mirror of
https://github.com/BerriAI/litellm.git
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410 lines
33 KiB
Markdown
410 lines
33 KiB
Markdown
<h1 align="center">
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🚅 LiteLLM
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</h1>
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<p align="center">
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<p align="center">
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<a href="https://render.com/deploy?repo=https://github.com/BerriAI/litellm" target="_blank" rel="nofollow"><img src="https://render.com/images/deploy-to-render-button.svg" alt="Deploy to Render"></a>
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<a href="https://railway.app/template/HLP0Ub?referralCode=jch2ME">
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<img src="https://railway.app/button.svg" alt="Deploy on Railway">
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</a>
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</p>
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<p align="center">Call all LLM APIs using the OpenAI format [Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, Groq etc.]
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<br>
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</p>
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<h4 align="center"><a href="https://docs.litellm.ai/docs/simple_proxy" target="_blank">LiteLLM Proxy Server (LLM Gateway)</a> | <a href="https://docs.litellm.ai/docs/hosted" target="_blank"> Hosted Proxy (Preview)</a> | <a href="https://docs.litellm.ai/docs/enterprise"target="_blank">Enterprise Tier</a></h4>
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<h4 align="center">
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<a href="https://pypi.org/project/litellm/" target="_blank">
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<img src="https://img.shields.io/pypi/v/litellm.svg" alt="PyPI Version">
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</a>
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<a href="https://www.ycombinator.com/companies/berriai">
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<img src="https://img.shields.io/badge/Y%20Combinator-W23-orange?style=flat-square" alt="Y Combinator W23">
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</a>
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<a href="https://wa.link/huol9n">
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<img src="https://img.shields.io/static/v1?label=Chat%20on&message=WhatsApp&color=success&logo=WhatsApp&style=flat-square" alt="Whatsapp">
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</a>
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<a href="https://discord.gg/wuPM9dRgDw">
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<img src="https://img.shields.io/static/v1?label=Chat%20on&message=Discord&color=blue&logo=Discord&style=flat-square" alt="Discord">
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</a>
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</h4>
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LiteLLM manages:
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- Translate inputs to provider's `completion`, `embedding`, and `image_generation` endpoints
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- [Consistent output](https://docs.litellm.ai/docs/completion/output), text responses will always be available at `['choices'][0]['message']['content']`
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- Retry/fallback logic across multiple deployments (e.g. Azure/OpenAI) - [Router](https://docs.litellm.ai/docs/routing)
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- Set Budgets & Rate limits per project, api key, model [LiteLLM Proxy Server (LLM Gateway)](https://docs.litellm.ai/docs/simple_proxy)
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[**Jump to LiteLLM Proxy (LLM Gateway) Docs**](https://github.com/BerriAI/litellm?tab=readme-ov-file#openai-proxy---docs) <br>
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[**Jump to Supported LLM Providers**](https://github.com/BerriAI/litellm?tab=readme-ov-file#supported-providers-docs)
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🚨 **Stable Release:** Use docker images with the `-stable` tag. These have undergone 12 hour load tests, before being published. [More information about the release cycle here](https://docs.litellm.ai/docs/proxy/release_cycle)
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Support for more providers. Missing a provider or LLM Platform, raise a [feature request](https://github.com/BerriAI/litellm/issues/new?assignees=&labels=enhancement&projects=&template=feature_request.yml&title=%5BFeature%5D%3A+).
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# Usage ([**Docs**](https://docs.litellm.ai/docs/))
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> [!IMPORTANT]
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> LiteLLM v1.0.0 now requires `openai>=1.0.0`. Migration guide [here](https://docs.litellm.ai/docs/migration)
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> LiteLLM v1.40.14+ now requires `pydantic>=2.0.0`. No changes required.
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<a target="_blank" href="https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/liteLLM_Getting_Started.ipynb">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
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</a>
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```shell
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pip install litellm
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```
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```python
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from litellm import completion
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import os
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## set ENV variables
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os.environ["OPENAI_API_KEY"] = "your-openai-key"
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os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-key"
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messages = [{ "content": "Hello, how are you?","role": "user"}]
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# openai call
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response = completion(model="openai/gpt-4o", messages=messages)
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# anthropic call
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response = completion(model="anthropic/claude-3-sonnet-20240229", messages=messages)
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print(response)
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```
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### Response (OpenAI Format)
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```json
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{
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"id": "chatcmpl-565d891b-a42e-4c39-8d14-82a1f5208885",
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"created": 1734366691,
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"model": "claude-3-sonnet-20240229",
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"object": "chat.completion",
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"system_fingerprint": null,
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"choices": [
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{
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"finish_reason": "stop",
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"index": 0,
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"message": {
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"content": "Hello! As an AI language model, I don't have feelings, but I'm operating properly and ready to assist you with any questions or tasks you may have. How can I help you today?",
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"role": "assistant",
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"tool_calls": null,
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"function_call": null
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}
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}
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],
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"usage": {
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"completion_tokens": 43,
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"prompt_tokens": 13,
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"total_tokens": 56,
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"completion_tokens_details": null,
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"prompt_tokens_details": {
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"audio_tokens": null,
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"cached_tokens": 0
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},
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"cache_creation_input_tokens": 0,
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"cache_read_input_tokens": 0
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}
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}
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```
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Call any model supported by a provider, with `model=<provider_name>/<model_name>`. There might be provider-specific details here, so refer to [provider docs for more information](https://docs.litellm.ai/docs/providers)
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## Async ([Docs](https://docs.litellm.ai/docs/completion/stream#async-completion))
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```python
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from litellm import acompletion
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import asyncio
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async def test_get_response():
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user_message = "Hello, how are you?"
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messages = [{"content": user_message, "role": "user"}]
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response = await acompletion(model="openai/gpt-4o", messages=messages)
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return response
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response = asyncio.run(test_get_response())
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print(response)
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```
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## Streaming ([Docs](https://docs.litellm.ai/docs/completion/stream))
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liteLLM supports streaming the model response back, pass `stream=True` to get a streaming iterator in response.
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Streaming is supported for all models (Bedrock, Huggingface, TogetherAI, Azure, OpenAI, etc.)
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```python
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from litellm import completion
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response = completion(model="openai/gpt-4o", messages=messages, stream=True)
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for part in response:
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print(part.choices[0].delta.content or "")
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# claude 2
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response = completion('anthropic/claude-3-sonnet-20240229', messages, stream=True)
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for part in response:
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print(part)
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```
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### Response chunk (OpenAI Format)
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```json
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{
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"id": "chatcmpl-2be06597-eb60-4c70-9ec5-8cd2ab1b4697",
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"created": 1734366925,
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"model": "claude-3-sonnet-20240229",
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"object": "chat.completion.chunk",
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"system_fingerprint": null,
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"choices": [
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{
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"finish_reason": null,
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"index": 0,
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"delta": {
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"content": "Hello",
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"role": "assistant",
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"function_call": null,
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"tool_calls": null,
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"audio": null
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},
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"logprobs": null
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}
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]
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}
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```
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## Logging Observability ([Docs](https://docs.litellm.ai/docs/observability/callbacks))
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LiteLLM exposes pre defined callbacks to send data to Lunary, MLflow, Langfuse, DynamoDB, s3 Buckets, Helicone, Promptlayer, Traceloop, Athina, Slack
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```python
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from litellm import completion
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## set env variables for logging tools (when using MLflow, no API key set up is required)
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os.environ["LUNARY_PUBLIC_KEY"] = "your-lunary-public-key"
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os.environ["HELICONE_API_KEY"] = "your-helicone-auth-key"
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os.environ["LANGFUSE_PUBLIC_KEY"] = ""
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os.environ["LANGFUSE_SECRET_KEY"] = ""
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os.environ["ATHINA_API_KEY"] = "your-athina-api-key"
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os.environ["OPENAI_API_KEY"] = "your-openai-key"
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# set callbacks
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litellm.success_callback = ["lunary", "mlflow", "langfuse", "athina", "helicone"] # log input/output to lunary, langfuse, supabase, athina, helicone etc
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#openai call
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response = completion(model="openai/gpt-4o", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
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```
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# LiteLLM Proxy Server (LLM Gateway) - ([Docs](https://docs.litellm.ai/docs/simple_proxy))
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Track spend + Load Balance across multiple projects
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[Hosted Proxy (Preview)](https://docs.litellm.ai/docs/hosted)
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The proxy provides:
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1. [Hooks for auth](https://docs.litellm.ai/docs/proxy/virtual_keys#custom-auth)
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2. [Hooks for logging](https://docs.litellm.ai/docs/proxy/logging#step-1---create-your-custom-litellm-callback-class)
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3. [Cost tracking](https://docs.litellm.ai/docs/proxy/virtual_keys#tracking-spend)
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4. [Rate Limiting](https://docs.litellm.ai/docs/proxy/users#set-rate-limits)
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## 📖 Proxy Endpoints - [Swagger Docs](https://litellm-api.up.railway.app/)
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## Quick Start Proxy - CLI
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```shell
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pip install 'litellm[proxy]'
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```
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### Step 1: Start litellm proxy
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```shell
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$ litellm --model huggingface/bigcode/starcoder
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#INFO: Proxy running on http://0.0.0.0:4000
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```
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### Step 2: Make ChatCompletions Request to Proxy
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> [!IMPORTANT]
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> 💡 [Use LiteLLM Proxy with Langchain (Python, JS), OpenAI SDK (Python, JS) Anthropic SDK, Mistral SDK, LlamaIndex, Instructor, Curl](https://docs.litellm.ai/docs/proxy/user_keys)
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```python
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import openai # openai v1.0.0+
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client = openai.OpenAI(api_key="anything",base_url="http://0.0.0.0:4000") # set proxy to base_url
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# request sent to model set on litellm proxy, `litellm --model`
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response = client.chat.completions.create(model="gpt-3.5-turbo", messages = [
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{
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"role": "user",
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"content": "this is a test request, write a short poem"
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}
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])
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print(response)
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```
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## Proxy Key Management ([Docs](https://docs.litellm.ai/docs/proxy/virtual_keys))
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Connect the proxy with a Postgres DB to create proxy keys
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```bash
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# Get the code
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git clone https://github.com/BerriAI/litellm
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# Go to folder
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cd litellm
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# Add the master key - you can change this after setup
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echo 'LITELLM_MASTER_KEY="sk-1234"' > .env
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# Add the litellm salt key - you cannot change this after adding a model
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# It is used to encrypt / decrypt your LLM API Key credentials
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# We recommend - https://1password.com/password-generator/
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# password generator to get a random hash for litellm salt key
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echo 'LITELLM_SALT_KEY="sk-1234"' > .env
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source .env
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# Start
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docker-compose up
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```
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UI on `/ui` on your proxy server
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Set budgets and rate limits across multiple projects
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`POST /key/generate`
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### Request
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```shell
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curl 'http://0.0.0.0:4000/key/generate' \
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--header 'Authorization: Bearer sk-1234' \
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--header 'Content-Type: application/json' \
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--data-raw '{"models": ["gpt-3.5-turbo", "gpt-4", "claude-2"], "duration": "20m","metadata": {"user": "ishaan@berri.ai", "team": "core-infra"}}'
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```
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### Expected Response
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```shell
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{
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"key": "sk-kdEXbIqZRwEeEiHwdg7sFA", # Bearer token
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"expires": "2023-11-19T01:38:25.838000+00:00" # datetime object
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}
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```
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## Supported Providers ([Docs](https://docs.litellm.ai/docs/providers))
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| Provider | [Completion](https://docs.litellm.ai/docs/#basic-usage) | [Streaming](https://docs.litellm.ai/docs/completion/stream#streaming-responses) | [Async Completion](https://docs.litellm.ai/docs/completion/stream#async-completion) | [Async Streaming](https://docs.litellm.ai/docs/completion/stream#async-streaming) | [Async Embedding](https://docs.litellm.ai/docs/embedding/supported_embedding) | [Async Image Generation](https://docs.litellm.ai/docs/image_generation) |
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|-------------------------------------------------------------------------------------|---------------------------------------------------------|---------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------|-------------------------------------------------------------------------------|-------------------------------------------------------------------------|
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| [openai](https://docs.litellm.ai/docs/providers/openai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| [azure](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| [AI/ML API](https://docs.litellm.ai/docs/providers/aiml) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| [aws - sagemaker](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| [aws - bedrock](https://docs.litellm.ai/docs/providers/bedrock) | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| [google - vertex_ai](https://docs.litellm.ai/docs/providers/vertex) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| [google - palm](https://docs.litellm.ai/docs/providers/palm) | ✅ | ✅ | ✅ | ✅ | | |
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| [google AI Studio - gemini](https://docs.litellm.ai/docs/providers/gemini) | ✅ | ✅ | ✅ | ✅ | | |
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| [mistral ai api](https://docs.litellm.ai/docs/providers/mistral) | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| [cloudflare AI Workers](https://docs.litellm.ai/docs/providers/cloudflare_workers) | ✅ | ✅ | ✅ | ✅ | | |
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| [cohere](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| [anthropic](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ | ✅ | | |
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| [empower](https://docs.litellm.ai/docs/providers/empower) | ✅ | ✅ | ✅ | ✅ |
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| [huggingface](https://docs.litellm.ai/docs/providers/huggingface) | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| [replicate](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ | ✅ | | |
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| [together_ai](https://docs.litellm.ai/docs/providers/togetherai) | ✅ | ✅ | ✅ | ✅ | | |
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| [openrouter](https://docs.litellm.ai/docs/providers/openrouter) | ✅ | ✅ | ✅ | ✅ | | |
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| [ai21](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ | ✅ | | |
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| [baseten](https://docs.litellm.ai/docs/providers/baseten) | ✅ | ✅ | ✅ | ✅ | | |
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| [vllm](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ | ✅ | | |
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| [nlp_cloud](https://docs.litellm.ai/docs/providers/nlp_cloud) | ✅ | ✅ | ✅ | ✅ | | |
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| [aleph alpha](https://docs.litellm.ai/docs/providers/aleph_alpha) | ✅ | ✅ | ✅ | ✅ | | |
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| [petals](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ | ✅ | | |
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| [ollama](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| [deepinfra](https://docs.litellm.ai/docs/providers/deepinfra) | ✅ | ✅ | ✅ | ✅ | | |
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| [perplexity-ai](https://docs.litellm.ai/docs/providers/perplexity) | ✅ | ✅ | ✅ | ✅ | | |
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| [Groq AI](https://docs.litellm.ai/docs/providers/groq) | ✅ | ✅ | ✅ | ✅ | | |
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| [Deepseek](https://docs.litellm.ai/docs/providers/deepseek) | ✅ | ✅ | ✅ | ✅ | | |
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| [anyscale](https://docs.litellm.ai/docs/providers/anyscale) | ✅ | ✅ | ✅ | ✅ | | |
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| [IBM - watsonx.ai](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| [voyage ai](https://docs.litellm.ai/docs/providers/voyage) | | | | | ✅ | |
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| [xinference [Xorbits Inference]](https://docs.litellm.ai/docs/providers/xinference) | | | | | ✅ | |
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| [FriendliAI](https://docs.litellm.ai/docs/providers/friendliai) | ✅ | ✅ | ✅ | ✅ | | |
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| [Galadriel](https://docs.litellm.ai/docs/providers/galadriel) | ✅ | ✅ | ✅ | ✅ | | |
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[**Read the Docs**](https://docs.litellm.ai/docs/)
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## Contributing
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Interested in contributing? Contributions to LiteLLM Python SDK, Proxy Server, and contributing LLM integrations are both accepted and highly encouraged! [See our Contribution Guide for more details](https://docs.litellm.ai/docs/extras/contributing_code)
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# Enterprise
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For companies that need better security, user management and professional support
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[Talk to founders](https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat)
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This covers:
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- ✅ **Features under the [LiteLLM Commercial License](https://docs.litellm.ai/docs/proxy/enterprise):**
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- ✅ **Feature Prioritization**
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- ✅ **Custom Integrations**
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- ✅ **Professional Support - Dedicated discord + slack**
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- ✅ **Custom SLAs**
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- ✅ **Secure access with Single Sign-On**
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# Code Quality / Linting
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LiteLLM follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html).
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We run:
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- Ruff for [formatting and linting checks](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.circleci/config.yml#L320)
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- Mypy + Pyright for typing [1](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.circleci/config.yml#L90), [2](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.pre-commit-config.yaml#L4)
|
||
- Black for [formatting](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.circleci/config.yml#L79)
|
||
- isort for [import sorting](https://github.com/BerriAI/litellm/blob/e19bb55e3b4c6a858b6e364302ebbf6633a51de5/.pre-commit-config.yaml#L10)
|
||
|
||
|
||
If you have suggestions on how to improve the code quality feel free to open an issue or a PR.
|
||
|
||
|
||
# Support / talk with founders
|
||
|
||
- [Schedule Demo 👋](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version)
|
||
- [Community Discord 💭](https://discord.gg/wuPM9dRgDw)
|
||
- Our numbers 📞 +1 (770) 8783-106 / +1 (412) 618-6238
|
||
- Our emails ✉️ ishaan@berri.ai / krrish@berri.ai
|
||
|
||
# Why did we build this
|
||
|
||
- **Need for simplicity**: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI and Cohere.
|
||
|
||
# Contributors
|
||
|
||
<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
|
||
<!-- prettier-ignore-start -->
|
||
<!-- markdownlint-disable -->
|
||
|
||
<!-- markdownlint-restore -->
|
||
<!-- prettier-ignore-end -->
|
||
|
||
<!-- ALL-CONTRIBUTORS-LIST:END -->
|
||
|
||
<a href="https://github.com/BerriAI/litellm/graphs/contributors">
|
||
<img src="https://contrib.rocks/image?repo=BerriAI/litellm" />
|
||
</a>
|
||
|
||
|
||
## Run in Developer mode
|
||
### Services
|
||
1. Setup .env file in root
|
||
2. Run dependant services `docker-compose up db prometheus`
|
||
|
||
### Backend
|
||
1. (In root) create virtual environment `python -m venv .venv`
|
||
2. Activate virtual environment `source .venv/bin/activate`
|
||
3. Install dependencies `pip install -e ".[all]"`
|
||
4. Start proxy backend `uvicorn litellm.proxy.proxy_server:app --host localhost --port 4000 --reload`
|
||
|
||
### Frontend
|
||
1. Navigate to `ui/litellm-dashboard`
|
||
2. Install dependencies `npm install`
|
||
3. Run `npm run dev` to start the dashboard
|