litellm.atext_completion( + model="huggingface/mistralai/Mistral-7B-v0.1", + prompt="good morning", + client=client, + ) - print("response=", response) + # Verify the request + mock_post.assert_called_once() + request_body = json.loads(mock_post.call_args.kwargs["data"]) + assert request_body == { + "inputs": "good morning", + "parameters": {"details": True, "return_full_text": False}, + "stream": False, + } - # Verify response structure - assert isinstance(response, TextCompletionResponse) - assert response.object == "text_completion" - assert response.model == "mistralai/Mistral-7B-v0.1" + print("response=", response) - # Verify logprobs structure - choice = response.choices[0] - assert choice.finish_reason == "length" - assert choice.index == 0 - assert isinstance(choice.logprobs.tokens, list) - assert isinstance(choice.logprobs.token_logprobs, list) - assert isinstance(choice.logprobs.text_offset, list) - assert isinstance(choice.logprobs.top_logprobs, list) - assert choice.logprobs.tokens == [",", "\n"] - assert choice.logprobs.token_logprobs == [-1.7626953, -1.7314453] - assert choice.logprobs.text_offset == [0, 1] - assert choice.logprobs.top_logprobs == [{}, {}] + # Verify response structure + assert isinstance(response, TextCompletionResponse) + assert response.object == "text_completion" + assert response.model == "mistralai/Mistral-7B-v0.1" - # Verify usage - assert response.usage["completion_tokens"] > 0 - assert response.usage["prompt_tokens"] > 0 - assert response.usage["total_tokens"] > 0 + # Verify logprobs structure + choice = response.choices[0] + assert choice.finish_reason == "length" + assert choice.index == 0 + assert isinstance(choice.logprobs.tokens, list) + assert isinstance(choice.logprobs.token_logprobs, list) + assert isinstance(choice.logprobs.text_offset, list) + assert isinstance(choice.logprobs.top_logprobs, list) + assert choice.logprobs.tokens == [",", "\n"] + assert choice.logprobs.token_logprobs == [-1.7626953, -1.7314453] + assert choice.logprobs.text_offset == [0, 1] + assert choice.logprobs.top_logprobs == [{}, {}] + + # Verify usage + assert response.usage["completion_tokens"] > 0 + assert response.usage["prompt_tokens"] > 0 + assert response.usage["total_tokens"] > 0 diff --git a/tests/llm_translation/test_vertex.py b/tests/llm_translation/test_vertex.py index 3e1087536..425b6f9f4 100644 --- a/tests/llm_translation/test_vertex.py +++ b/tests/llm_translation/test_vertex.py @@ -1146,6 +1146,21 @@ def test_process_gemini_image(): mime_type="image/png", file_uri="https://example.com/image.png" ) + # Test HTTPS VIDEO URL + https_result = _process_gemini_image("https://cloud-samples-data/video/animals.mp4") + print("https_result PNG", https_result) + assert https_result["file_data"] == FileDataType( + mime_type="video/mp4", file_uri="https://cloud-samples-data/video/animals.mp4" + ) + + # Test HTTPS PDF URL + https_result = _process_gemini_image("https://cloud-samples-data/pdf/animals.pdf") + print("https_result PDF", https_result) + assert https_result["file_data"] == FileDataType( + mime_type="application/pdf", + file_uri="https://cloud-samples-data/pdf/animals.pdf", + ) + # Test base64 image base64_image = "data:image/jpeg;base64,/9j/4AAQSkZJRg..." base64_result = _process_gemini_image(base64_image) @@ -1190,80 +1205,6 @@ def test_get_image_mime_type_from_url(): assert _get_image_mime_type_from_url("invalid_url") is None -@pytest.mark.parametrize( - "image_url", ["https://example.com/image.jpg", "https://example.com/image.png"] -) -def test_image_completion_request(image_url): - """https:// .jpg, .png images are passed directly to the model""" - from unittest.mock import patch, Mock - import litellm - from litellm.llms.vertex_ai_and_google_ai_studio.gemini.transformation import ( - _get_image_mime_type_from_url, - ) - - # Mock response data - mock_response = Mock() - mock_response.json.return_value = { - "candidates": [{"content": {"parts": [{"text": "This is a sunflower"}]}}], - "usageMetadata": { - "promptTokenCount": 11, - "candidatesTokenCount": 50, - "totalTokenCount": 61, - }, - "modelVersion": "gemini-1.5-pro", - } - mock_response.raise_for_status = MagicMock() - mock_response.status_code = 200 - - # Expected request body - expected_request_body = { - "contents": [ - { - "role": "user", - "parts": [ - {"text": "Whats in this image?"}, - { - "file_data": { - "file_uri": image_url, - "mime_type": _get_image_mime_type_from_url(image_url), - } - }, - ], - } - ], - "system_instruction": {"parts": [{"text": "Be a good bot"}]}, - "generationConfig": {}, - } - - messages = [ - {"role": "system", "content": "Be a good bot"}, - { - "role": "user", - "content": [ - {"type": "text", "text": "Whats in this image?"}, - {"type": "image_url", "image_url": {"url": image_url}}, - ], - }, - ] - - client = HTTPHandler() - with patch.object(client, "post", new=MagicMock()) as mock_post: - mock_post.return_value = mock_response - try: - litellm.completion( - model="gemini/gemini-1.5-pro", - messages=messages, - client=client, - ) - except Exception as e: - print(e) - - # Assert the request body matches expected - mock_post.assert_called_once() - print("mock_post.call_args.kwargs['json']", mock_post.call_args.kwargs["json"]) - assert mock_post.call_args.kwargs["json"] == expected_request_body - - @pytest.mark.parametrize( "model, expected_url", [ @@ -1298,20 +1239,3 @@ def test_vertex_embedding_url(model, expected_url): assert url == expected_url assert endpoint == "predict" - - -from base_llm_unit_tests import BaseLLMChatTest - - -class TestVertexGemini(BaseLLMChatTest): - def get_base_completion_call_args(self) -> dict: - return {"model": "gemini/gemini-1.5-flash"} - - def test_tool_call_no_arguments(self, tool_call_no_arguments): - """Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833""" - from litellm.llms.prompt_templates.factory import ( - convert_to_gemini_tool_call_invoke, - ) - - result = convert_to_gemini_tool_call_invoke(tool_call_no_arguments) - print(result) diff --git a/tests/local_testing/test_alangfuse.py b/tests/local_testing/test_alangfuse.py index 8c69f567b..1728b8feb 100644 --- a/tests/local_testing/test_alangfuse.py +++ b/tests/local_testing/test_alangfuse.py @@ -12,6 +12,7 @@ sys.path.insert(0, os.path.abspath("../..")) import litellm from litellm import completion +from litellm.caching import InMemoryCache litellm.num_retries = 3 litellm.success_callback = ["langfuse"] @@ -29,15 +30,20 @@ def langfuse_client(): f"{os.environ['LANGFUSE_PUBLIC_KEY']}-{os.environ['LANGFUSE_SECRET_KEY']}" ) # use a in memory langfuse client for testing, RAM util on ci/cd gets too high when we init many langfuse clients - if _langfuse_cache_key in litellm.in_memory_llm_clients_cache: - langfuse_client = litellm.in_memory_llm_clients_cache[_langfuse_cache_key] + + _cached_client = litellm.in_memory_llm_clients_cache.get_cache(_langfuse_cache_key) + if _cached_client: + langfuse_client = _cached_client else: langfuse_client = langfuse.Langfuse( public_key=os.environ["LANGFUSE_PUBLIC_KEY"], secret_key=os.environ["LANGFUSE_SECRET_KEY"], - host=None, + host="https://us.cloud.langfuse.com", + ) + litellm.in_memory_llm_clients_cache.set_cache( + key=_langfuse_cache_key, + value=langfuse_client, ) - litellm.in_memory_llm_clients_cache[_langfuse_cache_key] = langfuse_client print("NEW LANGFUSE CLIENT") @@ -262,7 +268,7 @@ audio_file = open(file_path, "rb") @pytest.mark.asyncio -@pytest.mark.flaky(retries=12, delay=2) +@pytest.mark.flaky(retries=4, delay=2) async def test_langfuse_logging_audio_transcriptions(langfuse_client): """ Test that creates a trace with masked input and output @@ -281,9 +287,10 @@ async def test_langfuse_logging_audio_transcriptions(langfuse_client): ) langfuse_client.flush() - await asyncio.sleep(5) + await asyncio.sleep(20) # get trace with _unique_trace_name + print("lookiing up trace", _unique_trace_name) trace = langfuse_client.get_trace(id=_unique_trace_name) generations = list( reversed(langfuse_client.get_generations(trace_id=_unique_trace_name).data) @@ -297,7 +304,6 @@ async def test_langfuse_logging_audio_transcriptions(langfuse_client): @pytest.mark.asyncio -@pytest.mark.flaky(retries=12, delay=2) async def test_langfuse_masked_input_output(langfuse_client): """ Test that creates a trace with masked input and output @@ -319,34 +325,25 @@ async def test_langfuse_masked_input_output(langfuse_client): mock_response="This is a test response", ) print(response) - expected_input = ( - "redacted-by-litellm" - if mask_value - else {"messages": [{"content": "This is a test", "role": "user"}]} - ) + expected_input = "redacted-by-litellm" if mask_value else "This is a test" expected_output = ( - "redacted-by-litellm" - if mask_value - else { - "content": "This is a test response", - "role": "assistant", - "function_call": None, - "tool_calls": None, - } + "redacted-by-litellm" if mask_value else "This is a test response" ) langfuse_client.flush() - await asyncio.sleep(2) + await asyncio.sleep(30) # get trace with _unique_trace_name trace = langfuse_client.get_trace(id=_unique_trace_name) + print("trace_from_langfuse", trace) generations = list( reversed(langfuse_client.get_generations(trace_id=_unique_trace_name).data) ) - assert trace.input == expected_input - assert trace.output == expected_output - assert generations[0].input == expected_input - assert generations[0].output == expected_output + assert expected_input in str(trace.input) + assert expected_output in str(trace.output) + if len(generations) > 0: + assert expected_input in str(generations[0].input) + assert expected_output in str(generations[0].output) @pytest.mark.asyncio @@ -442,7 +439,7 @@ async def test_aaalangfuse_logging_metadata(langfuse_client): try: trace = langfuse_client.get_trace(id=trace_id) except Exception as e: - if "Trace not found within authorized project" in str(e): + if "not found within authorized project" in str(e): print(f"Trace {trace_id} not found") continue assert trace.id == trace_id diff --git a/tests/local_testing/test_auth_checks.py b/tests/local_testing/test_auth_checks.py index f1683a153..67b5cf11d 100644 --- a/tests/local_testing/test_auth_checks.py +++ b/tests/local_testing/test_auth_checks.py @@ -95,3 +95,107 @@ async def test_handle_failed_db_connection(): print("_handle_failed_db_connection_for_get_key_object got exception", exc_info) assert str(exc_info.value) == "Failed to connect to DB" + + +@pytest.mark.parametrize( + "model, expect_to_work", + [("openai/gpt-4o-mini", True), ("openai/gpt-4o", False)], +) +@pytest.mark.asyncio +async def test_can_key_call_model(model, expect_to_work): + """ + If wildcard model + specific model is used, choose the specific model settings + """ + from litellm.proxy.auth.auth_checks import can_key_call_model + from fastapi import HTTPException + + llm_model_list = [ + { + "model_name": "openai/*", + "litellm_params": { + "model": "openai/*", + "api_key": "test-api-key", + }, + "model_info": { + "id": "e6e7006f83029df40ebc02ddd068890253f4cd3092bcb203d3d8e6f6f606f30f", + "db_model": False, + "access_groups": ["public-openai-models"], + }, + }, + { + "model_name": "openai/gpt-4o", + "litellm_params": { + "model": "openai/gpt-4o", + "api_key": "test-api-key", + }, + "model_info": { + "id": "0cfcd87f2cb12a783a466888d05c6c89df66db23e01cecd75ec0b83aed73c9ad", + "db_model": False, + "access_groups": ["private-openai-models"], + }, + }, + ] + router = litellm.Router(model_list=llm_model_list) + args = { + "model": model, + "llm_model_list": llm_model_list, + "valid_token": UserAPIKeyAuth( + models=["public-openai-models"], + ), + "llm_router": router, + } + if expect_to_work: + await can_key_call_model(**args) + else: + with pytest.raises(Exception) as e: + await can_key_call_model(**args) + + print(e) + + +@pytest.mark.parametrize( + "model, expect_to_work", + [("openai/gpt-4o", False), ("openai/gpt-4o-mini", True)], +) +@pytest.mark.asyncio +async def test_can_team_call_model(model, expect_to_work): + from litellm.proxy.auth.auth_checks import model_in_access_group + from fastapi import HTTPException + + llm_model_list = [ + { + "model_name": "openai/*", + "litellm_params": { + "model": "openai/*", + "api_key": "test-api-key", + }, + "model_info": { + "id": "e6e7006f83029df40ebc02ddd068890253f4cd3092bcb203d3d8e6f6f606f30f", + "db_model": False, + "access_groups": ["public-openai-models"], + }, + }, + { + "model_name": "openai/gpt-4o", + "litellm_params": { + "model": "openai/gpt-4o", + "api_key": "test-api-key", + }, + "model_info": { + "id": "0cfcd87f2cb12a783a466888d05c6c89df66db23e01cecd75ec0b83aed73c9ad", + "db_model": False, + "access_groups": ["private-openai-models"], + }, + }, + ] + router = litellm.Router(model_list=llm_model_list) + + args = { + "model": model, + "team_models": ["public-openai-models"], + "llm_router": router, + } + if expect_to_work: + assert model_in_access_group(**args) + else: + assert not model_in_access_group(**args) diff --git a/tests/local_testing/test_azure_openai.py b/tests/local_testing/test_azure_openai.py index e82419c17..fa4226b14 100644 --- a/tests/local_testing/test_azure_openai.py +++ b/tests/local_testing/test_azure_openai.py @@ -33,7 +33,7 @@ from litellm.router import Router @pytest.mark.asyncio() @pytest.mark.respx() -async def test_azure_tenant_id_auth(respx_mock: MockRouter): +async def test_aaaaazure_tenant_id_auth(respx_mock: MockRouter): """ Tests when we set tenant_id, client_id, client_secret they don't get sent with the request diff --git a/tests/local_testing/test_azure_perf.py b/tests/local_testing/test_azure_perf.py index 8afc59f92..b7d7abd55 100644 --- a/tests/local_testing/test_azure_perf.py +++ b/tests/local_testing/test_azure_perf.py @@ -1,128 +1,128 @@ -#### What this tests #### -# This adds perf testing to the router, to ensure it's never > 50ms slower than the azure-openai sdk. -import sys, os, time, inspect, asyncio, traceback -from datetime import datetime -import pytest +# #### What this tests #### +# # This adds perf testing to the router, to ensure it's never > 50ms slower than the azure-openai sdk. +# import sys, os, time, inspect, asyncio, traceback +# from datetime import datetime +# import pytest -sys.path.insert(0, os.path.abspath("../..")) -import openai, litellm, uuid -from openai import AsyncAzureOpenAI +# sys.path.insert(0, os.path.abspath("../..")) +# import openai, litellm, uuid +# from openai import AsyncAzureOpenAI -client = AsyncAzureOpenAI( - api_key=os.getenv("AZURE_API_KEY"), - azure_endpoint=os.getenv("AZURE_API_BASE"), # type: ignore - api_version=os.getenv("AZURE_API_VERSION"), -) +# client = AsyncAzureOpenAI( +# api_key=os.getenv("AZURE_API_KEY"), +# azure_endpoint=os.getenv("AZURE_API_BASE"), # type: ignore +# api_version=os.getenv("AZURE_API_VERSION"), +# ) -model_list = [ - { - "model_name": "azure-test", - "litellm_params": { - "model": "azure/chatgpt-v-2", - "api_key": os.getenv("AZURE_API_KEY"), - "api_base": os.getenv("AZURE_API_BASE"), - "api_version": os.getenv("AZURE_API_VERSION"), - }, - } -] +# model_list = [ +# { +# "model_name": "azure-test", +# "litellm_params": { +# "model": "azure/chatgpt-v-2", +# "api_key": os.getenv("AZURE_API_KEY"), +# "api_base": os.getenv("AZURE_API_BASE"), +# "api_version": os.getenv("AZURE_API_VERSION"), +# }, +# } +# ] -router = litellm.Router(model_list=model_list) # type: ignore +# router = litellm.Router(model_list=model_list) # type: ignore -async def _openai_completion(): - try: - start_time = time.time() - response = await client.chat.completions.create( - model="chatgpt-v-2", - messages=[{"role": "user", "content": f"This is a test: {uuid.uuid4()}"}], - stream=True, - ) - time_to_first_token = None - first_token_ts = None - init_chunk = None - async for chunk in response: - if ( - time_to_first_token is None - and len(chunk.choices) > 0 - and chunk.choices[0].delta.content is not None - ): - first_token_ts = time.time() - time_to_first_token = first_token_ts - start_time - init_chunk = chunk - end_time = time.time() - print( - "OpenAI Call: ", - init_chunk, - start_time, - first_token_ts, - time_to_first_token, - end_time, - ) - return time_to_first_token - except Exception as e: - print(e) - return None +# async def _openai_completion(): +# try: +# start_time = time.time() +# response = await client.chat.completions.create( +# model="chatgpt-v-2", +# messages=[{"role": "user", "content": f"This is a test: {uuid.uuid4()}"}], +# stream=True, +# ) +# time_to_first_token = None +# first_token_ts = None +# init_chunk = None +# async for chunk in response: +# if ( +# time_to_first_token is None +# and len(chunk.choices) > 0 +# and chunk.choices[0].delta.content is not None +# ): +# first_token_ts = time.time() +# time_to_first_token = first_token_ts - start_time +# init_chunk = chunk +# end_time = time.time() +# print( +# "OpenAI Call: ", +# init_chunk, +# start_time, +# first_token_ts, +# time_to_first_token, +# end_time, +# ) +# return time_to_first_token +# except Exception as e: +# print(e) +# return None -async def _router_completion(): - try: - start_time = time.time() - response = await router.acompletion( - model="azure-test", - messages=[{"role": "user", "content": f"This is a test: {uuid.uuid4()}"}], - stream=True, - ) - time_to_first_token = None - first_token_ts = None - init_chunk = None - async for chunk in response: - if ( - time_to_first_token is None - and len(chunk.choices) > 0 - and chunk.choices[0].delta.content is not None - ): - first_token_ts = time.time() - time_to_first_token = first_token_ts - start_time - init_chunk = chunk - end_time = time.time() - print( - "Router Call: ", - init_chunk, - start_time, - first_token_ts, - time_to_first_token, - end_time - first_token_ts, - ) - return time_to_first_token - except Exception as e: - print(e) - return None +# async def _router_completion(): +# try: +# start_time = time.time() +# response = await router.acompletion( +# model="azure-test", +# messages=[{"role": "user", "content": f"This is a test: {uuid.uuid4()}"}], +# stream=True, +# ) +# time_to_first_token = None +# first_token_ts = None +# init_chunk = None +# async for chunk in response: +# if ( +# time_to_first_token is None +# and len(chunk.choices) > 0 +# and chunk.choices[0].delta.content is not None +# ): +# first_token_ts = time.time() +# time_to_first_token = first_token_ts - start_time +# init_chunk = chunk +# end_time = time.time() +# print( +# "Router Call: ", +# init_chunk, +# start_time, +# first_token_ts, +# time_to_first_token, +# end_time - first_token_ts, +# ) +# return time_to_first_token +# except Exception as e: +# print(e) +# return None -async def test_azure_completion_streaming(): - """ - Test azure streaming call - measure on time to first (non-null) token. - """ - n = 3 # Number of concurrent tasks - ## OPENAI AVG. TIME - tasks = [_openai_completion() for _ in range(n)] - chat_completions = await asyncio.gather(*tasks) - successful_completions = [c for c in chat_completions if c is not None] - total_time = 0 - for item in successful_completions: - total_time += item - avg_openai_time = total_time / 3 - ## ROUTER AVG. TIME - tasks = [_router_completion() for _ in range(n)] - chat_completions = await asyncio.gather(*tasks) - successful_completions = [c for c in chat_completions if c is not None] - total_time = 0 - for item in successful_completions: - total_time += item - avg_router_time = total_time / 3 - ## COMPARE - print(f"avg_router_time: {avg_router_time}; avg_openai_time: {avg_openai_time}") - assert avg_router_time < avg_openai_time + 0.5 +# async def test_azure_completion_streaming(): +# """ +# Test azure streaming call - measure on time to first (non-null) token. +# """ +# n = 3 # Number of concurrent tasks +# ## OPENAI AVG. TIME +# tasks = [_openai_completion() for _ in range(n)] +# chat_completions = await asyncio.gather(*tasks) +# successful_completions = [c for c in chat_completions if c is not None] +# total_time = 0 +# for item in successful_completions: +# total_time += item +# avg_openai_time = total_time / 3 +# ## ROUTER AVG. TIME +# tasks = [_router_completion() for _ in range(n)] +# chat_completions = await asyncio.gather(*tasks) +# successful_completions = [c for c in chat_completions if c is not None] +# total_time = 0 +# for item in successful_completions: +# total_time += item +# avg_router_time = total_time / 3 +# ## COMPARE +# print(f"avg_router_time: {avg_router_time}; avg_openai_time: {avg_openai_time}") +# assert avg_router_time < avg_openai_time + 0.5 -# asyncio.run(test_azure_completion_streaming()) +# # asyncio.run(test_azure_completion_streaming()) diff --git a/tests/local_testing/test_caching.py b/tests/local_testing/test_caching.py index 222013a86..08da89172 100644 --- a/tests/local_testing/test_caching.py +++ b/tests/local_testing/test_caching.py @@ -2433,3 +2433,48 @@ async def test_dual_cache_caching_batch_get_cache(): await dc.async_batch_get_cache(keys=["test_key1", "test_key2"]) assert mock_async_get_cache.call_count == 1 + + +@pytest.mark.asyncio +async def test_redis_increment_pipeline(): + """Test Redis increment pipeline functionality""" + try: + from litellm.caching.redis_cache import RedisCache + + litellm.set_verbose = True + redis_cache = RedisCache( + host=os.environ["REDIS_HOST"], + port=os.environ["REDIS_PORT"], + password=os.environ["REDIS_PASSWORD"], + ) + + # Create test increment operations + increment_list = [ + {"key": "test_key1", "increment_value": 1.5, "ttl": 60}, + {"key": "test_key1", "increment_value": 1.1, "ttl": 58}, + {"key": "test_key1", "increment_value": 0.4, "ttl": 55}, + {"key": "test_key2", "increment_value": 2.5, "ttl": 60}, + ] + + # Test pipeline increment + results = await redis_cache.async_increment_pipeline(increment_list) + + # Verify results + assert len(results) == 8 # 4 increment operations + 4 expire operations + + # Verify the values were actually set in Redis + value1 = await redis_cache.async_get_cache("test_key1") + print("result in cache for key=test_key1", value1) + value2 = await redis_cache.async_get_cache("test_key2") + print("result in cache for key=test_key2", value2) + + assert float(value1) == 3.0 + assert float(value2) == 2.5 + + # Clean up + await redis_cache.async_delete_cache("test_key1") + await redis_cache.async_delete_cache("test_key2") + + except Exception as e: + print(f"Error occurred: {str(e)}") + raise e diff --git a/tests/local_testing/test_caching_ssl.py b/tests/local_testing/test_caching_ssl.py index 0825a8537..1b642f767 100644 --- a/tests/local_testing/test_caching_ssl.py +++ b/tests/local_testing/test_caching_ssl.py @@ -99,3 +99,29 @@ def test_caching_router(): # test_caching_router() +@pytest.mark.asyncio +async def test_redis_with_ssl(): + """ + Test connecting to redis connection pool when ssl=None + + + Relevant issue: + User was seeing this error: `TypeError: AbstractConnection.__init__() got an unexpected keyword argument 'ssl'` + """ + from litellm._redis import get_redis_connection_pool, get_redis_async_client + + # Get the connection pool with SSL + # REDIS_HOST_WITH_SSL is just a redis cloud instance with Transport layer security (TLS) enabled + pool = get_redis_connection_pool( + host=os.environ.get("REDIS_HOST_WITH_SSL"), + port=os.environ.get("REDIS_PORT_WITH_SSL"), + password=os.environ.get("REDIS_PASSWORD_WITH_SSL"), + ssl=None, + ) + + # Create Redis client with the pool + redis_client = get_redis_async_client(connection_pool=pool) + + print("pinging redis") + print(await redis_client.ping()) + print("pinged redis") diff --git a/tests/local_testing/test_completion.py b/tests/local_testing/test_completion.py index cf18e3673..f69778e48 100644 --- a/tests/local_testing/test_completion.py +++ b/tests/local_testing/test_completion.py @@ -24,7 +24,7 @@ from litellm import RateLimitError, Timeout, completion, completion_cost, embedd from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.llms.prompt_templates.factory import anthropic_messages_pt -# litellm.num_retries=3 +# litellm.num_retries = 3 litellm.cache = None litellm.success_callback = [] diff --git a/tests/local_testing/test_datadog.py b/tests/local_testing/test_datadog.py deleted file mode 100644 index 990a5b76c..000000000 --- a/tests/local_testing/test_datadog.py +++ /dev/null @@ -1,246 +0,0 @@ -import io -import os -import sys - -sys.path.insert(0, os.path.abspath("../..")) - -import asyncio -import gzip -import json -import logging -import time -from unittest.mock import AsyncMock, patch - -import pytest - -import litellm -from litellm import completion -from litellm._logging import verbose_logger -from litellm.integrations.datadog.types import DatadogPayload - -verbose_logger.setLevel(logging.DEBUG) - - -@pytest.mark.asyncio -async def test_datadog_logging_http_request(): - """ - - Test that the HTTP request is made to Datadog - - sent to the /api/v2/logs endpoint - - the payload is batched - - each element in the payload is a DatadogPayload - - each element in a DatadogPayload.message contains all the valid fields - """ - try: - from litellm.integrations.datadog.datadog import DataDogLogger - - os.environ["DD_SITE"] = "https://fake.datadoghq.com" - os.environ["DD_API_KEY"] = "anything" - dd_logger = DataDogLogger() - - litellm.callbacks = [dd_logger] - - litellm.set_verbose = True - - # Create a mock for the async_client's post method - mock_post = AsyncMock() - mock_post.return_value.status_code = 202 - mock_post.return_value.text = "Accepted" - dd_logger.async_client.post = mock_post - - # Make the completion call - for _ in range(5): - response = await litellm.acompletion( - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "what llm are u"}], - max_tokens=10, - temperature=0.2, - mock_response="Accepted", - ) - print(response) - - # Wait for 5 seconds - await asyncio.sleep(6) - - # Assert that the mock was called - assert mock_post.called, "HTTP request was not made" - - # Get the arguments of the last call - args, kwargs = mock_post.call_args - - print("CAll args and kwargs", args, kwargs) - - # Print the request body - - # You can add more specific assertions here if needed - # For example, checking if the URL is correct - assert kwargs["url"].endswith("/api/v2/logs"), "Incorrect DataDog endpoint" - - body = kwargs["data"] - - # use gzip to unzip the body - with gzip.open(io.BytesIO(body), "rb") as f: - body = f.read().decode("utf-8") - print(body) - - # body is string parse it to dict - body = json.loads(body) - print(body) - - assert len(body) == 5 # 5 logs should be sent to DataDog - - # Assert that the first element in body has the expected fields and shape - assert isinstance(body[0], dict), "First element in body should be a dictionary" - - # Get the expected fields and their types from DatadogPayload - expected_fields = DatadogPayload.__annotations__ - # Assert that all elements in body have the fields of DatadogPayload with correct types - for log in body: - assert isinstance(log, dict), "Each log should be a dictionary" - for field, expected_type in expected_fields.items(): - assert field in log, f"Field '{field}' is missing from the log" - assert isinstance( - log[field], expected_type - ), f"Field '{field}' has incorrect type. Expected {expected_type}, got {type(log[field])}" - - # Additional assertion to ensure no extra fields are present - for log in body: - assert set(log.keys()) == set( - expected_fields.keys() - ), f"Log contains unexpected fields: {set(log.keys()) - set(expected_fields.keys())}" - - # Parse the 'message' field as JSON and check its structure - message = json.loads(body[0]["message"]) - - expected_message_fields = [ - "id", - "call_type", - "cache_hit", - "start_time", - "end_time", - "response_time", - "model", - "user", - "model_parameters", - "spend", - "messages", - "response", - "usage", - "metadata", - ] - - for field in expected_message_fields: - assert field in message, f"Field '{field}' is missing from the message" - - # Check specific fields - assert message["call_type"] == "acompletion" - assert message["model"] == "gpt-3.5-turbo" - assert isinstance(message["model_parameters"], dict) - assert "temperature" in message["model_parameters"] - assert "max_tokens" in message["model_parameters"] - assert isinstance(message["response"], dict) - assert isinstance(message["usage"], dict) - assert isinstance(message["metadata"], dict) - - except Exception as e: - pytest.fail(f"Test failed with exception: {str(e)}") - - -@pytest.mark.asyncio -async def test_datadog_log_redis_failures(): - """ - Test that poorly configured Redis is logged as Warning on DataDog - """ - try: - from litellm.caching.caching import Cache - from litellm.integrations.datadog.datadog import DataDogLogger - - litellm.cache = Cache( - type="redis", host="badhost", port="6379", password="badpassword" - ) - - os.environ["DD_SITE"] = "https://fake.datadoghq.com" - os.environ["DD_API_KEY"] = "anything" - dd_logger = DataDogLogger() - - litellm.callbacks = [dd_logger] - litellm.service_callback = ["datadog"] - - litellm.set_verbose = True - - # Create a mock for the async_client's post method - mock_post = AsyncMock() - mock_post.return_value.status_code = 202 - mock_post.return_value.text = "Accepted" - dd_logger.async_client.post = mock_post - - # Make the completion call - for _ in range(3): - response = await litellm.acompletion( - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "what llm are u"}], - max_tokens=10, - temperature=0.2, - mock_response="Accepted", - ) - print(response) - - # Wait for 5 seconds - await asyncio.sleep(6) - - # Assert that the mock was called - assert mock_post.called, "HTTP request was not made" - - # Get the arguments of the last call - args, kwargs = mock_post.call_args - print("CAll args and kwargs", args, kwargs) - - # For example, checking if the URL is correct - assert kwargs["url"].endswith("/api/v2/logs"), "Incorrect DataDog endpoint" - - body = kwargs["data"] - - # use gzip to unzip the body - with gzip.open(io.BytesIO(body), "rb") as f: - body = f.read().decode("utf-8") - print(body) - - # body is string parse it to dict - body = json.loads(body) - print(body) - - failure_events = [log for log in body if log["status"] == "warning"] - assert len(failure_events) > 0, "No failure events logged" - - print("ALL FAILURE/WARN EVENTS", failure_events) - - for event in failure_events: - message = json.loads(event["message"]) - assert ( - event["status"] == "warning" - ), f"Event status is not 'warning': {event['status']}" - assert ( - message["service"] == "redis" - ), f"Service is not 'redis': {message['service']}" - assert "error" in message, "No 'error' field in the message" - assert message["error"], "Error field is empty" - except Exception as e: - pytest.fail(f"Test failed with exception: {str(e)}") - - -@pytest.mark.asyncio -@pytest.mark.skip(reason="local-only test, to test if everything works fine.") -async def test_datadog_logging(): - try: - litellm.success_callback = ["datadog"] - litellm.set_verbose = True - response = await litellm.acompletion( - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "what llm are u"}], - max_tokens=10, - temperature=0.2, - ) - print(response) - - await asyncio.sleep(5) - except Exception as e: - print(e) diff --git a/tests/local_testing/test_embedding.py b/tests/local_testing/test_embedding.py index d7988e690..096dfc419 100644 --- a/tests/local_testing/test_embedding.py +++ b/tests/local_testing/test_embedding.py @@ -1080,3 +1080,34 @@ def test_cohere_img_embeddings(input, input_type): assert response.usage.prompt_tokens_details.image_tokens > 0 else: assert response.usage.prompt_tokens_details.text_tokens > 0 + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +async def test_embedding_with_extra_headers(sync_mode): + + input = ["hello world"] + from litellm.llms.custom_httpx.http_handler import HTTPHandler, AsyncHTTPHandler + + if sync_mode: + client = HTTPHandler() + else: + client = AsyncHTTPHandler() + + data = { + "model": "cohere/embed-english-v3.0", + "input": input, + "extra_headers": {"my-test-param": "hello-world"}, + "client": client, + } + with patch.object(client, "post") as mock_post: + try: + if sync_mode: + embedding(**data) + else: + await litellm.aembedding(**data) + except Exception as e: + print(e) + + mock_post.assert_called_once() + assert "my-test-param" in mock_post.call_args.kwargs["headers"] diff --git a/tests/local_testing/test_exceptions.py b/tests/local_testing/test_exceptions.py index 67c36928f..18f732378 100644 --- a/tests/local_testing/test_exceptions.py +++ b/tests/local_testing/test_exceptions.py @@ -1146,7 +1146,9 @@ async def test_exception_with_headers_httpx( except litellm.RateLimitError as e: exception_raised = True - assert e.litellm_response_headers is not None + assert ( + e.litellm_response_headers is not None + ), "litellm_response_headers is None" print("e.litellm_response_headers", e.litellm_response_headers) assert int(e.litellm_response_headers["retry-after"]) == cooldown_time diff --git a/tests/local_testing/test_get_model_info.py b/tests/local_testing/test_get_model_info.py index 11506ed3d..dc77f8390 100644 --- a/tests/local_testing/test_get_model_info.py +++ b/tests/local_testing/test_get_model_info.py @@ -102,3 +102,17 @@ def test_get_model_info_ollama_chat(): print(mock_client.call_args.kwargs) assert mock_client.call_args.kwargs["json"]["name"] == "mistral" + + +def test_get_model_info_gemini(): + """ + Tests if ALL gemini models have 'tpm' and 'rpm' in the model info + """ + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + + model_map = litellm.model_cost + for model, info in model_map.items(): + if model.startswith("gemini/") and not "gemma" in model: + assert info.get("tpm") is not None, f"{model} does not have tpm" + assert info.get("rpm") is not None, f"{model} does not have rpm" diff --git a/tests/local_testing/test_http_parsing_utils.py b/tests/local_testing/test_http_parsing_utils.py new file mode 100644 index 000000000..2c6956c79 --- /dev/null +++ b/tests/local_testing/test_http_parsing_utils.py @@ -0,0 +1,79 @@ +import pytest +from fastapi import Request +from fastapi.testclient import TestClient +from starlette.datastructures import Headers +from starlette.requests import HTTPConnection +import os +import sys + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path + +from litellm.proxy.common_utils.http_parsing_utils import _read_request_body + + +@pytest.mark.asyncio +async def test_read_request_body_valid_json(): + """Test the function with a valid JSON payload.""" + + class MockRequest: + async def body(self): + return b'{"key": "value"}' + + request = MockRequest() + result = await _read_request_body(request) + assert result == {"key": "value"} + + +@pytest.mark.asyncio +async def test_read_request_body_empty_body(): + """Test the function with an empty body.""" + + class MockRequest: + async def body(self): + return b"" + + request = MockRequest() + result = await _read_request_body(request) + assert result == {} + + +@pytest.mark.asyncio +async def test_read_request_body_invalid_json(): + """Test the function with an invalid JSON payload.""" + + class MockRequest: + async def body(self): + return b'{"key": value}' # Missing quotes around `value` + + request = MockRequest() + result = await _read_request_body(request) + assert result == {} # Should return an empty dict on failure + + +@pytest.mark.asyncio +async def test_read_request_body_large_payload(): + """Test the function with a very large payload.""" + large_payload = '{"key":' + '"a"' * 10**6 + "}" # Large payload + + class MockRequest: + async def body(self): + return large_payload.encode() + + request = MockRequest() + result = await _read_request_body(request) + assert result == {} # Large payloads could trigger errors, so validate behavior + + +@pytest.mark.asyncio +async def test_read_request_body_unexpected_error(): + """Test the function when an unexpected error occurs.""" + + class MockRequest: + async def body(self): + raise ValueError("Unexpected error") + + request = MockRequest() + result = await _read_request_body(request) + assert result == {} # Ensure fallback behavior diff --git a/tests/local_testing/test_pass_through_endpoints.py b/tests/local_testing/test_pass_through_endpoints.py index b069dc0ef..7e9dfcfc7 100644 --- a/tests/local_testing/test_pass_through_endpoints.py +++ b/tests/local_testing/test_pass_through_endpoints.py @@ -261,7 +261,7 @@ async def test_aaapass_through_endpoint_pass_through_keys_langfuse( pass_through_endpoints = [ { "path": "/api/public/ingestion", - "target": "https://cloud.langfuse.com/api/public/ingestion", + "target": "https://us.cloud.langfuse.com/api/public/ingestion", "auth": auth, "custom_auth_parser": "langfuse", "headers": { diff --git a/tests/local_testing/test_rerank.py b/tests/local_testing/test_rerank.py index c5ed1efe5..5fca6f135 100644 --- a/tests/local_testing/test_rerank.py +++ b/tests/local_testing/test_rerank.py @@ -215,7 +215,10 @@ async def test_rerank_custom_api_base(): args_to_api = kwargs["json"] print("Arguments passed to API=", args_to_api) print("url = ", _url) - assert _url[0] == "https://exampleopenaiendpoint-production.up.railway.app/" + assert ( + _url[0] + == "https://exampleopenaiendpoint-production.up.railway.app/v1/rerank" + ) assert args_to_api == expected_payload assert response.id is not None assert response.results is not None @@ -258,3 +261,32 @@ async def test_rerank_custom_callbacks(): assert custom_logger.kwargs.get("response_cost") > 0.0 assert custom_logger.response_obj is not None assert custom_logger.response_obj.results is not None + + +def test_complete_base_url_cohere(): + from litellm.llms.custom_httpx.http_handler import HTTPHandler + + client = HTTPHandler() + litellm.api_base = "http://localhost:4000" + litellm.set_verbose = True + + text = "Hello there!" + list_texts = ["Hello there!", "How are you?", "How do you do?"] + + rerank_model = "rerank-multilingual-v3.0" + + with patch.object(client, "post") as mock_post: + try: + litellm.rerank( + model=rerank_model, + query=text, + documents=list_texts, + custom_llm_provider="cohere", + client=client, + ) + except Exception as e: + print(e) + + print("mock_post.call_args", mock_post.call_args) + mock_post.assert_called_once() + assert "http://localhost:4000/v1/rerank" in mock_post.call_args.kwargs["url"] diff --git a/tests/local_testing/test_router.py b/tests/local_testing/test_router.py index 20867e766..7b53d42db 100644 --- a/tests/local_testing/test_router.py +++ b/tests/local_testing/test_router.py @@ -2115,10 +2115,14 @@ def test_router_get_model_info(model, base_model, llm_provider): assert deployment is not None if llm_provider == "openai" or (base_model is not None and llm_provider == "azure"): - router.get_router_model_info(deployment=deployment.to_json()) + router.get_router_model_info( + deployment=deployment.to_json(), received_model_name=model + ) else: try: - router.get_router_model_info(deployment=deployment.to_json()) + router.get_router_model_info( + deployment=deployment.to_json(), received_model_name=model + ) pytest.fail("Expected this to raise model not mapped error") except Exception as e: if "This model isn't mapped yet" in str(e): diff --git a/tests/local_testing/test_router_init.py b/tests/local_testing/test_router_init.py index 3733af252..9b4e12f12 100644 --- a/tests/local_testing/test_router_init.py +++ b/tests/local_testing/test_router_init.py @@ -536,7 +536,7 @@ def test_init_clients_azure_command_r_plus(): @pytest.mark.asyncio -async def test_text_completion_with_organization(): +async def test_aaaaatext_completion_with_organization(): try: print("Testing Text OpenAI with organization") model_list = [ diff --git a/tests/local_testing/test_router_provider_budgets.py b/tests/local_testing/test_router_provider_budgets.py index 46b9ee29e..430550632 100644 --- a/tests/local_testing/test_router_provider_budgets.py +++ b/tests/local_testing/test_router_provider_budgets.py @@ -17,7 +17,7 @@ from litellm.types.router import ( ProviderBudgetConfigType, ProviderBudgetInfo, ) -from litellm.caching.caching import DualCache +from litellm.caching.caching import DualCache, RedisCache import logging from litellm._logging import verbose_router_logger import litellm @@ -25,6 +25,27 @@ import litellm verbose_router_logger.setLevel(logging.DEBUG) +def cleanup_redis(): + """Cleanup Redis cache before each test""" + try: + import redis + + print("cleaning up redis..") + + redis_client = redis.Redis( + host=os.getenv("REDIS_HOST"), + port=int(os.getenv("REDIS_PORT")), + password=os.getenv("REDIS_PASSWORD"), + ) + print("scan iter result", redis_client.scan_iter("provider_spend:*")) + # Delete all provider spend keys + for key in redis_client.scan_iter("provider_spend:*"): + print("deleting key", key) + redis_client.delete(key) + except Exception as e: + print(f"Error cleaning up Redis: {str(e)}") + + @pytest.mark.asyncio async def test_provider_budgets_e2e_test(): """ @@ -34,6 +55,8 @@ async def test_provider_budgets_e2e_test(): - Next 3 requests all go to Azure """ + cleanup_redis() + # Modify for test provider_budget_config: ProviderBudgetConfigType = { "openai": ProviderBudgetInfo(time_period="1d", budget_limit=0.000000000001), "azure": ProviderBudgetInfo(time_period="1d", budget_limit=100), @@ -71,7 +94,7 @@ async def test_provider_budgets_e2e_test(): ) print(response) - await asyncio.sleep(0.5) + await asyncio.sleep(2.5) for _ in range(3): response = await router.acompletion( @@ -94,6 +117,7 @@ async def test_provider_budgets_e2e_test_expect_to_fail(): - first request passes, all subsequent requests fail """ + cleanup_redis() # Note: We intentionally use a dictionary with string keys for budget_limit and time_period # we want to test that the router can handle type conversion, since the proxy config yaml passes these values as a dictionary @@ -125,7 +149,7 @@ async def test_provider_budgets_e2e_test_expect_to_fail(): ) print(response) - await asyncio.sleep(0.5) + await asyncio.sleep(2.5) for _ in range(3): with pytest.raises(Exception) as exc_info: @@ -142,28 +166,13 @@ async def test_provider_budgets_e2e_test_expect_to_fail(): assert "Exceeded budget for provider" in str(exc_info.value) -def test_get_ttl_seconds(): - """ - Test the get_ttl_seconds helper method" - - """ - provider_budget = ProviderBudgetLimiting( - router_cache=DualCache(), provider_budget_config={} - ) - - assert provider_budget.get_ttl_seconds("1d") == 86400 # 1 day in seconds - assert provider_budget.get_ttl_seconds("7d") == 604800 # 7 days in seconds - assert provider_budget.get_ttl_seconds("30d") == 2592000 # 30 days in seconds - - with pytest.raises(ValueError, match="Unsupported time period format"): - provider_budget.get_ttl_seconds("1h") - - -def test_get_llm_provider_for_deployment(): +@pytest.mark.asyncio +async def test_get_llm_provider_for_deployment(): """ Test the _get_llm_provider_for_deployment helper method """ + cleanup_redis() provider_budget = ProviderBudgetLimiting( router_cache=DualCache(), provider_budget_config={} ) @@ -189,11 +198,13 @@ def test_get_llm_provider_for_deployment(): assert provider_budget._get_llm_provider_for_deployment(unknown_deployment) is None -def test_get_budget_config_for_provider(): +@pytest.mark.asyncio +async def test_get_budget_config_for_provider(): """ Test the _get_budget_config_for_provider helper method """ + cleanup_redis() config = { "openai": ProviderBudgetInfo(time_period="1d", budget_limit=100), "anthropic": ProviderBudgetInfo(time_period="7d", budget_limit=500), @@ -223,6 +234,7 @@ async def test_prometheus_metric_tracking(): """ Test that the Prometheus metric for provider budget is tracked correctly """ + cleanup_redis() from unittest.mock import MagicMock from litellm.integrations.prometheus import PrometheusLogger @@ -280,7 +292,187 @@ async def test_prometheus_metric_tracking(): except Exception as e: print("error", e) - await asyncio.sleep(0.5) + await asyncio.sleep(2.5) # Verify the mock was called correctly mock_prometheus.track_provider_remaining_budget.assert_called_once() + + +@pytest.mark.asyncio +async def test_handle_new_budget_window(): + """ + Test _handle_new_budget_window helper method + + Current + """ + cleanup_redis() + provider_budget = ProviderBudgetLimiting( + router_cache=DualCache(), provider_budget_config={} + ) + + spend_key = "provider_spend:openai:7d" + start_time_key = "provider_budget_start_time:openai" + current_time = 1000.0 + response_cost = 0.5 + ttl_seconds = 86400 # 1 day + + # Test handling new budget window + new_start_time = await provider_budget._handle_new_budget_window( + spend_key=spend_key, + start_time_key=start_time_key, + current_time=current_time, + response_cost=response_cost, + ttl_seconds=ttl_seconds, + ) + + assert new_start_time == current_time + + # Verify the spend was set correctly + spend = await provider_budget.router_cache.async_get_cache(spend_key) + print("spend in cache for key", spend_key, "is", spend) + assert float(spend) == response_cost + + # Verify start time was set correctly + start_time = await provider_budget.router_cache.async_get_cache(start_time_key) + print("start time in cache for key", start_time_key, "is", start_time) + assert float(start_time) == current_time + + +@pytest.mark.asyncio +async def test_get_or_set_budget_start_time(): + """ + Test _get_or_set_budget_start_time helper method + + scenario 1: no existing start time in cache, should return current time + scenario 2: existing start time in cache, should return existing start time + """ + cleanup_redis() + provider_budget = ProviderBudgetLimiting( + router_cache=DualCache(), provider_budget_config={} + ) + + start_time_key = "test_start_time" + current_time = 1000.0 + ttl_seconds = 86400 # 1 day + + # When there is no existing start time, we should set it to the current time + start_time = await provider_budget._get_or_set_budget_start_time( + start_time_key=start_time_key, + current_time=current_time, + ttl_seconds=ttl_seconds, + ) + print("budget start time when no existing start time is in cache", start_time) + assert start_time == current_time + + # When there is an existing start time, we should return it even if the current time is later + new_current_time = 2000.0 + existing_start_time = await provider_budget._get_or_set_budget_start_time( + start_time_key=start_time_key, + current_time=new_current_time, + ttl_seconds=ttl_seconds, + ) + print( + "budget start time when existing start time is in cache, but current time is later", + existing_start_time, + ) + assert existing_start_time == current_time # Should return the original start time + + +@pytest.mark.asyncio +async def test_increment_spend_in_current_window(): + """ + Test _increment_spend_in_current_window helper method + + Expected behavior: + - Increment the spend in memory cache + - Queue the increment operation to Redis + """ + cleanup_redis() + provider_budget = ProviderBudgetLimiting( + router_cache=DualCache(), provider_budget_config={} + ) + + spend_key = "provider_spend:openai:1d" + response_cost = 0.5 + ttl = 86400 # 1 day + + # Set initial spend + await provider_budget.router_cache.async_set_cache( + key=spend_key, value=1.0, ttl=ttl + ) + + # Test incrementing spend + await provider_budget._increment_spend_in_current_window( + spend_key=spend_key, + response_cost=response_cost, + ttl=ttl, + ) + + # Verify the spend was incremented correctly in memory + spend = await provider_budget.router_cache.async_get_cache(spend_key) + assert float(spend) == 1.5 + + # Verify the increment operation was queued for Redis + print( + "redis_increment_operation_queue", + provider_budget.redis_increment_operation_queue, + ) + assert len(provider_budget.redis_increment_operation_queue) == 1 + queued_op = provider_budget.redis_increment_operation_queue[0] + assert queued_op["key"] == spend_key + assert queued_op["increment_value"] == response_cost + assert queued_op["ttl"] == ttl + + +@pytest.mark.asyncio +async def test_sync_in_memory_spend_with_redis(): + """ + Test _sync_in_memory_spend_with_redis helper method + + Expected behavior: + - Push all provider spend increments to Redis + - Fetch all current provider spend from Redis to update in-memory cache + """ + cleanup_redis() + provider_budget_config = { + "openai": ProviderBudgetInfo(time_period="1d", budget_limit=100), + "anthropic": ProviderBudgetInfo(time_period="1d", budget_limit=200), + } + + provider_budget = ProviderBudgetLimiting( + router_cache=DualCache( + redis_cache=RedisCache( + host=os.getenv("REDIS_HOST"), + port=int(os.getenv("REDIS_PORT")), + password=os.getenv("REDIS_PASSWORD"), + ) + ), + provider_budget_config=provider_budget_config, + ) + + # Set some values in Redis + spend_key_openai = "provider_spend:openai:1d" + spend_key_anthropic = "provider_spend:anthropic:1d" + + await provider_budget.router_cache.redis_cache.async_set_cache( + key=spend_key_openai, value=50.0 + ) + await provider_budget.router_cache.redis_cache.async_set_cache( + key=spend_key_anthropic, value=75.0 + ) + + # Test syncing with Redis + await provider_budget._sync_in_memory_spend_with_redis() + + # Verify in-memory cache was updated + openai_spend = await provider_budget.router_cache.in_memory_cache.async_get_cache( + spend_key_openai + ) + anthropic_spend = ( + await provider_budget.router_cache.in_memory_cache.async_get_cache( + spend_key_anthropic + ) + ) + + assert float(openai_spend) == 50.0 + assert float(anthropic_spend) == 75.0 diff --git a/tests/local_testing/test_router_utils.py b/tests/local_testing/test_router_utils.py index d266cfbd9..b3f3437c4 100644 --- a/tests/local_testing/test_router_utils.py +++ b/tests/local_testing/test_router_utils.py @@ -174,3 +174,185 @@ async def test_update_kwargs_before_fallbacks(call_type): print(mock_client.call_args.kwargs) assert mock_client.call_args.kwargs["litellm_trace_id"] is not None + + +def test_router_get_model_info_wildcard_routes(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + router = Router( + model_list=[ + { + "model_name": "gemini/*", + "litellm_params": {"model": "gemini/*"}, + "model_info": {"id": 1}, + }, + ] + ) + model_info = router.get_router_model_info( + deployment=None, received_model_name="gemini/gemini-1.5-flash", id="1" + ) + print(model_info) + assert model_info is not None + assert model_info["tpm"] is not None + assert model_info["rpm"] is not None + + +@pytest.mark.asyncio +async def test_router_get_model_group_usage_wildcard_routes(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + router = Router( + model_list=[ + { + "model_name": "gemini/*", + "litellm_params": {"model": "gemini/*"}, + "model_info": {"id": 1}, + }, + ] + ) + + resp = await router.acompletion( + model="gemini/gemini-1.5-flash", + messages=[{"role": "user", "content": "Hello, how are you?"}], + mock_response="Hello, I'm good.", + ) + print(resp) + + await asyncio.sleep(1) + + tpm, rpm = await router.get_model_group_usage(model_group="gemini/gemini-1.5-flash") + + assert tpm is not None, "tpm is None" + assert rpm is not None, "rpm is None" + + +@pytest.mark.asyncio +async def test_call_router_callbacks_on_success(): + router = Router( + model_list=[ + { + "model_name": "gemini/*", + "litellm_params": {"model": "gemini/*"}, + "model_info": {"id": 1}, + }, + ] + ) + + with patch.object( + router.cache, "async_increment_cache", new=AsyncMock() + ) as mock_callback: + await router.acompletion( + model="gemini/gemini-1.5-flash", + messages=[{"role": "user", "content": "Hello, how are you?"}], + mock_response="Hello, I'm good.", + ) + await asyncio.sleep(1) + assert mock_callback.call_count == 2 + + assert ( + mock_callback.call_args_list[0] + .kwargs["key"] + .startswith("global_router:1:gemini/gemini-1.5-flash:tpm") + ) + assert ( + mock_callback.call_args_list[1] + .kwargs["key"] + .startswith("global_router:1:gemini/gemini-1.5-flash:rpm") + ) + + +@pytest.mark.asyncio +async def test_call_router_callbacks_on_failure(): + router = Router( + model_list=[ + { + "model_name": "gemini/*", + "litellm_params": {"model": "gemini/*"}, + "model_info": {"id": 1}, + }, + ] + ) + + with patch.object( + router.cache, "async_increment_cache", new=AsyncMock() + ) as mock_callback: + with pytest.raises(litellm.RateLimitError): + await router.acompletion( + model="gemini/gemini-1.5-flash", + messages=[{"role": "user", "content": "Hello, how are you?"}], + mock_response="litellm.RateLimitError", + num_retries=0, + ) + await asyncio.sleep(1) + print(mock_callback.call_args_list) + assert mock_callback.call_count == 1 + + assert ( + mock_callback.call_args_list[0] + .kwargs["key"] + .startswith("global_router:1:gemini/gemini-1.5-flash:rpm") + ) + + +@pytest.mark.asyncio +async def test_router_model_group_headers(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + from litellm.types.utils import OPENAI_RESPONSE_HEADERS + + router = Router( + model_list=[ + { + "model_name": "gemini/*", + "litellm_params": {"model": "gemini/*"}, + "model_info": {"id": 1}, + } + ] + ) + + for _ in range(2): + resp = await router.acompletion( + model="gemini/gemini-1.5-flash", + messages=[{"role": "user", "content": "Hello, how are you?"}], + mock_response="Hello, I'm good.", + ) + await asyncio.sleep(1) + + assert ( + resp._hidden_params["additional_headers"]["x-litellm-model-group"] + == "gemini/gemini-1.5-flash" + ) + + assert "x-ratelimit-remaining-requests" in resp._hidden_params["additional_headers"] + assert "x-ratelimit-remaining-tokens" in resp._hidden_params["additional_headers"] + + +@pytest.mark.asyncio +async def test_get_remaining_model_group_usage(): + os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" + litellm.model_cost = litellm.get_model_cost_map(url="") + from litellm.types.utils import OPENAI_RESPONSE_HEADERS + + router = Router( + model_list=[ + { + "model_name": "gemini/*", + "litellm_params": {"model": "gemini/*"}, + "model_info": {"id": 1}, + } + ] + ) + for _ in range(2): + await router.acompletion( + model="gemini/gemini-1.5-flash", + messages=[{"role": "user", "content": "Hello, how are you?"}], + mock_response="Hello, I'm good.", + ) + await asyncio.sleep(1) + + remaining_usage = await router.get_remaining_model_group_usage( + model_group="gemini/gemini-1.5-flash" + ) + assert remaining_usage is not None + assert "x-ratelimit-remaining-requests" in remaining_usage + assert "x-ratelimit-remaining-tokens" in remaining_usage diff --git a/tests/local_testing/test_tpm_rpm_routing_v2.py b/tests/local_testing/test_tpm_rpm_routing_v2.py index 61b17d356..3641eecad 100644 --- a/tests/local_testing/test_tpm_rpm_routing_v2.py +++ b/tests/local_testing/test_tpm_rpm_routing_v2.py @@ -506,7 +506,7 @@ async def test_router_caching_ttl(): ) as mock_client: await router.acompletion(model=model, messages=messages) - mock_client.assert_called_once() + # mock_client.assert_called_once() print(f"mock_client.call_args.kwargs: {mock_client.call_args.kwargs}") print(f"mock_client.call_args.args: {mock_client.call_args.args}") diff --git a/tests/local_testing/test_user_api_key_auth.py b/tests/local_testing/test_user_api_key_auth.py index 1a129489c..167809da1 100644 --- a/tests/local_testing/test_user_api_key_auth.py +++ b/tests/local_testing/test_user_api_key_auth.py @@ -415,3 +415,18 @@ def test_allowed_route_inside_route( ) == expected_result ) + + +def test_read_request_body(): + from litellm.proxy.common_utils.http_parsing_utils import _read_request_body + from fastapi import Request + + payload = "()" * 1000000 + request = Request(scope={"type": "http"}) + + async def return_body(): + return payload + + request.body = return_body + result = _read_request_body(request) + assert result is not None diff --git a/tests/local_testing/test_utils.py b/tests/local_testing/test_utils.py index 52946ca30..7c349a658 100644 --- a/tests/local_testing/test_utils.py +++ b/tests/local_testing/test_utils.py @@ -17,7 +17,7 @@ import pytest import litellm from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, headers from litellm.proxy.utils import ( - _duration_in_seconds, + duration_in_seconds, _extract_from_regex, get_last_day_of_month, ) @@ -593,7 +593,7 @@ def test_duration_in_seconds(): duration_until_next_month = next_month - current_time expected_duration = int(duration_until_next_month.total_seconds()) - value = _duration_in_seconds(duration="1mo") + value = duration_in_seconds(duration="1mo") assert value - expected_duration < 2 @@ -1012,3 +1012,23 @@ def test_models_by_provider(): for provider in providers: assert provider in models_by_provider.keys() + + +@pytest.mark.parametrize( + "litellm_params, disable_end_user_cost_tracking, expected_end_user_id", + [ + ({}, False, None), + ({"proxy_server_request": {"body": {"user": "123"}}}, False, "123"), + ({"proxy_server_request": {"body": {"user": "123"}}}, True, None), + ], +) +def test_get_end_user_id_for_cost_tracking( + litellm_params, disable_end_user_cost_tracking, expected_end_user_id +): + from litellm.utils import get_end_user_id_for_cost_tracking + + litellm.disable_end_user_cost_tracking = disable_end_user_cost_tracking + assert ( + get_end_user_id_for_cost_tracking(litellm_params=litellm_params) + == expected_end_user_id + ) diff --git a/tests/logging_callback_tests/test_datadog.py b/tests/logging_callback_tests/test_datadog.py new file mode 100644 index 000000000..53667460e --- /dev/null +++ b/tests/logging_callback_tests/test_datadog.py @@ -0,0 +1,468 @@ +import io +import os +import sys + + +sys.path.insert(0, os.path.abspath("../..")) + +import asyncio +import gzip +import json +import logging +import time +from unittest.mock import AsyncMock, patch + +import pytest + +import litellm +from litellm import completion +from litellm._logging import verbose_logger +from litellm.integrations.datadog.datadog import * +from datetime import datetime, timedelta +from litellm.types.utils import ( + StandardLoggingPayload, + StandardLoggingModelInformation, + StandardLoggingMetadata, + StandardLoggingHiddenParams, +) + +verbose_logger.setLevel(logging.DEBUG) + + +def create_standard_logging_payload() -> StandardLoggingPayload: + return StandardLoggingPayload( + id="test_id", + call_type="completion", + response_cost=0.1, + response_cost_failure_debug_info=None, + status="success", + total_tokens=30, + prompt_tokens=20, + completion_tokens=10, + startTime=1234567890.0, + endTime=1234567891.0, + completionStartTime=1234567890.5, + model_map_information=StandardLoggingModelInformation( + model_map_key="gpt-3.5-turbo", model_map_value=None + ), + model="gpt-3.5-turbo", + model_id="model-123", + model_group="openai-gpt", + api_base="https://api.openai.com", + metadata=StandardLoggingMetadata( + user_api_key_hash="test_hash", + user_api_key_org_id=None, + user_api_key_alias="test_alias", + user_api_key_team_id="test_team", + user_api_key_user_id="test_user", + user_api_key_team_alias="test_team_alias", + spend_logs_metadata=None, + requester_ip_address="127.0.0.1", + requester_metadata=None, + ), + cache_hit=False, + cache_key=None, + saved_cache_cost=0.0, + request_tags=[], + end_user=None, + requester_ip_address="127.0.0.1", + messages=[{"role": "user", "content": "Hello, world!"}], + response={"choices": [{"message": {"content": "Hi there!"}}]}, + error_str=None, + model_parameters={"stream": True}, + hidden_params=StandardLoggingHiddenParams( + model_id="model-123", + cache_key=None, + api_base="https://api.openai.com", + response_cost="0.1", + additional_headers=None, + ), + ) + + +@pytest.mark.asyncio +async def test_create_datadog_logging_payload(): + """Test creating a DataDog logging payload from a standard logging object""" + dd_logger = DataDogLogger() + standard_payload = create_standard_logging_payload() + + # Create mock kwargs with the standard logging object + kwargs = {"standard_logging_object": standard_payload} + + # Test payload creation + dd_payload = dd_logger.create_datadog_logging_payload( + kwargs=kwargs, + response_obj=None, + start_time=datetime.now(), + end_time=datetime.now(), + ) + + # Verify payload structure + assert dd_payload["ddsource"] == os.getenv("DD_SOURCE", "litellm") + assert dd_payload["service"] == "litellm-server" + assert dd_payload["status"] == DataDogStatus.INFO + + # verify the message field == standard_payload + dict_payload = json.loads(dd_payload["message"]) + assert dict_payload == standard_payload + + +@pytest.mark.asyncio +async def test_datadog_failure_logging(): + """Test logging a failure event to DataDog""" + dd_logger = DataDogLogger() + standard_payload = create_standard_logging_payload() + standard_payload["status"] = "failure" # Set status to failure + standard_payload["error_str"] = "Test error" + + kwargs = {"standard_logging_object": standard_payload} + + dd_payload = dd_logger.create_datadog_logging_payload( + kwargs=kwargs, + response_obj=None, + start_time=datetime.now(), + end_time=datetime.now(), + ) + + assert ( + dd_payload["status"] == DataDogStatus.ERROR + ) # Verify failure maps to warning status + + # verify the message field == standard_payload + dict_payload = json.loads(dd_payload["message"]) + assert dict_payload == standard_payload + + # verify error_str is in the message field + assert "error_str" in dict_payload + assert dict_payload["error_str"] == "Test error" + + +@pytest.mark.asyncio +async def test_datadog_logging_http_request(): + """ + - Test that the HTTP request is made to Datadog + - sent to the /api/v2/logs endpoint + - the payload is batched + - each element in the payload is a DatadogPayload + - each element in a DatadogPayload.message contains all the valid fields + """ + try: + from litellm.integrations.datadog.datadog import DataDogLogger + + os.environ["DD_SITE"] = "https://fake.datadoghq.com" + os.environ["DD_API_KEY"] = "anything" + dd_logger = DataDogLogger() + + litellm.callbacks = [dd_logger] + + litellm.set_verbose = True + + # Create a mock for the async_client's post method + mock_post = AsyncMock() + mock_post.return_value.status_code = 202 + mock_post.return_value.text = "Accepted" + dd_logger.async_client.post = mock_post + + # Make the completion call + for _ in range(5): + response = await litellm.acompletion( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "what llm are u"}], + max_tokens=10, + temperature=0.2, + mock_response="Accepted", + ) + print(response) + + # Wait for 5 seconds + await asyncio.sleep(6) + + # Assert that the mock was called + assert mock_post.called, "HTTP request was not made" + + # Get the arguments of the last call + args, kwargs = mock_post.call_args + + print("CAll args and kwargs", args, kwargs) + + # Print the request body + + # You can add more specific assertions here if needed + # For example, checking if the URL is correct + assert kwargs["url"].endswith("/api/v2/logs"), "Incorrect DataDog endpoint" + + body = kwargs["data"] + + # use gzip to unzip the body + with gzip.open(io.BytesIO(body), "rb") as f: + body = f.read().decode("utf-8") + print(body) + + # body is string parse it to dict + body = json.loads(body) + print(body) + + assert len(body) == 5 # 5 logs should be sent to DataDog + + # Assert that the first element in body has the expected fields and shape + assert isinstance(body[0], dict), "First element in body should be a dictionary" + + # Get the expected fields and their types from DatadogPayload + expected_fields = DatadogPayload.__annotations__ + # Assert that all elements in body have the fields of DatadogPayload with correct types + for log in body: + assert isinstance(log, dict), "Each log should be a dictionary" + for field, expected_type in expected_fields.items(): + assert field in log, f"Field '{field}' is missing from the log" + assert isinstance( + log[field], expected_type + ), f"Field '{field}' has incorrect type. Expected {expected_type}, got {type(log[field])}" + + # Additional assertion to ensure no extra fields are present + for log in body: + assert set(log.keys()) == set( + expected_fields.keys() + ), f"Log contains unexpected fields: {set(log.keys()) - set(expected_fields.keys())}" + + # Parse the 'message' field as JSON and check its structure + message = json.loads(body[0]["message"]) + + expected_message_fields = StandardLoggingPayload.__annotations__.keys() + + for field in expected_message_fields: + assert field in message, f"Field '{field}' is missing from the message" + + # Check specific fields + assert message["call_type"] == "acompletion" + assert message["model"] == "gpt-3.5-turbo" + assert isinstance(message["model_parameters"], dict) + assert "temperature" in message["model_parameters"] + assert "max_tokens" in message["model_parameters"] + assert isinstance(message["response"], dict) + assert isinstance(message["metadata"], dict) + + except Exception as e: + pytest.fail(f"Test failed with exception: {str(e)}") + + +@pytest.mark.asyncio +async def test_datadog_log_redis_failures(): + """ + Test that poorly configured Redis is logged as Warning on DataDog + """ + try: + from litellm.caching.caching import Cache + from litellm.integrations.datadog.datadog import DataDogLogger + + litellm.cache = Cache( + type="redis", host="badhost", port="6379", password="badpassword" + ) + + os.environ["DD_SITE"] = "https://fake.datadoghq.com" + os.environ["DD_API_KEY"] = "anything" + dd_logger = DataDogLogger() + + litellm.callbacks = [dd_logger] + litellm.service_callback = ["datadog"] + + litellm.set_verbose = True + + # Create a mock for the async_client's post method + mock_post = AsyncMock() + mock_post.return_value.status_code = 202 + mock_post.return_value.text = "Accepted" + dd_logger.async_client.post = mock_post + + # Make the completion call + for _ in range(3): + response = await litellm.acompletion( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "what llm are u"}], + max_tokens=10, + temperature=0.2, + mock_response="Accepted", + ) + print(response) + + # Wait for 5 seconds + await asyncio.sleep(6) + + # Assert that the mock was called + assert mock_post.called, "HTTP request was not made" + + # Get the arguments of the last call + args, kwargs = mock_post.call_args + print("CAll args and kwargs", args, kwargs) + + # For example, checking if the URL is correct + assert kwargs["url"].endswith("/api/v2/logs"), "Incorrect DataDog endpoint" + + body = kwargs["data"] + + # use gzip to unzip the body + with gzip.open(io.BytesIO(body), "rb") as f: + body = f.read().decode("utf-8") + print(body) + + # body is string parse it to dict + body = json.loads(body) + print(body) + + failure_events = [log for log in body if log["status"] == "warning"] + assert len(failure_events) > 0, "No failure events logged" + + print("ALL FAILURE/WARN EVENTS", failure_events) + + for event in failure_events: + message = json.loads(event["message"]) + assert ( + event["status"] == "warning" + ), f"Event status is not 'warning': {event['status']}" + assert ( + message["service"] == "redis" + ), f"Service is not 'redis': {message['service']}" + assert "error" in message, "No 'error' field in the message" + assert message["error"], "Error field is empty" + except Exception as e: + pytest.fail(f"Test failed with exception: {str(e)}") + + +@pytest.mark.asyncio +@pytest.mark.skip(reason="local-only test, to test if everything works fine.") +async def test_datadog_logging(): + try: + litellm.success_callback = ["datadog"] + litellm.set_verbose = True + response = await litellm.acompletion( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "what llm are u"}], + max_tokens=10, + temperature=0.2, + ) + print(response) + + await asyncio.sleep(5) + except Exception as e: + print(e) + + +@pytest.mark.asyncio +async def test_datadog_post_call_failure_hook(): + """Test logging proxy failures (e.g., authentication errors) to DataDog""" + try: + from litellm.integrations.datadog.datadog import DataDogLogger + + os.environ["DD_SITE"] = "https://fake.datadoghq.com" + os.environ["DD_API_KEY"] = "anything" + dd_logger = DataDogLogger() + + # Create a mock for the async_client's post method + mock_post = AsyncMock() + mock_post.return_value.status_code = 202 + mock_post.return_value.text = "Accepted" + dd_logger.async_client.post = mock_post + + # Create a test exception + class AuthenticationError(Exception): + def __init__(self): + self.status_code = 401 + super().__init__("Invalid API key") + + test_exception = AuthenticationError() + + # Create test request data and user API key dict + request_data = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + } + + user_api_key_dict = UserAPIKeyAuth( + api_key="fake_key", user_id="test_user", team_id="test_team" + ) + + # Call the failure hook + await dd_logger.async_post_call_failure_hook( + request_data=request_data, + original_exception=test_exception, + user_api_key_dict=user_api_key_dict, + ) + + # Wait for the periodic flush + await asyncio.sleep(6) + + # Assert that the mock was called + assert mock_post.called, "HTTP request was not made" + + # Get the arguments of the last call + args, kwargs = mock_post.call_args + + # Verify endpoint + assert kwargs["url"].endswith("/api/v2/logs"), "Incorrect DataDog endpoint" + + # Decode and verify payload + body = kwargs["data"] + with gzip.open(io.BytesIO(body), "rb") as f: + body = f.read().decode("utf-8") + + body = json.loads(body) + assert len(body) == 1, "Expected one log entry" + + log_entry = body[0] + assert log_entry["status"] == "error", "Expected error status" + assert log_entry["service"] == "litellm-server" + + # Verify message content + message = json.loads(log_entry["message"]) + print("logged message", json.dumps(message, indent=2)) + assert message["exception"] == "Invalid API key" + assert message["error_class"] == "AuthenticationError" + assert message["status_code"] == 401 + assert "traceback" in message + assert message["user_api_key_dict"]["api_key"] == "fake_key" + + except Exception as e: + pytest.fail(f"Test failed with exception: {str(e)}") + + +@pytest.mark.asyncio +async def test_datadog_payload_environment_variables(): + """Test that DataDog payload correctly includes environment variables in the payload structure""" + try: + # Set test environment variables + test_env = { + "DD_ENV": "test-env", + "DD_SERVICE": "test-service", + "DD_VERSION": "1.0.0", + "DD_SOURCE": "test-source", + "DD_API_KEY": "fake-key", + "DD_SITE": "datadoghq.com", + } + + with patch.dict(os.environ, test_env): + dd_logger = DataDogLogger() + standard_payload = create_standard_logging_payload() + + # Create the payload + dd_payload = dd_logger.create_datadog_logging_payload( + kwargs={"standard_logging_object": standard_payload}, + response_obj=None, + start_time=datetime.now(), + end_time=datetime.now(), + ) + + print("dd payload=", json.dumps(dd_payload, indent=2)) + + # Verify payload structure and environment variables + assert ( + dd_payload["ddsource"] == "test-source" + ), "Incorrect source in payload" + assert ( + dd_payload["service"] == "test-service" + ), "Incorrect service in payload" + assert ( + dd_payload["ddtags"] + == "env:test-env,service:test-service,version:1.0.0" + ), "Incorrect tags in payload" + + except Exception as e: + pytest.fail(f"Test failed with exception: {str(e)}") diff --git a/tests/logging_callback_tests/test_unit_tests_init_callbacks.py b/tests/logging_callback_tests/test_unit_tests_init_callbacks.py index 38883fa38..15c2118d8 100644 --- a/tests/logging_callback_tests/test_unit_tests_init_callbacks.py +++ b/tests/logging_callback_tests/test_unit_tests_init_callbacks.py @@ -216,3 +216,78 @@ async def test_init_custom_logger_compatible_class_as_callback(): await use_callback_in_llm_call(callback, used_in="success_callback") reset_env_vars() + + +def test_dynamic_logging_global_callback(): + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + from litellm.integrations.custom_logger import CustomLogger + from litellm.types.utils import ModelResponse, Choices, Message, Usage + + cl = CustomLogger() + + litellm_logging = LiteLLMLoggingObj( + model="claude-3-opus-20240229", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="completion", + start_time=datetime.now(), + litellm_call_id="123", + function_id="456", + kwargs={ + "langfuse_public_key": "my-mock-public-key", + "langfuse_secret_key": "my-mock-secret-key", + }, + dynamic_success_callbacks=["langfuse"], + ) + + with patch.object(cl, "log_success_event") as mock_log_success_event: + cl.log_success_event = mock_log_success_event + litellm.success_callback = [cl] + + try: + litellm_logging.success_handler( + result=ModelResponse( + id="chatcmpl-5418737b-ab14-420b-b9c5-b278b6681b70", + created=1732306261, + model="claude-3-opus-20240229", + object="chat.completion", + system_fingerprint=None, + choices=[ + Choices( + finish_reason="stop", + index=0, + message=Message( + content="hello", + role="assistant", + tool_calls=None, + function_call=None, + ), + ) + ], + usage=Usage( + completion_tokens=20, + prompt_tokens=10, + total_tokens=30, + completion_tokens_details=None, + prompt_tokens_details=None, + ), + ), + start_time=datetime.now(), + end_time=datetime.now(), + cache_hit=False, + ) + except Exception as e: + print(f"Error: {e}") + + mock_log_success_event.assert_called_once() + + +def test_get_combined_callback_list(): + from litellm.litellm_core_utils.litellm_logging import get_combined_callback_list + + assert "langfuse" in get_combined_callback_list( + dynamic_success_callbacks=["langfuse"], global_callbacks=["lago"] + ) + assert "lago" in get_combined_callback_list( + dynamic_success_callbacks=["langfuse"], global_callbacks=["lago"] + ) diff --git a/tests/otel_tests/test_guardrails.py b/tests/otel_tests/test_guardrails.py index 342ce33b9..12d9d1c38 100644 --- a/tests/otel_tests/test_guardrails.py +++ b/tests/otel_tests/test_guardrails.py @@ -212,7 +212,7 @@ async def test_bedrock_guardrail_triggered(): session, "sk-1234", model="fake-openai-endpoint", - messages=[{"role": "user", "content": f"Hello do you like coffee?"}], + messages=[{"role": "user", "content": "Hello do you like coffee?"}], guardrails=["bedrock-pre-guard"], ) pytest.fail("Should have thrown an exception") diff --git a/tests/otel_tests/test_moderations.py b/tests/otel_tests/test_moderations.py new file mode 100644 index 000000000..21abf7489 --- /dev/null +++ b/tests/otel_tests/test_moderations.py @@ -0,0 +1,71 @@ +import pytest +import asyncio +import aiohttp, openai +from openai import OpenAI, AsyncOpenAI +from typing import Optional, List, Union +import uuid + + +async def make_moderations_curl_request( + session, + key, + request_data: dict, +): + url = "http://0.0.0.0:4000/moderations" + headers = { + "Authorization": f"Bearer {key}", + "Content-Type": "application/json", + } + + async with session.post(url, headers=headers, json=request_data) as response: + status = response.status + response_text = await response.text() + + if status != 200: + raise Exception(response_text) + + return await response.json() + + +@pytest.mark.asyncio +async def test_basic_moderations_on_proxy_no_model(): + """ + Test moderations endpoint on proxy when no `model` is specified in the request + """ + async with aiohttp.ClientSession() as session: + test_text = "I want to harm someone" # Test text that should trigger moderation + request_data = { + "input": test_text, + } + try: + response = await make_moderations_curl_request( + session, + "sk-1234", + request_data, + ) + print("response=", response) + except Exception as e: + print(e) + pytest.fail("Moderations request failed") + + +@pytest.mark.asyncio +async def test_basic_moderations_on_proxy_with_model(): + """ + Test moderations endpoint on proxy when `model` is specified in the request + """ + async with aiohttp.ClientSession() as session: + test_text = "I want to harm someone" # Test text that should trigger moderation + request_data = { + "input": test_text, + "model": "text-moderation-stable", + } + try: + response = await make_moderations_curl_request( + session, + "sk-1234", + request_data, + ) + print("response=", response) + except Exception as e: + pytest.fail("Moderations request failed") diff --git a/tests/pass_through_tests/test_anthropic_passthrough.py b/tests/pass_through_tests/test_anthropic_passthrough.py index beffcbc95..6e7839282 100644 --- a/tests/pass_through_tests/test_anthropic_passthrough.py +++ b/tests/pass_through_tests/test_anthropic_passthrough.py @@ -1,9 +1,12 @@ """ This test ensures that the proxy can passthrough anthropic requests + """ import pytest import anthropic +import aiohttp +import asyncio client = anthropic.Anthropic( base_url="http://0.0.0.0:4000/anthropic", api_key="sk-1234" @@ -16,6 +19,11 @@ def test_anthropic_basic_completion(): model="claude-3-5-sonnet-20241022", max_tokens=1024, messages=[{"role": "user", "content": "Say 'hello test' and nothing else"}], + extra_body={ + "litellm_metadata": { + "tags": ["test-tag-1", "test-tag-2"], + } + }, ) print(response) @@ -30,9 +38,230 @@ def test_anthropic_streaming(): {"role": "user", "content": "Say 'hello stream test' and nothing else"} ], model="claude-3-5-sonnet-20241022", + extra_body={ + "litellm_metadata": { + "tags": ["test-tag-stream-1", "test-tag-stream-2"], + } + }, ) as stream: for text in stream.text_stream: collected_output.append(text) full_response = "".join(collected_output) print(full_response) + + +@pytest.mark.asyncio +async def test_anthropic_basic_completion_with_headers(): + print("making basic completion request to anthropic passthrough with aiohttp") + + headers = { + "Authorization": f"Bearer sk-1234", + "Content-Type": "application/json", + "Anthropic-Version": "2023-06-01", + } + + payload = { + "model": "claude-3-5-sonnet-20241022", + "max_tokens": 10, + "messages": [{"role": "user", "content": "Say 'hello test' and nothing else"}], + "litellm_metadata": { + "tags": ["test-tag-1", "test-tag-2"], + }, + } + + async with aiohttp.ClientSession() as session: + async with session.post( + "http://0.0.0.0:4000/anthropic/v1/messages", json=payload, headers=headers + ) as response: + response_text = await response.text() + print(f"Response text: {response_text}") + + response_json = await response.json() + response_headers = response.headers + litellm_call_id = response_headers.get("x-litellm-call-id") + + print(f"LiteLLM Call ID: {litellm_call_id}") + + # Wait for spend to be logged + await asyncio.sleep(15) + + # Check spend logs for this specific request + async with session.get( + f"http://0.0.0.0:4000/spend/logs?request_id={litellm_call_id}", + headers={"Authorization": "Bearer sk-1234"}, + ) as spend_response: + print("text spend response") + print(f"Spend response: {spend_response}") + spend_data = await spend_response.json() + print(f"Spend data: {spend_data}") + assert spend_data is not None, "Should have spend data for the request" + + log_entry = spend_data[ + 0 + ] # Get the first (and should be only) log entry + + # Basic existence checks + assert spend_data is not None, "Should have spend data for the request" + assert isinstance(log_entry, dict), "Log entry should be a dictionary" + + # Request metadata assertions + assert ( + log_entry["request_id"] == litellm_call_id + ), "Request ID should match" + assert ( + log_entry["call_type"] == "pass_through_endpoint" + ), "Call type should be pass_through_endpoint" + assert ( + log_entry["api_base"] == "https://api.anthropic.com/v1/messages" + ), "API base should be Anthropic's endpoint" + + # Token and spend assertions + assert log_entry["spend"] > 0, "Spend value should not be None" + assert isinstance( + log_entry["spend"], (int, float) + ), "Spend should be a number" + assert log_entry["total_tokens"] > 0, "Should have some tokens" + assert log_entry["prompt_tokens"] > 0, "Should have prompt tokens" + assert ( + log_entry["completion_tokens"] > 0 + ), "Should have completion tokens" + assert ( + log_entry["total_tokens"] + == log_entry["prompt_tokens"] + log_entry["completion_tokens"] + ), "Total tokens should equal prompt + completion" + + # Time assertions + assert all( + key in log_entry + for key in ["startTime", "endTime", "completionStartTime"] + ), "Should have all time fields" + assert ( + log_entry["startTime"] < log_entry["endTime"] + ), "Start time should be before end time" + + # Metadata assertions + assert ( + str(log_entry["cache_hit"]).lower() != "true" + ), "Cache should be off" + assert log_entry["request_tags"] == [ + "test-tag-1", + "test-tag-2", + ], "Tags should match input" + assert ( + "user_api_key" in log_entry["metadata"] + ), "Should have user API key in metadata" + + assert "claude" in log_entry["model"] + + +@pytest.mark.asyncio +async def test_anthropic_streaming_with_headers(): + print("making streaming request to anthropic passthrough with aiohttp") + + headers = { + "Authorization": f"Bearer sk-1234", + "Content-Type": "application/json", + "Anthropic-Version": "2023-06-01", + } + + payload = { + "model": "claude-3-5-sonnet-20241022", + "max_tokens": 10, + "messages": [ + {"role": "user", "content": "Say 'hello stream test' and nothing else"} + ], + "stream": True, + "litellm_metadata": { + "tags": ["test-tag-stream-1", "test-tag-stream-2"], + }, + } + + async with aiohttp.ClientSession() as session: + async with session.post( + "http://0.0.0.0:4000/anthropic/v1/messages", json=payload, headers=headers + ) as response: + print("response status") + print(response.status) + assert response.status == 200, "Response should be successful" + response_headers = response.headers + print(f"Response headers: {response_headers}") + litellm_call_id = response_headers.get("x-litellm-call-id") + print(f"LiteLLM Call ID: {litellm_call_id}") + + collected_output = [] + async for line in response.content: + if line: + text = line.decode("utf-8").strip() + if text.startswith("data: "): + collected_output.append(text[6:]) # Remove 'data: ' prefix + + print("Collected output:", "".join(collected_output)) + + # Wait for spend to be logged + await asyncio.sleep(20) + + # Check spend logs for this specific request + async with session.get( + f"http://0.0.0.0:4000/spend/logs?request_id={litellm_call_id}", + headers={"Authorization": "Bearer sk-1234"}, + ) as spend_response: + spend_data = await spend_response.json() + print(f"Spend data: {spend_data}") + assert spend_data is not None, "Should have spend data for the request" + + log_entry = spend_data[ + 0 + ] # Get the first (and should be only) log entry + + # Basic existence checks + assert spend_data is not None, "Should have spend data for the request" + assert isinstance(log_entry, dict), "Log entry should be a dictionary" + + # Request metadata assertions + assert ( + log_entry["request_id"] == litellm_call_id + ), "Request ID should match" + assert ( + log_entry["call_type"] == "pass_through_endpoint" + ), "Call type should be pass_through_endpoint" + assert ( + log_entry["api_base"] == "https://api.anthropic.com/v1/messages" + ), "API base should be Anthropic's endpoint" + + # Token and spend assertions + assert log_entry["spend"] > 0, "Spend value should not be None" + assert isinstance( + log_entry["spend"], (int, float) + ), "Spend should be a number" + assert log_entry["total_tokens"] > 0, "Should have some tokens" + assert ( + log_entry["completion_tokens"] > 0 + ), "Should have completion tokens" + assert ( + log_entry["total_tokens"] + == log_entry["prompt_tokens"] + log_entry["completion_tokens"] + ), "Total tokens should equal prompt + completion" + + # Time assertions + assert all( + key in log_entry + for key in ["startTime", "endTime", "completionStartTime"] + ), "Should have all time fields" + assert ( + log_entry["startTime"] < log_entry["endTime"] + ), "Start time should be before end time" + + # Metadata assertions + assert ( + str(log_entry["cache_hit"]).lower() != "true" + ), "Cache should be off" + assert log_entry["request_tags"] == [ + "test-tag-stream-1", + "test-tag-stream-2", + ], "Tags should match input" + assert ( + "user_api_key" in log_entry["metadata"] + ), "Should have user API key in metadata" + + assert "claude" in log_entry["model"] diff --git a/tests/anthropic_passthrough/test_anthropic_passthrough.py b/tests/pass_through_tests/test_anthropic_passthrough_python_sdkpy similarity index 100% rename from tests/anthropic_passthrough/test_anthropic_passthrough.py rename to tests/pass_through_tests/test_anthropic_passthrough_python_sdkpy diff --git a/tests/pass_through_tests/test_gemini.js b/tests/pass_through_tests/test_gemini.js new file mode 100644 index 000000000..2b7d6c5c6 --- /dev/null +++ b/tests/pass_through_tests/test_gemini.js @@ -0,0 +1,23 @@ +// const { GoogleGenerativeAI } = require("@google/generative-ai"); + +// const genAI = new GoogleGenerativeAI("sk-1234"); +// const model = genAI.getGenerativeModel({ model: "gemini-1.5-flash" }); + +// const prompt = "Explain how AI works in 2 pages"; + +// async function run() { +// try { +// const result = await model.generateContentStream(prompt, { baseUrl: "http://localhost:4000/gemini" }); +// const response = await result.response; +// console.log(response.text()); +// for await (const chunk of result.stream) { +// const chunkText = chunk.text(); +// console.log(chunkText); +// process.stdout.write(chunkText); +// } +// } catch (error) { +// console.error("Error:", error); +// } +// } + +// run(); \ No newline at end of file diff --git a/tests/pass_through_tests/test_gemini_with_spend.test.js b/tests/pass_through_tests/test_gemini_with_spend.test.js new file mode 100644 index 000000000..d02237fe3 --- /dev/null +++ b/tests/pass_through_tests/test_gemini_with_spend.test.js @@ -0,0 +1,123 @@ +const { GoogleGenerativeAI } = require("@google/generative-ai"); +const fs = require('fs'); +const path = require('path'); + +// Import fetch if the SDK uses it +const originalFetch = global.fetch || require('node-fetch'); + +let lastCallId; + +// Monkey-patch the fetch used internally +global.fetch = async function patchedFetch(url, options) { + const response = await originalFetch(url, options); + + // Store the call ID if it exists + lastCallId = response.headers.get('x-litellm-call-id'); + + return response; +}; + +describe('Gemini AI Tests', () => { + test('should successfully generate non-streaming content with tags', async () => { + const genAI = new GoogleGenerativeAI("sk-1234"); // litellm proxy API key + + const requestOptions = { + baseUrl: 'http://127.0.0.1:4000/gemini', + customHeaders: { + "tags": "gemini-js-sdk,pass-through-endpoint" + } + }; + + const model = genAI.getGenerativeModel({ + model: 'gemini-pro' + }, requestOptions); + + const prompt = 'Say "hello test" and nothing else'; + + const result = await model.generateContent(prompt); + expect(result).toBeDefined(); + + // Use the captured callId + const callId = lastCallId; + console.log("Captured Call ID:", callId); + + // Wait for spend to be logged + await new Promise(resolve => setTimeout(resolve, 15000)); + + // Check spend logs + const spendResponse = await fetch( + `http://127.0.0.1:4000/spend/logs?request_id=${callId}`, + { + headers: { + 'Authorization': 'Bearer sk-1234' + } + } + ); + + const spendData = await spendResponse.json(); + console.log("spendData", spendData) + expect(spendData).toBeDefined(); + expect(spendData[0].request_id).toBe(callId); + expect(spendData[0].call_type).toBe('pass_through_endpoint'); + expect(spendData[0].request_tags).toEqual(['gemini-js-sdk', 'pass-through-endpoint']); + expect(spendData[0].metadata).toHaveProperty('user_api_key'); + expect(spendData[0].model).toContain('gemini'); + expect(spendData[0].spend).toBeGreaterThan(0); + }, 25000); + + test('should successfully generate streaming content with tags', async () => { + const genAI = new GoogleGenerativeAI("sk-1234"); // litellm proxy API key + + const requestOptions = { + baseUrl: 'http://127.0.0.1:4000/gemini', + customHeaders: { + "tags": "gemini-js-sdk,pass-through-endpoint" + } + }; + + const model = genAI.getGenerativeModel({ + model: 'gemini-pro' + }, requestOptions); + + const prompt = 'Say "hello test" and nothing else'; + + const streamingResult = await model.generateContentStream(prompt); + expect(streamingResult).toBeDefined(); + + for await (const chunk of streamingResult.stream) { + console.log('stream chunk:', JSON.stringify(chunk)); + expect(chunk).toBeDefined(); + } + + const aggregatedResponse = await streamingResult.response; + console.log('aggregated response:', JSON.stringify(aggregatedResponse)); + expect(aggregatedResponse).toBeDefined(); + + // Use the captured callId + const callId = lastCallId; + console.log("Captured Call ID:", callId); + + // Wait for spend to be logged + await new Promise(resolve => setTimeout(resolve, 15000)); + + // Check spend logs + const spendResponse = await fetch( + `http://127.0.0.1:4000/spend/logs?request_id=${callId}`, + { + headers: { + 'Authorization': 'Bearer sk-1234' + } + } + ); + + const spendData = await spendResponse.json(); + console.log("spendData", spendData) + expect(spendData).toBeDefined(); + expect(spendData[0].request_id).toBe(callId); + expect(spendData[0].call_type).toBe('pass_through_endpoint'); + expect(spendData[0].request_tags).toEqual(['gemini-js-sdk', 'pass-through-endpoint']); + expect(spendData[0].metadata).toHaveProperty('user_api_key'); + expect(spendData[0].model).toContain('gemini'); + expect(spendData[0].spend).toBeGreaterThan(0); + }, 25000); +}); diff --git a/tests/pass_through_tests/test_local_gemini.js b/tests/pass_through_tests/test_local_gemini.js new file mode 100644 index 000000000..7043a5ab4 --- /dev/null +++ b/tests/pass_through_tests/test_local_gemini.js @@ -0,0 +1,55 @@ +const { GoogleGenerativeAI, ModelParams, RequestOptions } = require("@google/generative-ai"); + +const modelParams = { + model: 'gemini-pro', +}; + +const requestOptions = { + baseUrl: 'http://127.0.0.1:4000/gemini', + customHeaders: { + "tags": "gemini-js-sdk,gemini-pro" + } +}; + +const genAI = new GoogleGenerativeAI("sk-1234"); // litellm proxy API key +const model = genAI.getGenerativeModel(modelParams, requestOptions); + +const testPrompt = "Explain how AI works"; + +async function main() { + console.log("making request") + try { + const result = await model.generateContent(testPrompt); + console.log(result.response.text()); + } catch (error) { + console.error('Error details:', { + name: error.name, + message: error.message, + cause: error.cause, + // Check if there's a network error + isNetworkError: error instanceof TypeError && error.message === 'fetch failed' + }); + + // Check if the server is running + if (error instanceof TypeError && error.message === 'fetch failed') { + console.error('Make sure your local server is running at http://localhost:4000'); + } + } +} + + +async function main_streaming() { + try { + const streamingResult = await model.generateContentStream(testPrompt); + for await (const item of streamingResult.stream) { + console.log('stream chunk: ', JSON.stringify(item)); + } + const aggregatedResponse = await streamingResult.response; + console.log('aggregated response: ', JSON.stringify(aggregatedResponse)); + } catch (error) { + console.error('Error details:', error); + } +} + +// main(); +main_streaming(); \ No newline at end of file diff --git a/tests/pass_through_tests/test_local_vertex.js b/tests/pass_through_tests/test_local_vertex.js new file mode 100644 index 000000000..9ee603e7a --- /dev/null +++ b/tests/pass_through_tests/test_local_vertex.js @@ -0,0 +1,43 @@ +const { VertexAI, RequestOptions } = require('@google-cloud/vertexai'); + + + +const vertexAI = new VertexAI({ + project: 'adroit-crow-413218', + location: 'us-central1', + apiEndpoint: "127.0.0.1:4000/vertex-ai" +}); + +// Create customHeaders using Headers +const customHeaders = new Headers({ + "X-Litellm-Api-Key": "sk-1234", + tags: "vertexjs,test-2" +}); + +// Use customHeaders in RequestOptions +const requestOptions = { + customHeaders: customHeaders, +}; + +const generativeModel = vertexAI.getGenerativeModel( + { model: 'gemini-1.0-pro' }, + requestOptions +); + +async function testModel() { + try { + const request = { + contents: [{role: 'user', parts: [{text: 'How are you doing today tell me your name?'}]}], + }; + const streamingResult = await generativeModel.generateContentStream(request); + for await (const item of streamingResult.stream) { + console.log('stream chunk: ', JSON.stringify(item)); + } + const aggregatedResponse = await streamingResult.response; + console.log('aggregated response: ', JSON.stringify(aggregatedResponse)); + } catch (error) { + console.error('Error:', error); + } +} + +testModel(); \ No newline at end of file diff --git a/tests/pass_through_tests/test_vertex.test.js b/tests/pass_through_tests/test_vertex.test.js new file mode 100644 index 000000000..dc457c68a --- /dev/null +++ b/tests/pass_through_tests/test_vertex.test.js @@ -0,0 +1,114 @@ +const { VertexAI, RequestOptions } = require('@google-cloud/vertexai'); +const fs = require('fs'); +const path = require('path'); +const os = require('os'); +const { writeFileSync } = require('fs'); + + +// Import fetch if the SDK uses it +const originalFetch = global.fetch || require('node-fetch'); + +// Monkey-patch the fetch used internally +global.fetch = async function patchedFetch(url, options) { + // Modify the URL to use HTTP instead of HTTPS + if (url.startsWith('https://localhost:4000')) { + url = url.replace('https://', 'http://'); + } + console.log('Patched fetch sending request to:', url); + return originalFetch(url, options); +}; + +function loadVertexAiCredentials() { + console.log("loading vertex ai credentials"); + const filepath = path.dirname(__filename); + const vertexKeyPath = path.join(filepath, "vertex_key.json"); + + // Initialize default empty service account data + let serviceAccountKeyData = {}; + + // Try to read existing vertex_key.json + try { + const content = fs.readFileSync(vertexKeyPath, 'utf8'); + if (content && content.trim()) { + serviceAccountKeyData = JSON.parse(content); + } + } catch (error) { + // File doesn't exist or is invalid, continue with empty object + } + + // Update with environment variables + const privateKeyId = process.env.VERTEX_AI_PRIVATE_KEY_ID || ""; + const privateKey = (process.env.VERTEX_AI_PRIVATE_KEY || "").replace(/\\n/g, "\n"); + + serviceAccountKeyData.private_key_id = privateKeyId; + serviceAccountKeyData.private_key = privateKey; + + // Create temporary file + const tempFilePath = path.join(os.tmpdir(), `vertex-credentials-${Date.now()}.json`); + writeFileSync(tempFilePath, JSON.stringify(serviceAccountKeyData, null, 2)); + + // Set environment variable + process.env.GOOGLE_APPLICATION_CREDENTIALS = tempFilePath; +} + +// Run credential loading before tests +beforeAll(() => { + loadVertexAiCredentials(); +}); + + + +describe('Vertex AI Tests', () => { + test('should successfully generate content from Vertex AI', async () => { + const vertexAI = new VertexAI({ + project: 'adroit-crow-413218', + location: 'us-central1', + apiEndpoint: "localhost:4000/vertex-ai" + }); + + const customHeaders = new Headers({ + "x-litellm-api-key": "sk-1234" + }); + + const requestOptions = { + customHeaders: customHeaders + }; + + const generativeModel = vertexAI.getGenerativeModel( + { model: 'gemini-1.0-pro' }, + requestOptions + ); + + const request = { + contents: [{role: 'user', parts: [{text: 'How are you doing today tell me your name?'}]}], + }; + + const streamingResult = await generativeModel.generateContentStream(request); + + // Add some assertions + expect(streamingResult).toBeDefined(); + + for await (const item of streamingResult.stream) { + console.log('stream chunk:', JSON.stringify(item)); + expect(item).toBeDefined(); + } + + const aggregatedResponse = await streamingResult.response; + console.log('aggregated response:', JSON.stringify(aggregatedResponse)); + expect(aggregatedResponse).toBeDefined(); + }); + + + test('should successfully generate non-streaming content from Vertex AI', async () => { + const vertexAI = new VertexAI({project: 'adroit-crow-413218', location: 'us-central1', apiEndpoint: "localhost:4000/vertex-ai"}); + const customHeaders = new Headers({"x-litellm-api-key": "sk-1234"}); + const requestOptions = {customHeaders: customHeaders}; + const generativeModel = vertexAI.getGenerativeModel({model: 'gemini-1.0-pro'}, requestOptions); + const request = {contents: [{role: 'user', parts: [{text: 'What is 2+2?'}]}]}; + + const result = await generativeModel.generateContent(request); + expect(result).toBeDefined(); + expect(result.response).toBeDefined(); + console.log('non-streaming response:', JSON.stringify(result.response)); + }); +}); \ No newline at end of file diff --git a/tests/pass_through_tests/test_vertex_ai.py b/tests/pass_through_tests/test_vertex_ai.py index 32d6515b8..99b513e82 100644 --- a/tests/pass_through_tests/test_vertex_ai.py +++ b/tests/pass_through_tests/test_vertex_ai.py @@ -99,7 +99,7 @@ async def test_basic_vertex_ai_pass_through_with_spendlog(): vertexai.init( project="adroit-crow-413218", location="us-central1", - api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex-ai", + api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex_ai", api_transport="rest", ) @@ -121,6 +121,7 @@ async def test_basic_vertex_ai_pass_through_with_spendlog(): @pytest.mark.asyncio() +@pytest.mark.skip(reason="skip flaky test - vertex pass through streaming is flaky") async def test_basic_vertex_ai_pass_through_streaming_with_spendlog(): spend_before = await call_spend_logs_endpoint() or 0.0 @@ -130,7 +131,7 @@ async def test_basic_vertex_ai_pass_through_streaming_with_spendlog(): vertexai.init( project="adroit-crow-413218", location="us-central1", - api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex-ai", + api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex_ai", api_transport="rest", ) @@ -169,7 +170,7 @@ async def test_vertex_ai_pass_through_endpoint_context_caching(): vertexai.init( project="adroit-crow-413218", location="us-central1", - api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex-ai", + api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex_ai", api_transport="rest", ) diff --git a/tests/pass_through_tests/test_vertex_with_spend.test.js b/tests/pass_through_tests/test_vertex_with_spend.test.js new file mode 100644 index 000000000..d49b1eda2 --- /dev/null +++ b/tests/pass_through_tests/test_vertex_with_spend.test.js @@ -0,0 +1,194 @@ +const { VertexAI, RequestOptions } = require('@google-cloud/vertexai'); +const fs = require('fs'); +const path = require('path'); +const os = require('os'); +const { writeFileSync } = require('fs'); + + +// Import fetch if the SDK uses it +const originalFetch = global.fetch || require('node-fetch'); + +let lastCallId; + +// Monkey-patch the fetch used internally +global.fetch = async function patchedFetch(url, options) { + // Modify the URL to use HTTP instead of HTTPS + if (url.startsWith('https://127.0.0.1:4000')) { + url = url.replace('https://', 'http://'); + } + console.log('Patched fetch sending request to:', url); + + const response = await originalFetch(url, options); + + // Store the call ID if it exists + lastCallId = response.headers.get('x-litellm-call-id'); + + return response; +}; + +function loadVertexAiCredentials() { + console.log("loading vertex ai credentials"); + const filepath = path.dirname(__filename); + const vertexKeyPath = path.join(filepath, "vertex_key.json"); + + // Initialize default empty service account data + let serviceAccountKeyData = {}; + + // Try to read existing vertex_key.json + try { + const content = fs.readFileSync(vertexKeyPath, 'utf8'); + if (content && content.trim()) { + serviceAccountKeyData = JSON.parse(content); + } + } catch (error) { + // File doesn't exist or is invalid, continue with empty object + } + + // Update with environment variables + const privateKeyId = process.env.VERTEX_AI_PRIVATE_KEY_ID || ""; + const privateKey = (process.env.VERTEX_AI_PRIVATE_KEY || "").replace(/\\n/g, "\n"); + + serviceAccountKeyData.private_key_id = privateKeyId; + serviceAccountKeyData.private_key = privateKey; + + // Create temporary file + const tempFilePath = path.join(os.tmpdir(), `vertex-credentials-${Date.now()}.json`); + writeFileSync(tempFilePath, JSON.stringify(serviceAccountKeyData, null, 2)); + + // Set environment variable + process.env.GOOGLE_APPLICATION_CREDENTIALS = tempFilePath; +} + +// Run credential loading before tests +beforeAll(() => { + loadVertexAiCredentials(); +}); + + + +describe('Vertex AI Tests', () => { + test('should successfully generate non-streaming content with tags', async () => { + const vertexAI = new VertexAI({ + project: 'adroit-crow-413218', + location: 'us-central1', + apiEndpoint: "127.0.0.1:4000/vertex_ai" + }); + + const customHeaders = new Headers({ + "x-litellm-api-key": "sk-1234", + "tags": "vertex-js-sdk,pass-through-endpoint" + }); + + const requestOptions = { + customHeaders: customHeaders + }; + + const generativeModel = vertexAI.getGenerativeModel( + { model: 'gemini-1.0-pro' }, + requestOptions + ); + + const request = { + contents: [{role: 'user', parts: [{text: 'Say "hello test" and nothing else'}]}] + }; + + const result = await generativeModel.generateContent(request); + expect(result).toBeDefined(); + + // Use the captured callId + const callId = lastCallId; + console.log("Captured Call ID:", callId); + + // Wait for spend to be logged + await new Promise(resolve => setTimeout(resolve, 15000)); + + // Check spend logs + const spendResponse = await fetch( + `http://127.0.0.1:4000/spend/logs?request_id=${callId}`, + { + headers: { + 'Authorization': 'Bearer sk-1234' + } + } + ); + + const spendData = await spendResponse.json(); + console.log("spendData", spendData) + expect(spendData).toBeDefined(); + expect(spendData[0].request_id).toBe(callId); + expect(spendData[0].call_type).toBe('pass_through_endpoint'); + expect(spendData[0].request_tags).toEqual(['vertex-js-sdk', 'pass-through-endpoint']); + expect(spendData[0].metadata).toHaveProperty('user_api_key'); + expect(spendData[0].model).toContain('gemini'); + expect(spendData[0].spend).toBeGreaterThan(0); + }, 25000); + + test('should successfully generate streaming content with tags', async () => { + const vertexAI = new VertexAI({ + project: 'adroit-crow-413218', + location: 'us-central1', + apiEndpoint: "127.0.0.1:4000/vertex_ai" + }); + + const customHeaders = new Headers({ + "x-litellm-api-key": "sk-1234", + "tags": "vertex-js-sdk,pass-through-endpoint" + }); + + const requestOptions = { + customHeaders: customHeaders + }; + + const generativeModel = vertexAI.getGenerativeModel( + { model: 'gemini-1.0-pro' }, + requestOptions + ); + + const request = { + contents: [{role: 'user', parts: [{text: 'Say "hello test" and nothing else'}]}] + }; + + const streamingResult = await generativeModel.generateContentStream(request); + expect(streamingResult).toBeDefined(); + + + // Add some assertions + expect(streamingResult).toBeDefined(); + + for await (const item of streamingResult.stream) { + console.log('stream chunk:', JSON.stringify(item)); + expect(item).toBeDefined(); + } + + const aggregatedResponse = await streamingResult.response; + console.log('aggregated response:', JSON.stringify(aggregatedResponse)); + expect(aggregatedResponse).toBeDefined(); + + // Use the captured callId + const callId = lastCallId; + console.log("Captured Call ID:", callId); + + // Wait for spend to be logged + await new Promise(resolve => setTimeout(resolve, 15000)); + + // Check spend logs + const spendResponse = await fetch( + `http://127.0.0.1:4000/spend/logs?request_id=${callId}`, + { + headers: { + 'Authorization': 'Bearer sk-1234' + } + } + ); + + const spendData = await spendResponse.json(); + console.log("spendData", spendData) + expect(spendData).toBeDefined(); + expect(spendData[0].request_id).toBe(callId); + expect(spendData[0].call_type).toBe('pass_through_endpoint'); + expect(spendData[0].request_tags).toEqual(['vertex-js-sdk', 'pass-through-endpoint']); + expect(spendData[0].metadata).toHaveProperty('user_api_key'); + expect(spendData[0].model).toContain('gemini'); + expect(spendData[0].spend).toBeGreaterThan(0); + }, 25000); +}); \ No newline at end of file diff --git a/tests/pass_through_unit_tests/test_pass_through_unit_tests.py b/tests/pass_through_unit_tests/test_pass_through_unit_tests.py new file mode 100644 index 000000000..d5b6b1c9a --- /dev/null +++ b/tests/pass_through_unit_tests/test_pass_through_unit_tests.py @@ -0,0 +1,357 @@ +import json +import os +import sys +from datetime import datetime +from unittest.mock import AsyncMock, Mock, patch, MagicMock +from typing import Optional + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path + +import fastapi +from fastapi import FastAPI +from fastapi.routing import APIRoute +import httpx +import pytest +import litellm +from typing import AsyncGenerator +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.proxy.pass_through_endpoints.types import EndpointType +from litellm.proxy.pass_through_endpoints.success_handler import ( + PassThroughEndpointLogging, +) +from litellm.proxy.pass_through_endpoints.streaming_handler import ( + PassThroughStreamingHandler, +) + +from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + pass_through_request, +) +from fastapi import Request +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + _init_kwargs_for_pass_through_endpoint, + _update_metadata_with_tags_in_header, +) +from litellm.proxy.pass_through_endpoints.types import PassthroughStandardLoggingPayload + + +@pytest.fixture +def mock_request(): + # Create a mock request with headers + class QueryParams: + def __init__(self): + self._dict = {} + + class MockRequest: + def __init__( + self, headers=None, method="POST", request_body: Optional[dict] = None + ): + self.headers = headers or {} + self.query_params = QueryParams() + self.method = method + self.request_body = request_body or {} + + async def body(self) -> bytes: + return bytes(json.dumps(self.request_body), "utf-8") + + return MockRequest + + +@pytest.fixture +def mock_user_api_key_dict(): + return UserAPIKeyAuth( + api_key="test-key", + user_id="test-user", + team_id="test-team", + ) + + +def test_update_metadata_with_tags_in_header_no_tags(mock_request): + """ + No tags should be added to metadata if they do not exist in headers + """ + # Test when no tags are present in headers + request = mock_request(headers={}) + metadata = {"existing": "value"} + + result = _update_metadata_with_tags_in_header(request=request, metadata=metadata) + + assert result == {"existing": "value"} + assert "tags" not in result + + +def test_update_metadata_with_tags_in_header_with_tags(mock_request): + """ + Tags should be added to metadata if they exist in headers + """ + # Test when tags are present in headers + request = mock_request(headers={"tags": "tag1,tag2,tag3"}) + metadata = {"existing": "value"} + + result = _update_metadata_with_tags_in_header(request=request, metadata=metadata) + + assert result == {"existing": "value", "tags": ["tag1", "tag2", "tag3"]} + + +def test_init_kwargs_for_pass_through_endpoint_basic( + mock_request, mock_user_api_key_dict +): + """ + Basic test for init_kwargs_for_pass_through_endpoint + + - metadata should contain user_api_key, user_api_key_user_id, user_api_key_team_id, user_api_key_end_user_id from `mock_user_api_key_dict` + """ + request = mock_request() + passthrough_payload = PassthroughStandardLoggingPayload( + url="https://test.com", + request_body={}, + ) + + result = _init_kwargs_for_pass_through_endpoint( + request=request, + user_api_key_dict=mock_user_api_key_dict, + passthrough_logging_payload=passthrough_payload, + litellm_call_id="test-call-id", + ) + + assert result["call_type"] == "pass_through_endpoint" + assert result["litellm_call_id"] == "test-call-id" + assert result["passthrough_logging_payload"] == passthrough_payload + + # Check metadata + expected_metadata = { + "user_api_key": "test-key", + "user_api_key_user_id": "test-user", + "user_api_key_team_id": "test-team", + "user_api_key_end_user_id": "test-user", + } + assert result["litellm_params"]["metadata"] == expected_metadata + + +def test_init_kwargs_with_litellm_metadata(mock_request, mock_user_api_key_dict): + """ + Expected behavior: litellm_metadata should be merged with default metadata + + see usage example here: https://docs.litellm.ai/docs/pass_through/anthropic_completion#send-litellm_metadata-tags + """ + request = mock_request() + parsed_body = { + "litellm_metadata": {"custom_field": "custom_value", "tags": ["tag1", "tag2"]} + } + passthrough_payload = PassthroughStandardLoggingPayload( + url="https://test.com", + request_body={}, + ) + + result = _init_kwargs_for_pass_through_endpoint( + request=request, + user_api_key_dict=mock_user_api_key_dict, + passthrough_logging_payload=passthrough_payload, + _parsed_body=parsed_body, + litellm_call_id="test-call-id", + ) + + # Check that litellm_metadata was merged with default metadata + metadata = result["litellm_params"]["metadata"] + print("metadata", metadata) + assert metadata["custom_field"] == "custom_value" + assert metadata["tags"] == ["tag1", "tag2"] + assert metadata["user_api_key"] == "test-key" + + +def test_init_kwargs_with_tags_in_header(mock_request, mock_user_api_key_dict): + """ + Tags should be added to metadata if they exist in headers + """ + request = mock_request(headers={"tags": "tag1,tag2"}) + passthrough_payload = PassthroughStandardLoggingPayload( + url="https://test.com", + request_body={}, + ) + + result = _init_kwargs_for_pass_through_endpoint( + request=request, + user_api_key_dict=mock_user_api_key_dict, + passthrough_logging_payload=passthrough_payload, + litellm_call_id="test-call-id", + ) + + # Check that tags were added to metadata + metadata = result["litellm_params"]["metadata"] + print("metadata", metadata) + assert metadata["tags"] == ["tag1", "tag2"] + + +athropic_request_body = { + "model": "claude-3-5-sonnet-20241022", + "max_tokens": 256, + "messages": [{"role": "user", "content": "Hello, world tell me 2 sentences "}], + "litellm_metadata": {"tags": ["hi", "hello"]}, +} + + +@pytest.mark.asyncio +async def test_pass_through_request_logging_failure( + mock_request, mock_user_api_key_dict +): + """ + Test that pass_through_request still returns a response even if logging raises an Exception + """ + + # Mock the logging handler to raise an error + async def mock_logging_failure(*args, **kwargs): + raise Exception("Logging failed!") + + # Create a mock response + mock_response = AsyncMock() + mock_response.status_code = 200 + mock_response.headers = {"content-type": "application/json"} + + # Add mock content + mock_response._content = b'{"mock": "response"}' + + async def mock_aread(): + return mock_response._content + + mock_response.aread = mock_aread + + # Patch both the logging handler and the httpx client + with patch( + "litellm.proxy.pass_through_endpoints.pass_through_endpoints.PassThroughEndpointLogging.pass_through_async_success_handler", + new=mock_logging_failure, + ), patch( + "httpx.AsyncClient.send", + return_value=mock_response, + ), patch( + "httpx.AsyncClient.request", + return_value=mock_response, + ): + request = mock_request( + headers={}, method="POST", request_body=athropic_request_body + ) + response = await pass_through_request( + request=request, + target="https://exampleopenaiendpoint-production.up.railway.app/v1/messages", + custom_headers={}, + user_api_key_dict=mock_user_api_key_dict, + ) + + # Assert response was returned successfully despite logging failure + assert response.status_code == 200 + + # Verify we got the mock response content + if hasattr(response, "body"): + content = response.body + else: + content = await response.aread() + + assert content == b'{"mock": "response"}' + + +@pytest.mark.asyncio +async def test_pass_through_request_logging_failure_with_stream( + mock_request, mock_user_api_key_dict +): + """ + Test that pass_through_request still returns a response even if logging raises an Exception + """ + + # Mock the logging handler to raise an error + async def mock_logging_failure(*args, **kwargs): + raise Exception("Logging failed!") + + # Create a mock response + mock_response = AsyncMock() + mock_response.status_code = 200 + + # Add headers property to mock response + mock_response.headers = { + "content-type": "application/json", # Not streaming + } + + # Create mock chunks for streaming + mock_chunks = [b'{"chunk": 1}', b'{"chunk": 2}'] + mock_response.body_iterator = AsyncMock() + mock_response.body_iterator.__aiter__.return_value = mock_chunks + + # Add aread method to mock response + mock_response._content = b'{"mock": "response"}' + + async def mock_aread(): + return mock_response._content + + mock_response.aread = mock_aread + + # Patch both the logging handler and the httpx client + with patch( + "litellm.proxy.pass_through_endpoints.streaming_handler.PassThroughStreamingHandler._route_streaming_logging_to_handler", + new=mock_logging_failure, + ), patch( + "httpx.AsyncClient.send", + return_value=mock_response, + ), patch( + "httpx.AsyncClient.request", + return_value=mock_response, + ): + request = mock_request( + headers={}, method="POST", request_body=athropic_request_body + ) + response = await pass_through_request( + request=request, + target="https://exampleopenaiendpoint-production.up.railway.app/v1/messages", + custom_headers={}, + user_api_key_dict=mock_user_api_key_dict, + ) + + # Assert response was returned successfully despite logging failure + assert response.status_code == 200 + + # For non-streaming responses, we can access the content directly + if hasattr(response, "body"): + content = response.body + else: + # For streaming responses, we need to read the chunks + chunks = [] + async for chunk in response.body_iterator: + chunks.append(chunk) + content = b"".join(chunks) + + # Verify we got some response content + assert content is not None + if isinstance(content, bytes): + assert len(content) > 0 + + +def test_pass_through_routes_support_all_methods(): + """ + Test that all pass-through routes support GET, POST, PUT, DELETE, PATCH methods + """ + # Import the routers + from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import ( + router as llm_router, + ) + from litellm.proxy.vertex_ai_endpoints.vertex_endpoints import ( + router as vertex_router, + ) + + # Expected HTTP methods + expected_methods = {"GET", "POST", "PUT", "DELETE", "PATCH"} + + # Function to check routes in a router + def check_router_methods(router): + for route in router.routes: + if isinstance(route, APIRoute): + # Get path and methods for this route + path = route.path + methods = set(route.methods) + print("supported methods for route", path, "are", methods) + # Assert all expected methods are supported + assert ( + methods == expected_methods + ), f"Route {path} does not support all methods. Supported: {methods}, Expected: {expected_methods}" + + # Check both routers + check_router_methods(llm_router) + check_router_methods(vertex_router) diff --git a/tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py b/tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py new file mode 100644 index 000000000..ecd289005 --- /dev/null +++ b/tests/pass_through_unit_tests/test_unit_test_anthropic_pass_through.py @@ -0,0 +1,112 @@ +import json +import os +import sys +from datetime import datetime +from unittest.mock import AsyncMock, Mock, patch + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path + + +import httpx +import pytest +import litellm +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + +# Import the class we're testing +from litellm.proxy.pass_through_endpoints.llm_provider_handlers.anthropic_passthrough_logging_handler import ( + AnthropicPassthroughLoggingHandler, +) + + +@pytest.fixture +def mock_response(): + return { + "model": "claude-3-opus-20240229", + "content": [{"text": "Hello, world!", "type": "text"}], + "role": "assistant", + } + + +@pytest.fixture +def mock_httpx_response(): + mock_resp = Mock(spec=httpx.Response) + mock_resp.json.return_value = { + "content": [{"text": "Hi! My name is Claude.", "type": "text"}], + "id": "msg_013Zva2CMHLNnXjNJJKqJ2EF", + "model": "claude-3-5-sonnet-20241022", + "role": "assistant", + "stop_reason": "end_turn", + "stop_sequence": None, + "type": "message", + "usage": {"input_tokens": 2095, "output_tokens": 503}, + } + mock_resp.status_code = 200 + mock_resp.headers = {"Content-Type": "application/json"} + return mock_resp + + +@pytest.fixture +def mock_logging_obj(): + logging_obj = LiteLLMLoggingObj( + model="claude-3-opus-20240229", + messages=[], + stream=False, + call_type="completion", + start_time=datetime.now(), + litellm_call_id="123", + function_id="456", + ) + + logging_obj.async_success_handler = AsyncMock() + return logging_obj + + +@pytest.mark.asyncio +async def test_anthropic_passthrough_handler( + mock_httpx_response, mock_response, mock_logging_obj +): + """ + Unit test - Assert that the anthropic passthrough handler calls the litellm logging object's async_success_handler + """ + start_time = datetime.now() + end_time = datetime.now() + + result = AnthropicPassthroughLoggingHandler.anthropic_passthrough_handler( + httpx_response=mock_httpx_response, + response_body=mock_response, + logging_obj=mock_logging_obj, + url_route="/v1/chat/completions", + result="success", + start_time=start_time, + end_time=end_time, + cache_hit=False, + ) + + assert isinstance(result["result"], litellm.ModelResponse) + + +def test_create_anthropic_response_logging_payload(mock_logging_obj): + # Test the logging payload creation + model_response = litellm.ModelResponse() + model_response.choices = [{"message": {"content": "Test response"}}] + + start_time = datetime.now() + end_time = datetime.now() + + result = ( + AnthropicPassthroughLoggingHandler._create_anthropic_response_logging_payload( + litellm_model_response=model_response, + model="claude-3-opus-20240229", + kwargs={}, + start_time=start_time, + end_time=end_time, + logging_obj=mock_logging_obj, + ) + ) + + assert isinstance(result, dict) + assert "model" in result + assert "response_cost" in result + assert "standard_logging_object" in result diff --git a/tests/pass_through_unit_tests/test_unit_test_streaming.py b/tests/pass_through_unit_tests/test_unit_test_streaming.py new file mode 100644 index 000000000..61b71b56d --- /dev/null +++ b/tests/pass_through_unit_tests/test_unit_test_streaming.py @@ -0,0 +1,119 @@ +import json +import os +import sys +from datetime import datetime +from unittest.mock import AsyncMock, Mock, patch, MagicMock + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path + +import httpx +import pytest +import litellm +from typing import AsyncGenerator +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.proxy.pass_through_endpoints.types import EndpointType +from litellm.proxy.pass_through_endpoints.success_handler import ( + PassThroughEndpointLogging, +) +from litellm.proxy.pass_through_endpoints.streaming_handler import ( + PassThroughStreamingHandler, +) + + +# Helper function to mock async iteration +async def aiter_mock(iterable): + for item in iterable: + yield item + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "endpoint_type,url_route", + [ + ( + EndpointType.VERTEX_AI, + "v1/projects/adroit-crow-413218/locations/us-central1/publishers/google/models/gemini-1.0-pro:generateContent", + ), + (EndpointType.ANTHROPIC, "/v1/messages"), + ], +) +async def test_chunk_processor_yields_raw_bytes(endpoint_type, url_route): + """ + Test that the chunk_processor yields raw bytes + + This is CRITICAL for pass throughs streaming with Vertex AI and Anthropic + """ + # Mock inputs + response = AsyncMock(spec=httpx.Response) + raw_chunks = [ + b'{"id": "1", "content": "Hello"}', + b'{"id": "2", "content": "World"}', + b'\n\ndata: {"id": "3"}', # Testing different byte formats + ] + + # Mock aiter_bytes to return an async generator + async def mock_aiter_bytes(): + for chunk in raw_chunks: + yield chunk + + response.aiter_bytes = mock_aiter_bytes + + request_body = {"key": "value"} + litellm_logging_obj = MagicMock() + start_time = datetime.now() + passthrough_success_handler_obj = MagicMock() + litellm_logging_obj.async_success_handler = AsyncMock() + + # Capture yielded chunks and perform detailed assertions + received_chunks = [] + async for chunk in PassThroughStreamingHandler.chunk_processor( + response=response, + request_body=request_body, + litellm_logging_obj=litellm_logging_obj, + endpoint_type=endpoint_type, + start_time=start_time, + passthrough_success_handler_obj=passthrough_success_handler_obj, + url_route=url_route, + ): + # Assert each chunk is bytes + assert isinstance(chunk, bytes), f"Chunk should be bytes, got {type(chunk)}" + # Assert no decoding/encoding occurred (chunk should be exactly as input) + assert ( + chunk in raw_chunks + ), f"Chunk {chunk} was modified during processing. For pass throughs streaming, chunks should be raw bytes" + received_chunks.append(chunk) + + # Assert all chunks were processed + assert len(received_chunks) == len(raw_chunks), "Not all chunks were processed" + + # collected chunks all together + assert b"".join(received_chunks) == b"".join( + raw_chunks + ), "Collected chunks do not match raw chunks" + + +def test_convert_raw_bytes_to_str_lines(): + """ + Test that the _convert_raw_bytes_to_str_lines method correctly converts raw bytes to a list of strings + """ + # Test case 1: Single chunk + raw_bytes = [b'data: {"content": "Hello"}\n'] + result = PassThroughStreamingHandler._convert_raw_bytes_to_str_lines(raw_bytes) + assert result == ['data: {"content": "Hello"}'] + + # Test case 2: Multiple chunks + raw_bytes = [b'data: {"content": "Hello"}\n', b'data: {"content": "World"}\n'] + result = PassThroughStreamingHandler._convert_raw_bytes_to_str_lines(raw_bytes) + assert result == ['data: {"content": "Hello"}', 'data: {"content": "World"}'] + + # Test case 3: Empty input + raw_bytes = [] + result = PassThroughStreamingHandler._convert_raw_bytes_to_str_lines(raw_bytes) + assert result == [] + + # Test case 4: Chunks with empty lines + raw_bytes = [b'data: {"content": "Hello"}\n\n', b'\ndata: {"content": "World"}\n'] + result = PassThroughStreamingHandler._convert_raw_bytes_to_str_lines(raw_bytes) + assert result == ['data: {"content": "Hello"}', 'data: {"content": "World"}'] diff --git a/tests/pass_through_unit_tests/test_unit_test_vertex_pass_through.py b/tests/pass_through_unit_tests/test_unit_test_vertex_pass_through.py new file mode 100644 index 000000000..4c66f6993 --- /dev/null +++ b/tests/pass_through_unit_tests/test_unit_test_vertex_pass_through.py @@ -0,0 +1,169 @@ +import json +import os +import sys +from datetime import datetime +from unittest.mock import AsyncMock, Mock, patch + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path + + +import httpx +import pytest +import litellm +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + + +from litellm.proxy.vertex_ai_endpoints.vertex_endpoints import ( + get_litellm_virtual_key, + vertex_proxy_route, + _get_vertex_env_vars, + set_default_vertex_config, + VertexPassThroughCredentials, + default_vertex_config, +) + + +@pytest.mark.asyncio +async def test_get_litellm_virtual_key(): + """ + Test that the get_litellm_virtual_key function correctly handles the API key authentication + """ + # Test with x-litellm-api-key + mock_request = Mock() + mock_request.headers = {"x-litellm-api-key": "test-key-123"} + result = get_litellm_virtual_key(mock_request) + assert result == "Bearer test-key-123" + + # Test with Authorization header + mock_request.headers = {"Authorization": "Bearer auth-key-456"} + result = get_litellm_virtual_key(mock_request) + assert result == "Bearer auth-key-456" + + # Test with both headers (x-litellm-api-key should take precedence) + mock_request.headers = { + "x-litellm-api-key": "test-key-123", + "Authorization": "Bearer auth-key-456", + } + result = get_litellm_virtual_key(mock_request) + assert result == "Bearer test-key-123" + + +@pytest.mark.asyncio +async def test_vertex_proxy_route_api_key_auth(): + """ + Critical + + This is how Vertex AI JS SDK will Auth to Litellm Proxy + """ + # Mock dependencies + mock_request = Mock() + mock_request.headers = {"x-litellm-api-key": "test-key-123"} + mock_request.method = "POST" + mock_response = Mock() + + with patch( + "litellm.proxy.vertex_ai_endpoints.vertex_endpoints.user_api_key_auth" + ) as mock_auth: + mock_auth.return_value = {"api_key": "test-key-123"} + + with patch( + "litellm.proxy.vertex_ai_endpoints.vertex_endpoints.create_pass_through_route" + ) as mock_pass_through: + mock_pass_through.return_value = AsyncMock( + return_value={"status": "success"} + ) + + # Call the function + result = await vertex_proxy_route( + endpoint="v1/projects/test-project/locations/us-central1/publishers/google/models/gemini-1.5-pro:generateContent", + request=mock_request, + fastapi_response=mock_response, + ) + + # Verify user_api_key_auth was called with the correct Bearer token + mock_auth.assert_called_once() + call_args = mock_auth.call_args[1] + assert call_args["api_key"] == "Bearer test-key-123" + + +@pytest.mark.asyncio +async def test_get_vertex_env_vars(): + """Test that _get_vertex_env_vars correctly reads environment variables""" + # Set environment variables for the test + os.environ["DEFAULT_VERTEXAI_PROJECT"] = "test-project-123" + os.environ["DEFAULT_VERTEXAI_LOCATION"] = "us-central1" + os.environ["DEFAULT_GOOGLE_APPLICATION_CREDENTIALS"] = "/path/to/creds" + + try: + result = _get_vertex_env_vars() + print(result) + + # Verify the result + assert isinstance(result, VertexPassThroughCredentials) + assert result.vertex_project == "test-project-123" + assert result.vertex_location == "us-central1" + assert result.vertex_credentials == "/path/to/creds" + + finally: + # Clean up environment variables + del os.environ["DEFAULT_VERTEXAI_PROJECT"] + del os.environ["DEFAULT_VERTEXAI_LOCATION"] + del os.environ["DEFAULT_GOOGLE_APPLICATION_CREDENTIALS"] + + +@pytest.mark.asyncio +async def test_set_default_vertex_config(): + """Test set_default_vertex_config with various inputs""" + # Test with None config - set environment variables first + os.environ["DEFAULT_VERTEXAI_PROJECT"] = "env-project" + os.environ["DEFAULT_VERTEXAI_LOCATION"] = "env-location" + os.environ["DEFAULT_GOOGLE_APPLICATION_CREDENTIALS"] = "env-creds" + os.environ["GOOGLE_CREDS"] = "secret-creds" + + try: + # Test with None config + set_default_vertex_config() + from litellm.proxy.vertex_ai_endpoints.vertex_endpoints import ( + default_vertex_config, + ) + + assert default_vertex_config.vertex_project == "env-project" + assert default_vertex_config.vertex_location == "env-location" + assert default_vertex_config.vertex_credentials == "env-creds" + + # Test with valid config.yaml settings on vertex_config + test_config = { + "vertex_project": "my-project-123", + "vertex_location": "us-central1", + "vertex_credentials": "path/to/creds", + } + set_default_vertex_config(test_config) + from litellm.proxy.vertex_ai_endpoints.vertex_endpoints import ( + default_vertex_config, + ) + + assert default_vertex_config.vertex_project == "my-project-123" + assert default_vertex_config.vertex_location == "us-central1" + assert default_vertex_config.vertex_credentials == "path/to/creds" + + # Test with environment variable reference + test_config = { + "vertex_project": "my-project-123", + "vertex_location": "us-central1", + "vertex_credentials": "os.environ/GOOGLE_CREDS", + } + set_default_vertex_config(test_config) + from litellm.proxy.vertex_ai_endpoints.vertex_endpoints import ( + default_vertex_config, + ) + + assert default_vertex_config.vertex_credentials == "secret-creds" + + finally: + # Clean up environment variables + del os.environ["DEFAULT_VERTEXAI_PROJECT"] + del os.environ["DEFAULT_VERTEXAI_LOCATION"] + del os.environ["DEFAULT_GOOGLE_APPLICATION_CREDENTIALS"] + del os.environ["GOOGLE_CREDS"] diff --git a/tests/proxy_admin_ui_tests/conftest.py b/tests/proxy_admin_ui_tests/conftest.py new file mode 100644 index 000000000..eca0bc431 --- /dev/null +++ b/tests/proxy_admin_ui_tests/conftest.py @@ -0,0 +1,54 @@ +# conftest.py + +import importlib +import os +import sys + +import pytest + +sys.path.insert( + 0, os.path.abspath("../..") +) # Adds the parent directory to the system path +import litellm + + +@pytest.fixture(scope="function", autouse=True) +def setup_and_teardown(): + """ + This fixture reloads litellm before every function. To speed up testing by removing callbacks being chained. + """ + curr_dir = os.getcwd() # Get the current working directory + sys.path.insert( + 0, os.path.abspath("../..") + ) # Adds the project directory to the system path + + import litellm + from litellm import Router + + importlib.reload(litellm) + import asyncio + + loop = asyncio.get_event_loop_policy().new_event_loop() + asyncio.set_event_loop(loop) + print(litellm) + # from litellm import Router, completion, aembedding, acompletion, embedding + yield + + # Teardown code (executes after the yield point) + loop.close() # Close the loop created earlier + asyncio.set_event_loop(None) # Remove the reference to the loop + + +def pytest_collection_modifyitems(config, items): + # Separate tests in 'test_amazing_proxy_custom_logger.py' and other tests + custom_logger_tests = [ + item for item in items if "custom_logger" in item.parent.name + ] + other_tests = [item for item in items if "custom_logger" not in item.parent.name] + + # Sort tests based on their names + custom_logger_tests.sort(key=lambda x: x.name) + other_tests.sort(key=lambda x: x.name) + + # Reorder the items list + items[:] = custom_logger_tests + other_tests diff --git a/tests/proxy_admin_ui_tests/playwright.config.ts b/tests/proxy_admin_ui_tests/playwright.config.ts index c77897a02..3be77a319 100644 --- a/tests/proxy_admin_ui_tests/playwright.config.ts +++ b/tests/proxy_admin_ui_tests/playwright.config.ts @@ -13,6 +13,8 @@ import { defineConfig, devices } from '@playwright/test'; */ export default defineConfig({ testDir: './e2e_ui_tests', + testIgnore: ['**/tests/pass_through_tests/**', '../pass_through_tests/**/*'], + testMatch: '**/*.spec.ts', // Only run files ending in .spec.ts /* Run tests in files in parallel */ fullyParallel: true, /* Fail the build on CI if you accidentally left test.only in the source code. */ diff --git a/tests/proxy_admin_ui_tests/test_key_management.py b/tests/proxy_admin_ui_tests/test_key_management.py index b039a101b..7a2764e3f 100644 --- a/tests/proxy_admin_ui_tests/test_key_management.py +++ b/tests/proxy_admin_ui_tests/test_key_management.py @@ -542,3 +542,198 @@ async def test_list_teams(prisma_client): # Clean up await prisma_client.delete_data(team_id_list=[team_id], table_name="team") + + +def test_is_team_key(): + from litellm.proxy.management_endpoints.key_management_endpoints import _is_team_key + + assert _is_team_key(GenerateKeyRequest(team_id="test_team_id")) + assert not _is_team_key(GenerateKeyRequest(user_id="test_user_id")) + + +def test_team_key_generation_team_member_check(): + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _team_key_generation_check, + ) + from fastapi import HTTPException + from litellm.proxy._types import LiteLLM_TeamTableCachedObj + + litellm.key_generation_settings = { + "team_key_generation": {"allowed_team_member_roles": ["admin"]} + } + + team_table = LiteLLM_TeamTableCachedObj( + team_id="test_team_id", + team_alias="test_team_alias", + members_with_roles=[Member(role="admin", user_id="test_user_id")], + ) + + assert _team_key_generation_check( + team_table=team_table, + user_api_key_dict=UserAPIKeyAuth( + user_id="test_user_id", + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-1234", + team_member=Member(role="admin", user_id="test_user_id"), + ), + data=GenerateKeyRequest(), + ) + + team_table = LiteLLM_TeamTableCachedObj( + team_id="test_team_id", + team_alias="test_team_alias", + members_with_roles=[Member(role="user", user_id="test_user_id")], + ) + + with pytest.raises(HTTPException): + _team_key_generation_check( + team_table=team_table, + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-1234", + user_id="test_user_id", + team_member=Member(role="user", user_id="test_user_id"), + ), + data=GenerateKeyRequest(), + ) + + +@pytest.mark.parametrize( + "team_key_generation_settings, input_data, expected_result", + [ + ({"required_params": ["tags"]}, GenerateKeyRequest(tags=["test_tags"]), True), + ({}, GenerateKeyRequest(), True), + ( + {"required_params": ["models"]}, + GenerateKeyRequest(tags=["test_tags"]), + False, + ), + ], +) +@pytest.mark.parametrize("key_type", ["team_key", "personal_key"]) +def test_key_generation_required_params_check( + team_key_generation_settings, input_data, expected_result, key_type +): + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _team_key_generation_check, + _personal_key_generation_check, + ) + from litellm.types.utils import ( + TeamUIKeyGenerationConfig, + StandardKeyGenerationConfig, + PersonalUIKeyGenerationConfig, + ) + from litellm.proxy._types import LiteLLM_TeamTableCachedObj + from fastapi import HTTPException + + user_api_key_dict = UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-1234", + user_id="test_user_id", + team_id="test_team_id", + team_member=None, + ) + + team_table = LiteLLM_TeamTableCachedObj( + team_id="test_team_id", + team_alias="test_team_alias", + members_with_roles=[Member(role="admin", user_id="test_user_id")], + ) + + if key_type == "team_key": + litellm.key_generation_settings = StandardKeyGenerationConfig( + team_key_generation=TeamUIKeyGenerationConfig( + **team_key_generation_settings + ) + ) + elif key_type == "personal_key": + litellm.key_generation_settings = StandardKeyGenerationConfig( + personal_key_generation=PersonalUIKeyGenerationConfig( + **team_key_generation_settings + ) + ) + + if expected_result: + if key_type == "team_key": + assert _team_key_generation_check(team_table, user_api_key_dict, input_data) + elif key_type == "personal_key": + assert _personal_key_generation_check(user_api_key_dict, input_data) + else: + if key_type == "team_key": + with pytest.raises(HTTPException): + _team_key_generation_check(team_table, user_api_key_dict, input_data) + elif key_type == "personal_key": + with pytest.raises(HTTPException): + _personal_key_generation_check(user_api_key_dict, input_data) + + +def test_personal_key_generation_check(): + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _personal_key_generation_check, + ) + from fastapi import HTTPException + + litellm.key_generation_settings = { + "personal_key_generation": {"allowed_user_roles": ["proxy_admin"]} + } + + assert _personal_key_generation_check( + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234", user_id="admin" + ), + data=GenerateKeyRequest(), + ) + + with pytest.raises(HTTPException): + _personal_key_generation_check( + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, + api_key="sk-1234", + user_id="admin", + ), + data=GenerateKeyRequest(), + ) + + +def test_prepare_metadata_fields(): + from litellm.proxy.management_endpoints.key_management_endpoints import ( + prepare_metadata_fields, + ) + + new_metadata = {"test": "new"} + old_metadata = {"test": "test"} + + args = { + "data": UpdateKeyRequest( + key_alias=None, + duration=None, + models=[], + spend=None, + max_budget=None, + user_id=None, + team_id=None, + max_parallel_requests=None, + metadata=new_metadata, + tpm_limit=None, + rpm_limit=None, + budget_duration=None, + allowed_cache_controls=[], + soft_budget=None, + config={}, + permissions={}, + model_max_budget={}, + send_invite_email=None, + model_rpm_limit=None, + model_tpm_limit=None, + guardrails=None, + blocked=None, + aliases={}, + key="sk-1qGQUJJTcljeaPfzgWRrXQ", + tags=None, + ), + "non_default_values": {"metadata": new_metadata}, + "existing_metadata": {"tags": None, **old_metadata}, + } + + non_default_values = prepare_metadata_fields(**args) + assert non_default_values == {"metadata": new_metadata} diff --git a/tests/proxy_admin_ui_tests/test_role_based_access.py b/tests/proxy_admin_ui_tests/test_role_based_access.py index 609a3598d..ff73143bf 100644 --- a/tests/proxy_admin_ui_tests/test_role_based_access.py +++ b/tests/proxy_admin_ui_tests/test_role_based_access.py @@ -160,7 +160,7 @@ async def test_create_new_user_in_organization(prisma_client, user_role): response = await organization_member_add( data=OrganizationMemberAddRequest( organization_id=org_id, - member=Member(role=user_role, user_id=created_user_id), + member=OrgMember(role=user_role, user_id=created_user_id), ), http_request=None, ) @@ -220,7 +220,7 @@ async def test_org_admin_create_team_permissions(prisma_client): response = await organization_member_add( data=OrganizationMemberAddRequest( organization_id=org_id, - member=Member(role=LitellmUserRoles.ORG_ADMIN, user_id=created_user_id), + member=OrgMember(role=LitellmUserRoles.ORG_ADMIN, user_id=created_user_id), ), http_request=None, ) @@ -292,7 +292,7 @@ async def test_org_admin_create_user_permissions(prisma_client): response = await organization_member_add( data=OrganizationMemberAddRequest( organization_id=org_id, - member=Member(role=LitellmUserRoles.ORG_ADMIN, user_id=created_user_id), + member=OrgMember(role=LitellmUserRoles.ORG_ADMIN, user_id=created_user_id), ), http_request=None, ) @@ -323,7 +323,7 @@ async def test_org_admin_create_user_permissions(prisma_client): response = await organization_member_add( data=OrganizationMemberAddRequest( organization_id=org_id, - member=Member( + member=OrgMember( role=LitellmUserRoles.INTERNAL_USER, user_id=new_internal_user_for_org ), ), @@ -375,7 +375,7 @@ async def test_org_admin_create_user_team_wrong_org_permissions(prisma_client): response = await organization_member_add( data=OrganizationMemberAddRequest( organization_id=org1_id, - member=Member(role=LitellmUserRoles.ORG_ADMIN, user_id=created_user_id), + member=OrgMember(role=LitellmUserRoles.ORG_ADMIN, user_id=created_user_id), ), http_request=None, ) diff --git a/tests/proxy_unit_tests/example_config_yaml/config_with_include.yaml b/tests/proxy_unit_tests/example_config_yaml/config_with_include.yaml new file mode 100644 index 000000000..0a0c9434b --- /dev/null +++ b/tests/proxy_unit_tests/example_config_yaml/config_with_include.yaml @@ -0,0 +1,5 @@ +include: + - included_models.yaml + +litellm_settings: + callbacks: ["prometheus"] \ No newline at end of file diff --git a/tests/proxy_unit_tests/example_config_yaml/config_with_missing_include.yaml b/tests/proxy_unit_tests/example_config_yaml/config_with_missing_include.yaml new file mode 100644 index 000000000..40d3e9e7f --- /dev/null +++ b/tests/proxy_unit_tests/example_config_yaml/config_with_missing_include.yaml @@ -0,0 +1,5 @@ +include: + - non-existent-file.yaml + +litellm_settings: + callbacks: ["prometheus"] \ No newline at end of file diff --git a/tests/proxy_unit_tests/example_config_yaml/config_with_multiple_includes.yaml b/tests/proxy_unit_tests/example_config_yaml/config_with_multiple_includes.yaml new file mode 100644 index 000000000..c46adacd7 --- /dev/null +++ b/tests/proxy_unit_tests/example_config_yaml/config_with_multiple_includes.yaml @@ -0,0 +1,6 @@ +include: + - models_file_1.yaml + - models_file_2.yaml + +litellm_settings: + callbacks: ["prometheus"] \ No newline at end of file diff --git a/tests/proxy_unit_tests/example_config_yaml/included_models.yaml b/tests/proxy_unit_tests/example_config_yaml/included_models.yaml new file mode 100644 index 000000000..c1526b203 --- /dev/null +++ b/tests/proxy_unit_tests/example_config_yaml/included_models.yaml @@ -0,0 +1,4 @@ +model_list: + - model_name: included-model + litellm_params: + model: gpt-4 \ No newline at end of file diff --git a/tests/proxy_unit_tests/example_config_yaml/models_file_1.yaml b/tests/proxy_unit_tests/example_config_yaml/models_file_1.yaml new file mode 100644 index 000000000..344f67128 --- /dev/null +++ b/tests/proxy_unit_tests/example_config_yaml/models_file_1.yaml @@ -0,0 +1,4 @@ +model_list: + - model_name: included-model-1 + litellm_params: + model: gpt-4 \ No newline at end of file diff --git a/tests/proxy_unit_tests/example_config_yaml/models_file_2.yaml b/tests/proxy_unit_tests/example_config_yaml/models_file_2.yaml new file mode 100644 index 000000000..56bc3b1aa --- /dev/null +++ b/tests/proxy_unit_tests/example_config_yaml/models_file_2.yaml @@ -0,0 +1,4 @@ +model_list: + - model_name: included-model-2 + litellm_params: + model: gpt-3.5-turbo \ No newline at end of file diff --git a/tests/proxy_unit_tests/test_key_generate_prisma.py b/tests/proxy_unit_tests/test_key_generate_prisma.py index e6f8ca541..e1720654b 100644 --- a/tests/proxy_unit_tests/test_key_generate_prisma.py +++ b/tests/proxy_unit_tests/test_key_generate_prisma.py @@ -23,7 +23,7 @@ import os import sys import traceback import uuid -from datetime import datetime +from datetime import datetime, timezone from dotenv import load_dotenv from fastapi import Request @@ -1305,6 +1305,8 @@ def test_generate_and_update_key(prisma_client): data=UpdateKeyRequest( key=generated_key, models=["ada", "babbage", "curie", "davinci"], + budget_duration="1mo", + max_budget=100, ), ) @@ -1333,6 +1335,18 @@ def test_generate_and_update_key(prisma_client): } assert result["info"]["models"] == ["ada", "babbage", "curie", "davinci"] assert result["info"]["team_id"] == _team_2 + assert result["info"]["budget_duration"] == "1mo" + assert result["info"]["max_budget"] == 100 + + # budget_reset_at should be 30 days from now + assert result["info"]["budget_reset_at"] is not None + budget_reset_at = result["info"]["budget_reset_at"].replace( + tzinfo=timezone.utc + ) + current_time = datetime.now(timezone.utc) + + # assert budget_reset_at is 30 days from now + assert 31 >= (budget_reset_at - current_time).days >= 29 # cleanup - delete key delete_key_request = KeyRequest(keys=[generated_key]) @@ -2613,6 +2627,15 @@ async def test_create_update_team(prisma_client): _updated_info["budget_reset_at"], datetime.datetime ) + # budget_reset_at should be 2 days from now + budget_reset_at = _updated_info["budget_reset_at"].replace(tzinfo=timezone.utc) + current_time = datetime.datetime.now(timezone.utc) + + # assert budget_reset_at is 2 days from now + assert ( + abs((budget_reset_at - current_time).total_seconds() - 2 * 24 * 60 * 60) <= 10 + ) + # now hit team_info try: response = await team_info( @@ -2756,6 +2779,56 @@ async def test_update_user_role(prisma_client): print("result from user auth with new key", result) +@pytest.mark.asyncio() +async def test_update_user_unit_test(prisma_client): + """ + Unit test for /user/update + + Ensure that params are updated for UpdateUserRequest + """ + setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) + setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") + await litellm.proxy.proxy_server.prisma_client.connect() + key = await new_user( + data=NewUserRequest( + user_email="test@test.com", + ) + ) + + print(key) + + user_info = await user_update( + data=UpdateUserRequest( + user_id=key.user_id, + team_id="1234", + max_budget=100, + budget_duration="10d", + tpm_limit=100, + rpm_limit=100, + metadata={"very-new-metadata": "something"}, + ) + ) + + print("user_info", user_info) + assert user_info is not None + _user_info = user_info["data"].model_dump() + + assert _user_info["user_id"] == key.user_id + assert _user_info["team_id"] == "1234" + assert _user_info["max_budget"] == 100 + assert _user_info["budget_duration"] == "10d" + assert _user_info["tpm_limit"] == 100 + assert _user_info["rpm_limit"] == 100 + assert _user_info["metadata"] == {"very-new-metadata": "something"} + + # budget reset at should be 10 days from now + budget_reset_at = _user_info["budget_reset_at"].replace(tzinfo=timezone.utc) + current_time = datetime.now(timezone.utc) + assert ( + abs((budget_reset_at - current_time).total_seconds() - 10 * 24 * 60 * 60) <= 10 + ) + + @pytest.mark.asyncio() async def test_custom_api_key_header_name(prisma_client): """ """ @@ -2844,7 +2917,6 @@ async def test_generate_key_with_model_tpm_limit(prisma_client): "team": "litellm-team3", "model_tpm_limit": {"gpt-4": 100}, "model_rpm_limit": {"gpt-4": 2}, - "tags": None, } # Update model tpm_limit and rpm_limit @@ -2868,7 +2940,6 @@ async def test_generate_key_with_model_tpm_limit(prisma_client): "team": "litellm-team3", "model_tpm_limit": {"gpt-4": 200}, "model_rpm_limit": {"gpt-4": 3}, - "tags": None, } @@ -2908,7 +2979,6 @@ async def test_generate_key_with_guardrails(prisma_client): assert result["info"]["metadata"] == { "team": "litellm-team3", "guardrails": ["aporia-pre-call"], - "tags": None, } # Update model tpm_limit and rpm_limit @@ -2930,7 +3000,6 @@ async def test_generate_key_with_guardrails(prisma_client): assert result["info"]["metadata"] == { "team": "litellm-team3", "guardrails": ["aporia-pre-call", "aporia-post-call"], - "tags": None, } @@ -3550,3 +3619,152 @@ async def test_key_generate_with_secret_manager_call(prisma_client): ################################################################################ + + +@pytest.mark.asyncio +async def test_key_alias_uniqueness(prisma_client): + """ + Test that: + 1. We cannot create two keys with the same alias + 2. We cannot update a key to use an alias that's already taken + 3. We can update a key while keeping its existing alias + """ + setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) + setattr(litellm.proxy.proxy_server, "master_key", "sk-1234") + await litellm.proxy.proxy_server.prisma_client.connect() + + try: + # Create first key with an alias + unique_alias = f"test-alias-{uuid.uuid4()}" + key1 = await generate_key_fn( + data=GenerateKeyRequest(key_alias=unique_alias), + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + ) + + # Try to create second key with same alias - should fail + try: + key2 = await generate_key_fn( + data=GenerateKeyRequest(key_alias=unique_alias), + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + ) + pytest.fail("Should not be able to create a second key with the same alias") + except Exception as e: + print("vars(e)=", vars(e)) + assert "Unique key aliases across all keys are required" in str(e.message) + + # Create another key with different alias + another_alias = f"test-alias-{uuid.uuid4()}" + key3 = await generate_key_fn( + data=GenerateKeyRequest(key_alias=another_alias), + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + ) + + # Try to update key3 to use key1's alias - should fail + try: + await update_key_fn( + data=UpdateKeyRequest(key=key3.key, key_alias=unique_alias), + request=Request(scope={"type": "http"}), + ) + pytest.fail("Should not be able to update a key to use an existing alias") + except Exception as e: + assert "Unique key aliases across all keys are required" in str(e.message) + + # Update key1 with its own existing alias - should succeed + updated_key = await update_key_fn( + data=UpdateKeyRequest(key=key1.key, key_alias=unique_alias), + request=Request(scope={"type": "http"}), + ) + assert updated_key is not None + + except Exception as e: + print("got exceptions, e=", e) + print("vars(e)=", vars(e)) + pytest.fail(f"An unexpected error occurred: {str(e)}") + + +@pytest.mark.asyncio +async def test_enforce_unique_key_alias(prisma_client): + """ + Unit test the _enforce_unique_key_alias function: + 1. Test it allows unique aliases + 2. Test it blocks duplicate aliases for new keys + 3. Test it allows updating a key with its own existing alias + 4. Test it blocks updating a key with another key's alias + """ + from litellm.proxy.management_endpoints.key_management_endpoints import ( + _enforce_unique_key_alias, + ) + + setattr(litellm.proxy.proxy_server, "prisma_client", prisma_client) + await litellm.proxy.proxy_server.prisma_client.connect() + + try: + # Test 1: Allow unique alias + unique_alias = f"test-alias-{uuid.uuid4()}" + await _enforce_unique_key_alias( + key_alias=unique_alias, + prisma_client=prisma_client, + ) # Should pass + + # Create a key with this alias in the database + key1 = await generate_key_fn( + data=GenerateKeyRequest(key_alias=unique_alias), + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + ) + + # Test 2: Block duplicate alias for new key + try: + await _enforce_unique_key_alias( + key_alias=unique_alias, + prisma_client=prisma_client, + ) + pytest.fail("Should not allow duplicate alias") + except Exception as e: + assert "Unique key aliases across all keys are required" in str(e.message) + + # Test 3: Allow updating key with its own alias + await _enforce_unique_key_alias( + key_alias=unique_alias, + existing_key_token=hash_token(key1.key), + prisma_client=prisma_client, + ) # Should pass + + # Test 4: Block updating with another key's alias + another_key = await generate_key_fn( + data=GenerateKeyRequest(key_alias=f"test-alias-{uuid.uuid4()}"), + user_api_key_dict=UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + api_key="sk-1234", + user_id="1234", + ), + ) + + try: + await _enforce_unique_key_alias( + key_alias=unique_alias, + existing_key_token=another_key.key, + prisma_client=prisma_client, + ) + pytest.fail("Should not allow using another key's alias") + except Exception as e: + assert "Unique key aliases across all keys are required" in str(e.message) + + except Exception as e: + print("Unexpected error:", e) + pytest.fail(f"An unexpected error occurred: {str(e)}") diff --git a/tests/proxy_unit_tests/test_proxy_config_unit_test.py b/tests/proxy_unit_tests/test_proxy_config_unit_test.py index bb51ce726..e9923e89d 100644 --- a/tests/proxy_unit_tests/test_proxy_config_unit_test.py +++ b/tests/proxy_unit_tests/test_proxy_config_unit_test.py @@ -23,6 +23,8 @@ import logging from litellm.proxy.proxy_server import ProxyConfig +INVALID_FILES = ["config_with_missing_include.yaml"] + @pytest.mark.asyncio async def test_basic_reading_configs_from_files(): @@ -38,6 +40,9 @@ async def test_basic_reading_configs_from_files(): print(files) for file in files: + if file in INVALID_FILES: # these are intentionally invalid files + continue + print("reading file=", file) config_path = os.path.join(example_config_yaml_path, file) config = await proxy_config_instance.get_config(config_file_path=config_path) print(config) @@ -115,3 +120,67 @@ async def test_read_config_file_with_os_environ_vars(): os.environ[key] = _old_env_vars[key] else: del os.environ[key] + + +@pytest.mark.asyncio +async def test_basic_include_directive(): + """ + Test that the include directive correctly loads and merges configs + """ + proxy_config_instance = ProxyConfig() + current_path = os.path.dirname(os.path.abspath(__file__)) + config_path = os.path.join( + current_path, "example_config_yaml", "config_with_include.yaml" + ) + + config = await proxy_config_instance.get_config(config_file_path=config_path) + + # Verify the included model list was merged + assert len(config["model_list"]) > 0 + assert any( + model["model_name"] == "included-model" for model in config["model_list"] + ) + + # Verify original config settings remain + assert config["litellm_settings"]["callbacks"] == ["prometheus"] + + +@pytest.mark.asyncio +async def test_missing_include_file(): + """ + Test that a missing included file raises FileNotFoundError + """ + proxy_config_instance = ProxyConfig() + current_path = os.path.dirname(os.path.abspath(__file__)) + config_path = os.path.join( + current_path, "example_config_yaml", "config_with_missing_include.yaml" + ) + + with pytest.raises(FileNotFoundError): + await proxy_config_instance.get_config(config_file_path=config_path) + + +@pytest.mark.asyncio +async def test_multiple_includes(): + """ + Test that multiple files in the include list are all processed correctly + """ + proxy_config_instance = ProxyConfig() + current_path = os.path.dirname(os.path.abspath(__file__)) + config_path = os.path.join( + current_path, "example_config_yaml", "config_with_multiple_includes.yaml" + ) + + config = await proxy_config_instance.get_config(config_file_path=config_path) + + # Verify models from both included files are present + assert len(config["model_list"]) == 2 + assert any( + model["model_name"] == "included-model-1" for model in config["model_list"] + ) + assert any( + model["model_name"] == "included-model-2" for model in config["model_list"] + ) + + # Verify original config settings remain + assert config["litellm_settings"]["callbacks"] == ["prometheus"] diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py index d70962858..bde5ca050 100644 --- a/tests/proxy_unit_tests/test_proxy_server.py +++ b/tests/proxy_unit_tests/test_proxy_server.py @@ -1014,7 +1014,11 @@ async def test_create_team_member_add(prisma_client, new_member_method): with patch( "litellm.proxy.proxy_server.prisma_client.db.litellm_usertable", new_callable=AsyncMock, - ) as mock_litellm_usertable: + ) as mock_litellm_usertable, patch( + "litellm.proxy.auth.auth_checks._get_team_object_from_user_api_key_cache", + new=AsyncMock(return_value=team_obj), + ) as mock_team_obj: + mock_client = AsyncMock( return_value=LiteLLM_UserTable( user_id="1234", max_budget=100, user_email="1234" @@ -1193,7 +1197,10 @@ async def test_create_team_member_add_team_admin( with patch( "litellm.proxy.proxy_server.prisma_client.db.litellm_usertable", new_callable=AsyncMock, - ) as mock_litellm_usertable: + ) as mock_litellm_usertable, patch( + "litellm.proxy.auth.auth_checks._get_team_object_from_user_api_key_cache", + new=AsyncMock(return_value=team_obj), + ) as mock_team_obj: mock_client = AsyncMock( return_value=LiteLLM_UserTable( user_id="1234", max_budget=100, user_email="1234" @@ -2118,3 +2125,196 @@ async def test_proxy_server_prisma_setup_invalid_db(): if _old_db_url: os.environ["DATABASE_URL"] = _old_db_url + + +@pytest.mark.asyncio +async def test_async_log_proxy_authentication_errors(): + """ + Test if async_log_proxy_authentication_errors correctly logs authentication errors through custom loggers + """ + import json + from fastapi import Request + from litellm.proxy.utils import ProxyLogging + from litellm.caching import DualCache + from litellm.integrations.custom_logger import CustomLogger + + # Create a mock custom logger to verify it's called + class MockCustomLogger(CustomLogger): + def __init__(self): + self.called = False + self.exception_logged = None + self.request_data_logged = None + self.user_api_key_dict_logged = None + + async def async_post_call_failure_hook( + self, + request_data: dict, + original_exception: Exception, + user_api_key_dict: UserAPIKeyAuth, + ): + self.called = True + self.exception_logged = original_exception + self.request_data_logged = request_data + print("logged request_data", request_data) + if isinstance(request_data, AsyncMock): + self.request_data_logged = ( + await request_data() + ) # get the actual value from AsyncMock + else: + self.request_data_logged = request_data + self.user_api_key_dict_logged = user_api_key_dict + + # Create test data + test_data = {"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]} + + # Create a mock request + request = Request(scope={"type": "http", "method": "POST"}) + request._json = AsyncMock(return_value=test_data) + + # Create a test exception + test_exception = Exception("Invalid API Key") + + # Initialize ProxyLogging + mock_logger = MockCustomLogger() + litellm.callbacks = [mock_logger] + proxy_logging_obj = ProxyLogging(user_api_key_cache=DualCache()) + + # Call the method + await proxy_logging_obj.async_log_proxy_authentication_errors( + original_exception=test_exception, + request=request, + parent_otel_span=None, + api_key="test-key", + ) + + # Verify the mock logger was called with correct parameters + assert mock_logger.called == True + assert mock_logger.exception_logged == test_exception + assert mock_logger.request_data_logged == test_data + assert mock_logger.user_api_key_dict_logged is not None + assert ( + mock_logger.user_api_key_dict_logged.token is not None + ) # token should be hashed + + +@pytest.mark.asyncio +async def test_async_log_proxy_authentication_errors_get_request(): + """ + Test if async_log_proxy_authentication_errors correctly handles GET requests + that don't have a JSON body + """ + import json + from fastapi import Request + from litellm.proxy.utils import ProxyLogging + from litellm.caching import DualCache + from litellm.integrations.custom_logger import CustomLogger + + class MockCustomLogger(CustomLogger): + def __init__(self): + self.called = False + self.exception_logged = None + self.request_data_logged = None + self.user_api_key_dict_logged = None + + async def async_post_call_failure_hook( + self, + request_data: dict, + original_exception: Exception, + user_api_key_dict: UserAPIKeyAuth, + ): + self.called = True + self.exception_logged = original_exception + self.request_data_logged = request_data + self.user_api_key_dict_logged = user_api_key_dict + + # Create a mock GET request + request = Request(scope={"type": "http", "method": "GET"}) + + # Mock the json() method to raise JSONDecodeError + async def mock_json(): + raise json.JSONDecodeError("Expecting value", "", 0) + + request.json = mock_json + + # Create a test exception + test_exception = Exception("Invalid API Key") + + # Initialize ProxyLogging + mock_logger = MockCustomLogger() + litellm.callbacks = [mock_logger] + proxy_logging_obj = ProxyLogging(user_api_key_cache=DualCache()) + + # Call the method + await proxy_logging_obj.async_log_proxy_authentication_errors( + original_exception=test_exception, + request=request, + parent_otel_span=None, + api_key="test-key", + ) + + # Verify the mock logger was called with correct parameters + assert mock_logger.called == True + assert mock_logger.exception_logged == test_exception + assert mock_logger.user_api_key_dict_logged is not None + assert mock_logger.user_api_key_dict_logged.token is not None + + +@pytest.mark.asyncio +async def test_async_log_proxy_authentication_errors_no_api_key(): + """ + Test if async_log_proxy_authentication_errors correctly handles requests + with no API key provided + """ + from fastapi import Request + from litellm.proxy.utils import ProxyLogging + from litellm.caching import DualCache + from litellm.integrations.custom_logger import CustomLogger + + class MockCustomLogger(CustomLogger): + def __init__(self): + self.called = False + self.exception_logged = None + self.request_data_logged = None + self.user_api_key_dict_logged = None + + async def async_post_call_failure_hook( + self, + request_data: dict, + original_exception: Exception, + user_api_key_dict: UserAPIKeyAuth, + ): + self.called = True + self.exception_logged = original_exception + self.request_data_logged = request_data + self.user_api_key_dict_logged = user_api_key_dict + + # Create test data + test_data = {"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]} + + # Create a mock request + request = Request(scope={"type": "http", "method": "POST"}) + request._json = AsyncMock(return_value=test_data) + + # Create a test exception + test_exception = Exception("No API Key Provided") + + # Initialize ProxyLogging + mock_logger = MockCustomLogger() + litellm.callbacks = [mock_logger] + proxy_logging_obj = ProxyLogging(user_api_key_cache=DualCache()) + + # Call the method with api_key=None + await proxy_logging_obj.async_log_proxy_authentication_errors( + original_exception=test_exception, + request=request, + parent_otel_span=None, + api_key=None, + ) + + # Verify the mock logger was called with correct parameters + assert mock_logger.called == True + assert mock_logger.exception_logged == test_exception + assert mock_logger.user_api_key_dict_logged is not None + assert ( + mock_logger.user_api_key_dict_logged.token == "" + ) # Empty token for no API key diff --git a/tests/proxy_unit_tests/test_proxy_utils.py b/tests/proxy_unit_tests/test_proxy_utils.py index 607e54225..6de47b6ee 100644 --- a/tests/proxy_unit_tests/test_proxy_utils.py +++ b/tests/proxy_unit_tests/test_proxy_utils.py @@ -444,7 +444,7 @@ def test_foward_litellm_user_info_to_backend_llm_call(): def test_update_internal_user_params(): from litellm.proxy.management_endpoints.internal_user_endpoints import ( - _update_internal_user_params, + _update_internal_new_user_params, ) from litellm.proxy._types import NewUserRequest @@ -456,7 +456,7 @@ def test_update_internal_user_params(): data = NewUserRequest(user_role="internal_user", user_email="krrish3@berri.ai") data_json = data.model_dump() - updated_data_json = _update_internal_user_params(data_json, data) + updated_data_json = _update_internal_new_user_params(data_json, data) assert updated_data_json["models"] == litellm.default_internal_user_params["models"] assert ( updated_data_json["max_budget"] @@ -530,7 +530,7 @@ def test_prepare_key_update_data(): data = UpdateKeyRequest(key="test_key", metadata=None) updated_data = prepare_key_update_data(data, existing_key_row) - assert updated_data["metadata"] == None + assert updated_data["metadata"] is None @pytest.mark.parametrize( @@ -574,3 +574,108 @@ def test_get_docs_url(env_vars, expected_url): result = _get_docs_url() assert result == expected_url + + +@pytest.mark.parametrize( + "request_tags, tags_to_add, expected_tags", + [ + (None, None, []), # both None + (["tag1", "tag2"], None, ["tag1", "tag2"]), # tags_to_add is None + (None, ["tag3", "tag4"], ["tag3", "tag4"]), # request_tags is None + ( + ["tag1", "tag2"], + ["tag3", "tag4"], + ["tag1", "tag2", "tag3", "tag4"], + ), # both have unique tags + ( + ["tag1", "tag2"], + ["tag2", "tag3"], + ["tag1", "tag2", "tag3"], + ), # overlapping tags + ([], [], []), # both empty lists + ("not_a_list", ["tag1"], ["tag1"]), # request_tags invalid type + (["tag1"], "not_a_list", ["tag1"]), # tags_to_add invalid type + ( + ["tag1"], + ["tag1", "tag2"], + ["tag1", "tag2"], + ), # duplicate tags in inputs + ], +) +def test_merge_tags(request_tags, tags_to_add, expected_tags): + from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup + + result = LiteLLMProxyRequestSetup._merge_tags( + request_tags=request_tags, tags_to_add=tags_to_add + ) + + assert isinstance(result, list) + assert sorted(result) == sorted(expected_tags) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "key_tags, request_tags, expected_tags", + [ + # exact duplicates + (["tag1", "tag2", "tag3"], ["tag1", "tag2", "tag3"], ["tag1", "tag2", "tag3"]), + # partial duplicates + ( + ["tag1", "tag2", "tag3"], + ["tag2", "tag3", "tag4"], + ["tag1", "tag2", "tag3", "tag4"], + ), + # duplicates within key tags + (["tag1", "tag2"], ["tag3", "tag4"], ["tag1", "tag2", "tag3", "tag4"]), + # duplicates within request tags + (["tag1", "tag2"], ["tag2", "tag3", "tag4"], ["tag1", "tag2", "tag3", "tag4"]), + # case sensitive duplicates + (["Tag1", "TAG2"], ["tag1", "tag2"], ["Tag1", "TAG2", "tag1", "tag2"]), + ], +) +async def test_add_litellm_data_to_request_duplicate_tags( + key_tags, request_tags, expected_tags +): + """ + Test to verify duplicate tags between request and key metadata are handled correctly + + + Aggregation logic when checking spend can be impacted if duplicate tags are not handled correctly. + + User feedback: + "If I register my key with tag1 and + also pass the same tag1 when using the key + then I see tag1 twice in the + LiteLLM_SpendLogs table request_tags column. This can mess up aggregation logic" + """ + mock_request = Mock(spec=Request) + mock_request.url.path = "/chat/completions" + mock_request.query_params = {} + mock_request.headers = {} + + # Setup key with tags in metadata + user_api_key_dict = UserAPIKeyAuth( + api_key="test_api_key", + user_id="test_user_id", + org_id="test_org_id", + metadata={"tags": key_tags}, + ) + + # Setup request data with tags + data = {"metadata": {"tags": request_tags}} + + # Process request + proxy_config = Mock() + result = await add_litellm_data_to_request( + data=data, + request=mock_request, + user_api_key_dict=user_api_key_dict, + proxy_config=proxy_config, + ) + + # Verify results + assert "metadata" in result + assert "tags" in result["metadata"] + assert sorted(result["metadata"]["tags"]) == sorted( + expected_tags + ), f"Expected {expected_tags}, got {result['metadata']['tags']}" diff --git a/tests/proxy_unit_tests/test_unit_test_proxy_hooks.py b/tests/proxy_unit_tests/test_unit_test_proxy_hooks.py new file mode 100644 index 000000000..095b15368 --- /dev/null +++ b/tests/proxy_unit_tests/test_unit_test_proxy_hooks.py @@ -0,0 +1,111 @@ +import asyncio +import os +import sys +from unittest.mock import Mock, patch, AsyncMock +import pytest +from fastapi import Request +from litellm.proxy.utils import _get_redoc_url, _get_docs_url + +sys.path.insert(0, os.path.abspath("../..")) +import litellm + + +@pytest.mark.asyncio +async def test_disable_error_logs(): + """ + Test that the error logs are not written to the database when disable_error_logs is True + """ + # Mock the necessary components + mock_prisma_client = AsyncMock() + mock_general_settings = {"disable_error_logs": True} + + with patch( + "litellm.proxy.proxy_server.general_settings", mock_general_settings + ), patch("litellm.proxy.proxy_server.prisma_client", mock_prisma_client): + + # Create a test exception + test_exception = Exception("Test error") + test_kwargs = { + "model": "gpt-4", + "exception": test_exception, + "optional_params": {}, + "litellm_params": {"metadata": {}}, + } + + # Call the failure handler + from litellm.proxy.proxy_server import _PROXY_failure_handler + + await _PROXY_failure_handler( + kwargs=test_kwargs, + completion_response=None, + start_time="2024-01-01", + end_time="2024-01-01", + ) + + # Verify prisma client was not called to create error logs + if hasattr(mock_prisma_client, "db"): + assert not mock_prisma_client.db.litellm_errorlogs.create.called + + +@pytest.mark.asyncio +async def test_disable_spend_logs(): + """ + Test that the spend logs are not written to the database when disable_spend_logs is True + """ + # Mock the necessary components + mock_prisma_client = Mock() + mock_prisma_client.spend_log_transactions = [] + + with patch("litellm.proxy.proxy_server.disable_spend_logs", True), patch( + "litellm.proxy.proxy_server.prisma_client", mock_prisma_client + ): + from litellm.proxy.proxy_server import update_database + + # Call update_database with disable_spend_logs=True + await update_database( + token="fake-token", + response_cost=0.1, + user_id="user123", + completion_response=None, + start_time="2024-01-01", + end_time="2024-01-01", + ) + # Verify no spend logs were added + assert len(mock_prisma_client.spend_log_transactions) == 0 + + +@pytest.mark.asyncio +async def test_enable_error_logs(): + """ + Test that the error logs are written to the database when disable_error_logs is False + """ + # Mock the necessary components + mock_prisma_client = AsyncMock() + mock_general_settings = {"disable_error_logs": False} + + with patch( + "litellm.proxy.proxy_server.general_settings", mock_general_settings + ), patch("litellm.proxy.proxy_server.prisma_client", mock_prisma_client): + + # Create a test exception + test_exception = Exception("Test error") + test_kwargs = { + "model": "gpt-4", + "exception": test_exception, + "optional_params": {}, + "litellm_params": {"metadata": {}}, + } + + # Call the failure handler + from litellm.proxy.proxy_server import _PROXY_failure_handler + + await _PROXY_failure_handler( + kwargs=test_kwargs, + completion_response=None, + start_time="2024-01-01", + end_time="2024-01-01", + ) + + # Verify prisma client was called to create error logs + if hasattr(mock_prisma_client, "db"): + assert mock_prisma_client.db.litellm_errorlogs.create.called diff --git a/tests/router_unit_tests/test_router_endpoints.py b/tests/router_unit_tests/test_router_endpoints.py index 4c9fc8f35..19949ddba 100644 --- a/tests/router_unit_tests/test_router_endpoints.py +++ b/tests/router_unit_tests/test_router_endpoints.py @@ -215,7 +215,7 @@ async def test_rerank_endpoint(model_list): @pytest.mark.parametrize("sync_mode", [True, False]) @pytest.mark.asyncio -async def test_text_completion_endpoint(model_list, sync_mode): +async def test_aaaaatext_completion_endpoint(model_list, sync_mode): router = Router(model_list=model_list) if sync_mode: diff --git a/tests/router_unit_tests/test_router_helper_utils.py b/tests/router_unit_tests/test_router_helper_utils.py index 8a35f5652..f247c33e3 100644 --- a/tests/router_unit_tests/test_router_helper_utils.py +++ b/tests/router_unit_tests/test_router_helper_utils.py @@ -396,7 +396,8 @@ async def test_deployment_callback_on_success(model_list, sync_mode): assert tpm_key is not None -def test_deployment_callback_on_failure(model_list): +@pytest.mark.asyncio +async def test_deployment_callback_on_failure(model_list): """Test if the '_deployment_callback_on_failure' function is working correctly""" import time @@ -418,6 +419,18 @@ def test_deployment_callback_on_failure(model_list): assert isinstance(result, bool) assert result is False + model_response = router.completion( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "Hello, how are you?"}], + mock_response="I'm fine, thank you!", + ) + result = await router.async_deployment_callback_on_failure( + kwargs=kwargs, + completion_response=model_response, + start_time=time.time(), + end_time=time.time(), + ) + def test_log_retry(model_list): """Test if the '_log_retry' function is working correctly""" @@ -1027,8 +1040,11 @@ def test_pattern_match_deployment_set_model_name( async def test_pass_through_moderation_endpoint_factory(model_list): router = Router(model_list=model_list) response = await router._pass_through_moderation_endpoint_factory( - original_function=litellm.amoderation, input="this is valid good text" + original_function=litellm.amoderation, + input="this is valid good text", + model=None, ) + assert response is not None @pytest.mark.parametrize( diff --git a/tests/test_config.py b/tests/test_config.py index 03de4653f..888949982 100644 --- a/tests/test_config.py +++ b/tests/test_config.py @@ -20,6 +20,7 @@ async def config_update(session): "success_callback": ["langfuse"], }, "environment_variables": { + "LANGFUSE_HOST": os.environ["LANGFUSE_HOST"], "LANGFUSE_PUBLIC_KEY": os.environ["LANGFUSE_PUBLIC_KEY"], "LANGFUSE_SECRET_KEY": os.environ["LANGFUSE_SECRET_KEY"], }, @@ -98,6 +99,7 @@ async def test_team_logging(): import langfuse langfuse_client = langfuse.Langfuse( + host=os.getenv("LANGFUSE_HOST"), public_key=os.getenv("LANGFUSE_PUBLIC_KEY"), secret_key=os.getenv("LANGFUSE_SECRET_KEY"), ) diff --git a/tests/test_keys.py b/tests/test_keys.py index a569634bc..eaf9369d8 100644 --- a/tests/test_keys.py +++ b/tests/test_keys.py @@ -300,6 +300,7 @@ async def test_key_update(metadata): get_key=key, metadata=metadata, ) + print(f"updated_key['metadata']: {updated_key['metadata']}") assert updated_key["metadata"] == metadata await update_proxy_budget(session=session) # resets proxy spend await chat_completion(session=session, key=key) diff --git a/tests/test_organizations.py b/tests/test_organizations.py index 9bf6660d6..588d838f2 100644 --- a/tests/test_organizations.py +++ b/tests/test_organizations.py @@ -39,13 +39,12 @@ async def list_organization(session, i): response_json = await response.json() print(f"Response {i} (Status code: {status}):") - print(response_json) print() if status != 200: raise Exception(f"Request {i} did not return a 200 status code: {status}") - return await response.json() + return response_json @pytest.mark.asyncio diff --git a/tests/test_spend_logs.py b/tests/test_spend_logs.py index a5db51a88..4b0c357f3 100644 --- a/tests/test_spend_logs.py +++ b/tests/test_spend_logs.py @@ -114,7 +114,7 @@ async def test_spend_logs(): async def get_predict_spend_logs(session): - url = f"http://0.0.0.0:4000/global/predict/spend/logs" + url = "http://0.0.0.0:4000/global/predict/spend/logs" headers = {"Authorization": "Bearer sk-1234", "Content-Type": "application/json"} data = { "data": [ @@ -155,6 +155,7 @@ async def get_spend_report(session, start_date, end_date): return await response.json() +@pytest.mark.skip(reason="datetime in ci/cd gets set weirdly") @pytest.mark.asyncio async def test_get_predicted_spend_logs(): """ diff --git a/tests/test_team_logging.py b/tests/test_team_logging.py index cf0fa6354..516b6fa13 100644 --- a/tests/test_team_logging.py +++ b/tests/test_team_logging.py @@ -61,6 +61,7 @@ async def chat_completion(session, key, model="azure-gpt-3.5", request_metadata= raise Exception(f"Request did not return a 200 status code: {status}") +@pytest.mark.skip(reason="flaky test - covered by simpler unit testing.") @pytest.mark.asyncio @pytest.mark.flaky(retries=12, delay=2) async def test_aaateam_logging(): @@ -94,12 +95,15 @@ async def test_aaateam_logging(): # Test - if the logs were sent to the correct team on langfuse import langfuse + print(f"langfuse_public_key: {os.getenv('LANGFUSE_PROJECT1_PUBLIC')}") + print(f"langfuse_secret_key: {os.getenv('LANGFUSE_HOST')}") langfuse_client = langfuse.Langfuse( public_key=os.getenv("LANGFUSE_PROJECT1_PUBLIC"), secret_key=os.getenv("LANGFUSE_PROJECT1_SECRET"), + host="https://us.cloud.langfuse.com", ) - await asyncio.sleep(10) + await asyncio.sleep(30) print(f"searching for trace_id={_trace_id} on langfuse") @@ -163,7 +167,7 @@ async def test_team_2logging(): host=langfuse_host, ) - await asyncio.sleep(10) + await asyncio.sleep(30) print(f"searching for trace_id={_trace_id} on langfuse") @@ -177,6 +181,7 @@ async def test_team_2logging(): langfuse_client_1 = langfuse.Langfuse( public_key=os.getenv("LANGFUSE_PROJECT1_PUBLIC"), secret_key=os.getenv("LANGFUSE_PROJECT1_SECRET"), + host="https://us.cloud.langfuse.com", ) generations_team_1 = langfuse_client_1.get_generations( diff --git a/ui/litellm-dashboard/out/404.html b/ui/litellm-dashboard/out/404.html deleted file mode 100644 index 09dcdd244..000000000 --- a/ui/litellm-dashboard/out/404.html +++ /dev/null @@ -1 +0,0 @@ -404: This page could not be found.LiteLLM Dashboard

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