Merge pull request #5457 from BerriAI/litellm_track_spend_logs_for_vertex_pass_through_endpoints

[Feat-Proxy] track spend logs for vertex pass through endpoints

.circleci/config.yml

@@ -251,7 +251,7 @@ jobs:
           command: |
             pwd
             ls
-            python -m pytest -vv tests/ -x --junitxml=test-results/junit.xml --durations=5 --ignore=tests/otel_tests
+            python -m pytest -s -vv tests/ -x --junitxml=test-results/junit.xml --durations=5 --ignore=tests/otel_tests --ignore=tests/pass_through_tests
           no_output_timeout: 120m
 
       # Store test results
@@ -363,6 +363,100 @@ jobs:
       - store_test_results:
           path: test-results
 
+  proxy_pass_through_endpoint_tests:
+    machine:
+      image: ubuntu-2204:2023.10.1
+    resource_class: xlarge
+    working_directory: ~/project
+    steps:
+      - checkout
+      - run:
+          name: Install Docker CLI (In case it's not already installed)
+          command: |
+            sudo apt-get update
+            sudo apt-get install -y docker-ce docker-ce-cli containerd.io
+      - run:
+          name: Install Python 3.9
+          command: |
+            curl https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh --output miniconda.sh
+            bash miniconda.sh -b -p $HOME/miniconda
+            export PATH="$HOME/miniconda/bin:$PATH"
+            conda init bash
+            source ~/.bashrc
+            conda create -n myenv python=3.9 -y
+            conda activate myenv
+            python --version
+      - run:
+          name: Install Dependencies
+          command: |
+            pip install "pytest==7.3.1"
+            pip install "pytest-retry==1.6.3"
+            pip install "pytest-asyncio==0.21.1"
+            pip install "google-cloud-aiplatform==1.43.0"
+            pip install aiohttp
+            pip install "openai==1.40.0"
+            python -m pip install --upgrade pip
+            pip install "pydantic==2.7.1"
+            pip install "pytest==7.3.1"
+            pip install "pytest-mock==3.12.0"
+            pip install "pytest-asyncio==0.21.1"
+            pip install "boto3==1.34.34"
+            pip install mypy
+            pip install pyarrow
+            pip install numpydoc
+            pip install prisma            
+            pip install fastapi            
+            pip install jsonschema   
+            pip install "httpx==0.24.1"
+            pip install "anyio==3.7.1"
+            pip install "asyncio==3.4.3"
+            pip install "PyGithub==1.59.1"
+      - run:
+          name: Build Docker image
+          command: docker build -t my-app:latest -f Dockerfile.database .
+      - run:
+          name: Run Docker container
+          command: |
+            docker run -d \
+              -p 4000:4000 \
+              -e DATABASE_URL=$PROXY_DATABASE_URL \
+              -e LITELLM_MASTER_KEY="sk-1234" \
+              -e OPENAI_API_KEY=$OPENAI_API_KEY \
+              -e LITELLM_LICENSE=$LITELLM_LICENSE \
+              --name my-app \
+              -v $(pwd)/litellm/proxy/example_config_yaml/pass_through_config.yaml:/app/config.yaml \
+              -v $(pwd)/litellm/proxy/example_config_yaml/custom_auth_basic.py:/app/custom_auth_basic.py \
+              my-app:latest \
+              --config /app/config.yaml \
+              --port 4000 \
+              --detailed_debug \
+      - run:
+          name: Install curl and dockerize
+          command: |
+            sudo apt-get update
+            sudo apt-get install -y curl
+            sudo wget https://github.com/jwilder/dockerize/releases/download/v0.6.1/dockerize-linux-amd64-v0.6.1.tar.gz
+            sudo tar -C /usr/local/bin -xzvf dockerize-linux-amd64-v0.6.1.tar.gz
+            sudo rm dockerize-linux-amd64-v0.6.1.tar.gz
+      - run:
+          name: Start outputting logs
+          command: docker logs -f my-app
+          background: true
+      - run:
+          name: Wait for app to be ready
+          command: dockerize -wait http://localhost:4000 -timeout 5m
+      - run:
+          name: Run tests
+          command: |
+            pwd
+            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
+
   publish_to_pypi:
     docker:
       - image: cimg/python:3.8
@@ -457,6 +551,12 @@ workflows:
               only:
                 - main
                 - /litellm_.*/
+      - proxy_pass_through_endpoint_tests:
+          filters:
+            branches:
+              only:
+                - main
+                - /litellm_.*/
       - installing_litellm_on_python:
           filters:
             branches:
@@ -468,6 +568,7 @@ workflows:
             - local_testing
             - build_and_test
             - proxy_log_to_otel_tests
+            - proxy_pass_through_endpoint_tests
           filters:
             branches:
               only:

litellm/proxy/example_config_yaml/custom_auth.py

@@ -1,7 +1,9 @@
-from litellm.proxy._types import UserAPIKeyAuth, GenerateKeyRequest
-from fastapi import Request
 import os
 
+from fastapi import Request
+
+from litellm.proxy._types import GenerateKeyRequest, UserAPIKeyAuth
+
 
 async def user_api_key_auth(request: Request, api_key: str) -> UserAPIKeyAuth:
     try:

litellm/proxy/example_config_yaml/custom_auth_basic.py

@@ -0,0 +1,14 @@
+from fastapi import Request
+
+from litellm.proxy._types import UserAPIKeyAuth
+
+
+async def user_api_key_auth(request: Request, api_key: str) -> UserAPIKeyAuth:
+    try:
+        return UserAPIKeyAuth(
+            api_key="best-api-key-ever",
+            user_id="best-user-id-ever",
+            team_id="best-team-id-ever",
+        )
+    except:
+        raise Exception

litellm/proxy/example_config_yaml/pass_through_config.yaml

@@ -0,0 +1,9 @@
+model_list:
+ - model_name: fake-openai-endpoint
+   litellm_params:
+     model: openai/fake
+     api_key: fake-key
+     api_base: https://exampleopenaiendpoint-production.up.railway.app/
+general_settings: 
+ master_key: sk-1234 
+ custom_auth: custom_auth_basic.user_api_key_auth

litellm/proxy/pass_through_endpoints/pass_through_endpoints.py

@@ -3,6 +3,7 @@ import asyncio
 import json
 import traceback
 from base64 import b64encode
+from datetime import datetime
 from typing import AsyncIterable, List, Optional
 
 import httpx
@@ -20,6 +21,7 @@ from fastapi.responses import StreamingResponse
 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.proxy._types import (
     ConfigFieldInfo,
     ConfigFieldUpdate,
@@ -30,8 +32,12 @@ from litellm.proxy._types import (
 )
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
 
+from .success_handler import PassThroughEndpointLogging
+
 router = APIRouter()
 
+pass_through_endpoint_logging = PassThroughEndpointLogging()
+
 
 async def set_env_variables_in_header(custom_headers: dict):
     """
@@ -330,7 +336,7 @@ async def pass_through_request(
         async_client = httpx.AsyncClient(timeout=600)
 
         # create logging object
-        start_time = time.time()
+        start_time = datetime.now()
         logging_obj = Logging(
             model="unknown",
             messages=[{"role": "user", "content": "no-message-pass-through-endpoint"}],
@@ -473,12 +479,15 @@ async def pass_through_request(
         content = await response.aread()
 
         ## LOG SUCCESS
-        end_time = time.time()
+        end_time = datetime.now()
 
-        await logging_obj.async_success_handler(
+        await pass_through_endpoint_logging.pass_through_async_success_handler(
+            httpx_response=response,
+            url_route=str(url),
             result="",
             start_time=start_time,
             end_time=end_time,
+            logging_obj=logging_obj,
             cache_hit=False,
         )
 

litellm/proxy/pass_through_endpoints/success_handler.py

@@ -0,0 +1,105 @@
+import re
+from datetime import datetime
+
+import httpx
+
+import litellm
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.llms.vertex_ai_and_google_ai_studio.gemini.vertex_and_google_ai_studio_gemini import (
+    VertexLLM,
+)
+from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+
+
+class PassThroughEndpointLogging:
+    def __init__(self):
+        self.TRACKED_VERTEX_ROUTES = [
+            "generateContent",
+            "streamGenerateContent",
+            "predict",
+        ]
+
+    async def pass_through_async_success_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 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,
+            )
+        else:
+            await logging_obj.async_success_handler(
+                result="",
+                start_time=start_time,
+                end_time=end_time,
+                cache_hit=False,
+            )
+
+    def is_vertex_route(self, url_route: str):
+        for route in self.TRACKED_VERTEX_ROUTES:
+            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 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 = VertexLLM()
+            litellm_model_response: litellm.ModelResponse = (
+                instance_of_vertex_llm._process_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
+            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,
+            )

litellm/proxy/proxy_config.yaml

@@ -21,3 +21,4 @@ router_settings:
 
 general_settings: 
  master_key: sk-1234 
+ custom_auth: example_config_yaml.custom_auth_basic.user_api_key_auth

litellm/proxy/proxy_server.py

@@ -696,10 +696,10 @@ def load_from_azure_key_vault(use_azure_key_vault: bool = False):
 def cost_tracking():
     global prisma_client, custom_db_client
     if prisma_client is not None or custom_db_client is not None:
-        if isinstance(litellm.success_callback, list):
+        if isinstance(litellm._async_success_callback, list):
             verbose_proxy_logger.debug("setting litellm success callback to track cost")
-            if (_PROXY_track_cost_callback) not in litellm.success_callback:  # type: ignore
+            if (_PROXY_track_cost_callback) not in litellm._async_success_callback:  # type: ignore
-                litellm.success_callback.append(_PROXY_track_cost_callback)  # type: ignore
+                litellm._async_success_callback.append(_PROXY_track_cost_callback)  # type: ignore
 
 
 async def _PROXY_failure_handler(

litellm/tests/test_custom_callback_input.py

@@ -976,6 +976,7 @@ async def test_async_embedding_bedrock():
 # CACHING
 ## Test Azure - completion, embedding
 @pytest.mark.asyncio
+@pytest.mark.flaky(retries=3, delay=1)
 async def test_async_completion_azure_caching():
     litellm.set_verbose = True
     customHandler_caching = CompletionCustomHandler()

tests/pass_through_tests/test_vertex_ai.py

@@ -0,0 +1,119 @@
+"""
+Test Vertex AI Pass Through
+
+1. use Credentials client side, Assert SpendLog was created
+"""
+
+import vertexai
+from vertexai.preview.generative_models import GenerativeModel
+import tempfile
+import json
+import os
+import pytest
+import asyncio
+
+
+# Path to your service account JSON file
+SERVICE_ACCOUNT_FILE = "path/to/your/service-account.json"
+
+
+def load_vertex_ai_credentials():
+    # Define the path to the vertex_key.json file
+    print("loading vertex ai credentials")
+    filepath = os.path.dirname(os.path.abspath(__file__))
+    vertex_key_path = filepath + "/vertex_key.json"
+
+    # Read the existing content of the file or create an empty dictionary
+    try:
+        with open(vertex_key_path, "r") as file:
+            # Read the file content
+            print("Read vertexai file path")
+            content = file.read()
+
+            # If the file is empty or not valid JSON, create an empty dictionary
+            if not content or not content.strip():
+                service_account_key_data = {}
+            else:
+                # Attempt to load the existing JSON content
+                file.seek(0)
+                service_account_key_data = json.load(file)
+    except FileNotFoundError:
+        # If the file doesn't exist, create an empty dictionary
+        service_account_key_data = {}
+
+    # Update the service_account_key_data with environment variables
+    private_key_id = os.environ.get("VERTEX_AI_PRIVATE_KEY_ID", "")
+    private_key = os.environ.get("VERTEX_AI_PRIVATE_KEY", "")
+    private_key = private_key.replace("\\n", "\n")
+    service_account_key_data["private_key_id"] = private_key_id
+    service_account_key_data["private_key"] = private_key
+
+    # Create a temporary file
+    with tempfile.NamedTemporaryFile(mode="w+", delete=False) as temp_file:
+        # Write the updated content to the temporary files
+        json.dump(service_account_key_data, temp_file, indent=2)
+
+    # Export the temporary file as GOOGLE_APPLICATION_CREDENTIALS
+    os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = os.path.abspath(temp_file.name)
+
+
+async def call_spend_logs_endpoint():
+    """
+    Call this
+    curl -X GET "http://0.0.0.0:4000/spend/logs" -H "Authorization: Bearer sk-1234"
+    """
+    import datetime
+    import requests
+
+    todays_date = datetime.datetime.now().strftime("%Y-%m-%d")
+    url = f"http://0.0.0.0:4000/global/spend/logs?api_key=best-api-key-ever"
+    headers = {"Authorization": f"Bearer sk-1234"}
+    response = requests.get(url, headers=headers)
+    print("response from call_spend_logs_endpoint", response)
+
+    json_response = response.json()
+
+    # get spend for today
+    """
+    json response looks like this
+
+    [{'date': '2024-08-30', 'spend': 0.00016600000000000002, 'api_key': 'best-api-key-ever'}]
+    """
+
+    todays_date = datetime.datetime.now().strftime("%Y-%m-%d")
+    for spend_log in json_response:
+        if spend_log["date"] == todays_date:
+            return spend_log["spend"]
+
+
+LITE_LLM_ENDPOINT = "http://localhost:4000"
+
+
+@pytest.mark.asyncio()
+async def test_basic_vertex_ai_pass_through_with_spendlog():
+
+    spend_before = await call_spend_logs_endpoint() or 0.0
+    load_vertex_ai_credentials()
+
+    vertexai.init(
+        project="adroit-crow-413218",
+        location="us-central1",
+        api_endpoint=f"{LITE_LLM_ENDPOINT}/vertex-ai",
+        api_transport="rest",
+    )
+
+    model = GenerativeModel(model_name="gemini-1.0-pro")
+    response = model.generate_content("hi")
+
+    print("response", response)
+
+    await asyncio.sleep(20)
+    spend_after = await call_spend_logs_endpoint()
+    print("spend_after", spend_after)
+    assert (
+        spend_after > spend_before
+    ), "Spend should be greater than before. spend_before: {}, spend_after: {}".format(
+        spend_before, spend_after
+    )
+
+    pass

tests/pass_through_tests/vertex_key.json

@@ -0,0 +1,13 @@
+{
+  "type": "service_account",
+  "project_id": "adroit-crow-413218",
+  "private_key_id": "",
+  "private_key": "",
+  "client_email": "test-adroit-crow@adroit-crow-413218.iam.gserviceaccount.com",
+  "client_id": "104886546564708740969",
+  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+  "token_uri": "https://oauth2.googleapis.com/token",
+  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/test-adroit-crow%40adroit-crow-413218.iam.gserviceaccount.com",
+  "universe_domain": "googleapis.com"
+}