Files
Homelab/Development/litellm/README.md

449 lines
37 KiB
Markdown
Raw Blame History

This file contains invisible Unicode characters

This file contains invisible Unicode characters that are indistinguishable to humans but may be processed differently by a computer. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

<h1 align="center">
🚅 LiteLLM
</h1>
<p align="center">
<p align="center">
<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>
<a href="https://railway.app/template/HLP0Ub?referralCode=jch2ME">
<img src="https://railway.app/button.svg" alt="Deploy on Railway">
</a>
</p>
<p align="center">Call all LLM APIs using the OpenAI format [Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, Groq etc.]
<br>
</p>
<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>
<h4 align="center">
<a href="https://pypi.org/project/litellm/" target="_blank">
<img src="https://img.shields.io/pypi/v/litellm.svg" alt="PyPI Version">
</a>
<a href="https://www.ycombinator.com/companies/berriai">
<img src="https://img.shields.io/badge/Y%20Combinator-W23-orange?style=flat-square" alt="Y Combinator W23">
</a>
<a href="https://wa.link/huol9n">
<img src="https://img.shields.io/static/v1?label=Chat%20on&message=WhatsApp&color=success&logo=WhatsApp&style=flat-square" alt="Whatsapp">
</a>
<a href="https://discord.gg/wuPM9dRgDw">
<img src="https://img.shields.io/static/v1?label=Chat%20on&message=Discord&color=blue&logo=Discord&style=flat-square" alt="Discord">
</a>
<a href="https://join.slack.com/share/enQtOTE0ODczMzk2Nzk4NC01YjUxNjY2YjBlYTFmNDRiZTM3NDFiYTM3MzVkODFiMDVjOGRjMmNmZTZkZTMzOWQzZGQyZWIwYjQ0MWExYmE3">
<img src="https://img.shields.io/static/v1?label=Chat%20on&message=Slack&color=black&logo=Slack&style=flat-square" alt="Slack">
</a>
</h4>
LiteLLM manages:
- Translate inputs to provider's `completion`, `embedding`, and `image_generation` endpoints
- [Consistent output](https://docs.litellm.ai/docs/completion/output), text responses will always be available at `['choices'][0]['message']['content']`
- Retry/fallback logic across multiple deployments (e.g. Azure/OpenAI) - [Router](https://docs.litellm.ai/docs/routing)
- Set Budgets & Rate limits per project, api key, model [LiteLLM Proxy Server (LLM Gateway)](https://docs.litellm.ai/docs/simple_proxy)
[**Jump to LiteLLM Proxy (LLM Gateway) Docs**](https://github.com/BerriAI/litellm?tab=readme-ov-file#openai-proxy---docs) <br>
[**Jump to Supported LLM Providers**](https://github.com/BerriAI/litellm?tab=readme-ov-file#supported-providers-docs)
🚨 **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)
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+).
# Usage ([**Docs**](https://docs.litellm.ai/docs/))
> [!IMPORTANT]
> LiteLLM v1.0.0 now requires `openai>=1.0.0`. Migration guide [here](https://docs.litellm.ai/docs/migration)
> LiteLLM v1.40.14+ now requires `pydantic>=2.0.0`. No changes required.
<a target="_blank" href="https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/liteLLM_Getting_Started.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
```shell
pip install litellm
```
```python
from litellm import completion
import os
## set ENV variables
os.environ["OPENAI_API_KEY"] = "your-openai-key"
os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-key"
messages = [{ "content": "Hello, how are you?","role": "user"}]
# openai call
response = completion(model="openai/gpt-4o", messages=messages)
# anthropic call
response = completion(model="anthropic/claude-sonnet-4-20250514", messages=messages)
print(response)
```
### Response (OpenAI Format)
```json
{
"id": "chatcmpl-1214900a-6cdd-4148-b663-b5e2f642b4de",
"created": 1751494488,
"model": "claude-sonnet-4-20250514",
"object": "chat.completion",
"system_fingerprint": null,
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": "Hello! I'm doing well, thank you for asking. I'm here and ready to help with whatever you'd like to discuss or work on. How are you doing today?",
"role": "assistant",
"tool_calls": null,
"function_call": null
}
}
],
"usage": {
"completion_tokens": 39,
"prompt_tokens": 13,
"total_tokens": 52,
"completion_tokens_details": null,
"prompt_tokens_details": {
"audio_tokens": null,
"cached_tokens": 0
},
"cache_creation_input_tokens": 0,
"cache_read_input_tokens": 0
}
}
```
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)
## Async ([Docs](https://docs.litellm.ai/docs/completion/stream#async-completion))
```python
from litellm import acompletion
import asyncio
async def test_get_response():
user_message = "Hello, how are you?"
messages = [{"content": user_message, "role": "user"}]
response = await acompletion(model="openai/gpt-4o", messages=messages)
return response
response = asyncio.run(test_get_response())
print(response)
```
## Streaming ([Docs](https://docs.litellm.ai/docs/completion/stream))
liteLLM supports streaming the model response back, pass `stream=True` to get a streaming iterator in response.
Streaming is supported for all models (Bedrock, Huggingface, TogetherAI, Azure, OpenAI, etc.)
```python
from litellm import completion
response = completion(model="openai/gpt-4o", messages=messages, stream=True)
for part in response:
print(part.choices[0].delta.content or "")
# claude sonnet 4
response = completion('anthropic/claude-sonnet-4-20250514', messages, stream=True)
for part in response:
print(part)
```
### Response chunk (OpenAI Format)
```json
{
"id": "chatcmpl-fe575c37-5004-4926-ae5e-bfbc31f356ca",
"created": 1751494808,
"model": "claude-sonnet-4-20250514",
"object": "chat.completion.chunk",
"system_fingerprint": null,
"choices": [
{
"finish_reason": null,
"index": 0,
"delta": {
"provider_specific_fields": null,
"content": "Hello",
"role": "assistant",
"function_call": null,
"tool_calls": null,
"audio": null
},
"logprobs": null
}
],
"provider_specific_fields": null,
"stream_options": null,
"citations": null
}
```
## Logging Observability ([Docs](https://docs.litellm.ai/docs/observability/callbacks))
LiteLLM exposes pre defined callbacks to send data to Lunary, MLflow, Langfuse, DynamoDB, s3 Buckets, Helicone, Promptlayer, Traceloop, Athina, Slack
```python
from litellm import completion
## set env variables for logging tools (when using MLflow, no API key set up is required)
os.environ["LUNARY_PUBLIC_KEY"] = "your-lunary-public-key"
os.environ["HELICONE_API_KEY"] = "your-helicone-auth-key"
os.environ["LANGFUSE_PUBLIC_KEY"] = ""
os.environ["LANGFUSE_SECRET_KEY"] = ""
os.environ["ATHINA_API_KEY"] = "your-athina-api-key"
os.environ["OPENAI_API_KEY"] = "your-openai-key"
# set callbacks
litellm.success_callback = ["lunary", "mlflow", "langfuse", "athina", "helicone"] # log input/output to lunary, langfuse, supabase, athina, helicone etc
#openai call
response = completion(model="openai/gpt-4o", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
```
# LiteLLM Proxy Server (LLM Gateway) - ([Docs](https://docs.litellm.ai/docs/simple_proxy))
Track spend + Load Balance across multiple projects
[Hosted Proxy (Preview)](https://docs.litellm.ai/docs/hosted)
The proxy provides:
1. [Hooks for auth](https://docs.litellm.ai/docs/proxy/virtual_keys#custom-auth)
2. [Hooks for logging](https://docs.litellm.ai/docs/proxy/logging#step-1---create-your-custom-litellm-callback-class)
3. [Cost tracking](https://docs.litellm.ai/docs/proxy/virtual_keys#tracking-spend)
4. [Rate Limiting](https://docs.litellm.ai/docs/proxy/users#set-rate-limits)
## 📖 Proxy Endpoints - [Swagger Docs](https://litellm-api.up.railway.app/)
## Quick Start Proxy - CLI
```shell
pip install 'litellm[proxy]'
```
### Step 1: Start litellm proxy
```shell
$ litellm --model huggingface/bigcode/starcoder
#INFO: Proxy running on http://0.0.0.0:4000
```
### Step 2: Make ChatCompletions Request to Proxy
> [!IMPORTANT]
> 💡 [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)
```python
import openai # openai v1.0.0+
client = openai.OpenAI(api_key="anything",base_url="http://0.0.0.0:4000") # set proxy to base_url
# request sent to model set on litellm proxy, `litellm --model`
response = client.chat.completions.create(model="gpt-3.5-turbo", messages = [
{
"role": "user",
"content": "this is a test request, write a short poem"
}
])
print(response)
```
## Proxy Key Management ([Docs](https://docs.litellm.ai/docs/proxy/virtual_keys))
Connect the proxy with a Postgres DB to create proxy keys
```bash
# Get the code
git clone https://github.com/BerriAI/litellm
# Go to folder
cd litellm
# Add the master key - you can change this after setup
echo 'LITELLM_MASTER_KEY="sk-1234"' > .env
# Add the litellm salt key - you cannot change this after adding a model
# It is used to encrypt / decrypt your LLM API Key credentials
# We recommend - https://1password.com/password-generator/
# password generator to get a random hash for litellm salt key
echo 'LITELLM_SALT_KEY="sk-1234"' >> .env
source .env
# Start
docker-compose up
```
UI on `/ui` on your proxy server
![ui_3](https://github.com/BerriAI/litellm/assets/29436595/47c97d5e-b9be-4839-b28c-43d7f4f10033)
Set budgets and rate limits across multiple projects
`POST /key/generate`
### Request
```shell
curl 'http://0.0.0.0:4000/key/generate' \
--header 'Authorization: Bearer sk-1234' \
--header 'Content-Type: application/json' \
--data-raw '{"models": ["gpt-3.5-turbo", "gpt-4", "claude-2"], "duration": "20m","metadata": {"user": "ishaan@berri.ai", "team": "core-infra"}}'
```
### Expected Response
```shell
{
"key": "sk-kdEXbIqZRwEeEiHwdg7sFA", # Bearer token
"expires": "2023-11-19T01:38:25.838000+00:00" # datetime object
}
```
## Supported Providers ([Docs](https://docs.litellm.ai/docs/providers))
| 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) |
|-------------------------------------------------------------------------------------|---------------------------------------------------------|---------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------|-------------------------------------------------------------------------------|-------------------------------------------------------------------------|
| [openai](https://docs.litellm.ai/docs/providers/openai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| [Meta - Llama API](https://docs.litellm.ai/docs/providers/meta_llama) | ✅ | ✅ | ✅ | ✅ | | |
| [azure](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| [AI/ML API](https://docs.litellm.ai/docs/providers/aiml) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| [aws - sagemaker](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ | ✅ | ✅ | |
| [aws - bedrock](https://docs.litellm.ai/docs/providers/bedrock) | ✅ | ✅ | ✅ | ✅ | ✅ | |
| [google - vertex_ai](https://docs.litellm.ai/docs/providers/vertex) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| [google - palm](https://docs.litellm.ai/docs/providers/palm) | ✅ | ✅ | ✅ | ✅ | | |
| [google AI Studio - gemini](https://docs.litellm.ai/docs/providers/gemini) | ✅ | ✅ | ✅ | ✅ | | |
| [mistral ai api](https://docs.litellm.ai/docs/providers/mistral) | ✅ | ✅ | ✅ | ✅ | ✅ | |
| [cloudflare AI Workers](https://docs.litellm.ai/docs/providers/cloudflare_workers) | ✅ | ✅ | ✅ | ✅ | | |
| [cohere](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ | ✅ | ✅ | |
| [anthropic](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ | ✅ | | |
| [empower](https://docs.litellm.ai/docs/providers/empower) | ✅ | ✅ | ✅ | ✅ |
| [huggingface](https://docs.litellm.ai/docs/providers/huggingface) | ✅ | ✅ | ✅ | ✅ | ✅ | |
| [replicate](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ | ✅ | | |
| [together_ai](https://docs.litellm.ai/docs/providers/togetherai) | ✅ | ✅ | ✅ | ✅ | | |
| [openrouter](https://docs.litellm.ai/docs/providers/openrouter) | ✅ | ✅ | ✅ | ✅ | | |
| [ai21](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ | ✅ | | |
| [baseten](https://docs.litellm.ai/docs/providers/baseten) | ✅ | ✅ | ✅ | ✅ | | |
| [vllm](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ | ✅ | | |
| [nlp_cloud](https://docs.litellm.ai/docs/providers/nlp_cloud) | ✅ | ✅ | ✅ | ✅ | | |
| [aleph alpha](https://docs.litellm.ai/docs/providers/aleph_alpha) | ✅ | ✅ | ✅ | ✅ | | |
| [petals](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ | ✅ | | |
| [ollama](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ | ✅ | ✅ | |
| [deepinfra](https://docs.litellm.ai/docs/providers/deepinfra) | ✅ | ✅ | ✅ | ✅ | | |
| [perplexity-ai](https://docs.litellm.ai/docs/providers/perplexity) | ✅ | ✅ | ✅ | ✅ | | |
| [Groq AI](https://docs.litellm.ai/docs/providers/groq) | ✅ | ✅ | ✅ | ✅ | | |
| [Deepseek](https://docs.litellm.ai/docs/providers/deepseek) | ✅ | ✅ | ✅ | ✅ | | |
| [anyscale](https://docs.litellm.ai/docs/providers/anyscale) | ✅ | ✅ | ✅ | ✅ | | |
| [IBM - watsonx.ai](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ | ✅ | ✅ | |
| [voyage ai](https://docs.litellm.ai/docs/providers/voyage) | | | | | ✅ | |
| [xinference [Xorbits Inference]](https://docs.litellm.ai/docs/providers/xinference) | | | | | ✅ | |
| [FriendliAI](https://docs.litellm.ai/docs/providers/friendliai) | ✅ | ✅ | ✅ | ✅ | | |
| [Galadriel](https://docs.litellm.ai/docs/providers/galadriel) | ✅ | ✅ | ✅ | ✅ | | |
| [GradientAI](https://docs.litellm.ai/docs/providers/gradient_ai) | ✅ | ✅ | | | | |
| [Novita AI](https://novita.ai/models/llm?utm_source=github_litellm&utm_medium=github_readme&utm_campaign=github_link) | ✅ | ✅ | ✅ | ✅ | | |
| [Featherless AI](https://docs.litellm.ai/docs/providers/featherless_ai) | ✅ | ✅ | ✅ | ✅ | | |
| [Nebius AI Studio](https://docs.litellm.ai/docs/providers/nebius) | ✅ | ✅ | ✅ | ✅ | ✅ | |
[**Read the Docs**](https://docs.litellm.ai/docs/)
## Contributing
Interested in contributing? Contributions to LiteLLM Python SDK, Proxy Server, and LLM integrations are both accepted and highly encouraged!
**Quick start:** `git clone``make install-dev``make format``make lint``make test-unit`
See our comprehensive [Contributing Guide (CONTRIBUTING.md)](CONTRIBUTING.md) for detailed instructions.
# Enterprise
For companies that need better security, user management and professional support
[Talk to founders](https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat)
This covers:
-**Features under the [LiteLLM Commercial License](https://docs.litellm.ai/docs/proxy/enterprise):**
-**Feature Prioritization**
-**Custom Integrations**
-**Professional Support - Dedicated discord + slack**
-**Custom SLAs**
-**Secure access with Single Sign-On**
# Contributing
We welcome contributions to LiteLLM! Whether you're fixing bugs, adding features, or improving documentation, we appreciate your help.
## Quick Start for Contributors
This requires poetry to be installed.
```bash
git clone https://github.com/BerriAI/litellm.git
cd litellm
make install-dev # Install development dependencies
make format # Format your code
make lint # Run all linting checks
make test-unit # Run unit tests
make format-check # Check formatting only
```
For detailed contributing guidelines, see [CONTRIBUTING.md](CONTRIBUTING.md).
## Code Quality / Linting
LiteLLM follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html).
Our automated checks include:
- **Black** for code formatting
- **Ruff** for linting and code quality
- **MyPy** for type checking
- **Circular import detection**
- **Import safety checks**
All these checks must pass before your PR can be merged.
# 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)
- [Community Slack 💭](https://join.slack.com/share/enQtOTE0ODczMzk2Nzk4NC01YjUxNjY2YjBlYTFmNDRiZTM3NDFiYTM3MzVkODFiMDVjOGRjMmNmZTZkZTMzOWQzZGQyZWIwYjQ0MWExYmE3)
- 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 `python3 /path/to/litellm/proxy_cli.py`
### Frontend
1. Navigate to `ui/litellm-dashboard`
2. Install dependencies `npm install`
3. Run `npm run dev` to start the dashboard