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LiteLLM как единый шлюз для LLM и MCP

OpenAI

LiteLLM — open-source шлюз, унифицирующий вызовы 100+ LLM через OpenAI-совместимый API, с виртуальными ключами, трекингом расходов и поддержкой MCP.

LiteLLM — open-source шлюз, унифицирующий вызовы 100+ LLM через OpenAI-совместимый API, с виртуальными ключами, трекингом расходов и поддержкой MCP.

что из этого моё

Можно внедрить LiteLLM как ядро оркестрации: единый API для всех моделей, виртуальные ключи для клиентов, трекинг расходов и балансировка нагрузки. Это упростит интеграцию с buyanov.io и позволит предлагать клиентам гибкий выбор моделей без переписывания кода.

Что забрать
отметь, что берёшь в работу → или отбрось как не своёмоё →
поднять LiteLLM Proxy Server локально через docker compose и проверить вызов своей модели через OpenAI-совместимый API
настроить виртуальные ключи в LiteLLM для разграничения доступа клиентов к моделям
подключить MCP-сервер через LiteLLM Gateway и проверить вызов внешнего инструмента в своей модели
расшифровка ролика ↓

<h1 align="center"> 🚅 LiteLLM </h1> <p align="center"> <p align="center">LiteLLM AI Gateway </p> <p align="center">Open Source AI Gateway for 100+ LLMs. Self-hosted. Enterprise-ready. Call any LLM in OpenAI format.</p> <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" height="40"></a> <a href="https://railway.com/deploy/RhvhdC?referralCode=7mRv9K&utm_medium=integration&utm_source=template&utm_campaign=generic"><img src="https://railway.com/button.svg" alt="Deploy on Railway" height="40"></a> <a href="https://console.aws.amazon.com/cloudshell/home" target="_blank" rel="nofollow"><img src="./.github/deploy-on-aws.png" alt="Deploy on AWS" height="40"></a> <a href="https://ssh.cloud.google.com/cloudshell/editor?cloudshell_git_repo=https%3A%2F%2Fgithub.com%2FBerriAI%2Flitellm&cloudshell_workspace=terraform%2Flitellm%2Fgcp%2Fexamples%2Fdefault&cloudshell_tutorial=TUTORIAL.md&cloudshell_image=gcr.io/ds-artifacts-cloudshell/deploystack_custom_image&shellonly=true" target="_blank" rel="nofollow"><img src="./.github/deploy-on-gcp.png" alt="Deploy on GCP" height="40"></a> </p> </p> <h4 align="center"><a href="https://docs.litellm.ai/docs/simple_proxy" target="_blank">LiteLLM Proxy Server (AI Gateway)</a> | <a href="https://docs.litellm.ai/docs/enterprise#hosted-litellm-proxy" target="_blank"> Hosted Proxy</a> | <a href="https://litellm.ai/enterprise"target="_blank">Enterprise Tier</a> | <a href="https://www.litellm.ai/ai-gateway" target="_blank">Website</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://github.com/BerriAI/litellm" target="_blank"> <img src="https://img.shields.io/github/stars/BerriAI/litellm.svg?style=social" alt="GitHub Stars"> </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://www.litellm.ai/support"> <img src="https://img.shields.io/static/v1?label=Chat%20on&message=Slack&color=black&logo=Slack&style=flat-square" alt="Slack"> </a> <a href="https://codspeed.io/BerriAI/litellm?utm_source=badge"> <img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed"/> </a> </h4>

<img alt="LiteLLM AI Gateway" src="https://github.com/user-attachments/assets/c5ee0412-6fb5-4fb6-ab5b-bafae4209ca6" />

---

## What is LiteLLM

LiteLLM is an open source AI Gateway that gives you a single, unified interface to call 100+ LLM providers — OpenAI, Anthropic, Gemini, Bedrock, Azure, and more — using the OpenAI format.

Use it as a **Python SDK** for direct library integration, or deploy the **AI Gateway (Proxy Server)** as a centralized service for your team or organization.

[**Jump to LiteLLM Proxy (LLM Gateway) Docs**](https://docs.litellm.ai/docs/simple_proxy) <br> [**Jump to Supported LLM Providers**](https://docs.litellm.ai/docs/providers)

---

## Why LiteLLM

Managing LLM calls across providers gets complicated fast — different SDKs, auth patterns, request formats, and error types for every model. LiteLLM removes that friction:

- **Unified API** — one interface for 100+ LLMs, no provider-specific SDK juggling - **Drop-in OpenAI compatibility** — swap providers without rewriting your code - **Production-ready gateway** — virtual keys, spend tracking, guardrails, load balancing, and an admin dashboard out of the box - **8ms P95 latency** at 1k RPS ([benchmarks](https://docs.litellm.ai/docs/benchmarks))

### OSS Adopters

<table> <tr> <td><img height="60" alt="Stripe" src="https://github.com/user-attachments/assets/f7296d4f-9fbd-460d-9d05-e4df31697c4b" /></td> <td><img height="60" alt="image" src="https://github.com/user-attachments/assets/436fca71-988b-40bb-b5fe-8450c80fdbd0" /></td> <td><img height="60" alt="Google ADK" src="https://github.com/user-attachments/assets/caf270a2-5aee-45c4-8222-41a2070c4f19" /></td> <td><img height="60" alt="Greptile" src="https://github.com/user-attachments/assets/3db0ae72-0843-4005-a56d-bba1dde2193d" /></td> <td><img height="60" alt="OpenHands" src="https://github.com/user-attachments/assets/a6150c4c-149e-4cae-888b-8b92be6e003f" /></td> <td><h2>Netflix</h2></td> <td><img height="60" alt="OpenAI Agents SDK" src="https://github.com/user-attachments/assets/c02f7be0-8c2e-4d27-aea7-7c024bfaebc0" /></td> </tr> </table>

---

## Features

<details open> <summary><b>LLMs</b> - Call 100+ LLMs (Python SDK + AI Gateway)</summary>

[**All Supported Endpoints**](https://docs.litellm.ai/docs/supported_endpoints) - `/chat/completions`, `/responses`, `/embeddings`, `/images`, `/audio`, `/batches`, `/rerank`, `/a2a`, `/messages` and more.

### Python SDK

```shell uv add litellm ```

```python from litellm import completion import os

os.environ["OPENAI_API_KEY"] = "your-openai-key" os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-key"

# OpenAI response = completion(model="openai/gpt-4o", messages=[{"role": "user", "content": "Hello!"}])

# Anthropic response = completion(model="anthropic/claude-sonnet-4-20250514", messages=[{"role": "user", "content": "Hello!"}]) ```

### AI Gateway (Proxy Server)

[**Getting Started - E2E Tutorial**](https://docs.litellm.ai/docs/proxy/docker_quick_start) - Setup virtual keys, make your first request

```shell uv tool install 'litellm[proxy]' litellm --model gpt-4o ```

```python import openai

client = openai.OpenAI(api_key="anything", base_url="http://0.0.0.0:4000") response = client.chat.completions.create( model="gpt-4o", messages=[{"role": "user", "content": "Hello!"}] ) ```

[**Docs: LLM Providers**](https://docs.litellm.ai/docs/providers)

</details>

<details> <summary><b>Agents</b> - Invoke A2A Agents (Python SDK + AI Gateway)</summary>

[**Supported Providers**](https://docs.litellm.ai/docs/a2a#add-a2a-agents) - LangGraph, Vertex AI Agent Engine, Azure AI Foundry, Bedrock AgentCore, Pydantic AI

### Python SDK - A2A Protocol

```python from litellm.a2a_protocol import A2AClient from a2a.types import SendMessageRequest, MessageSendParams from uuid import uuid4

client = A2AClient(base_url="http://localhost:10001")

request = SendMessageRequest( id=str(uuid4()), params=MessageSendParams( message={ "role": "user", "parts": [{"kind": "text", "text": "Hello!"}], "messageId": uuid4().hex, } ) ) response = await client.send_message(request) ```

### AI Gateway (Proxy Server)

**Step 1.** [Add your Agent to the AI Gateway](https://docs.litellm.ai/docs/a2a#adding-your-agent) — set `protocolVersion` to `1.0` or `0.3` per agent

**Step 2.** Call Agent via A2A SDK (requires `a2a-sdk>=1.1.0`)

```python import httpx from a2a.client import A2ACardResolver, ClientConfig, ClientFactory from a2a.types import Message, Part, Role, SendMessageRequest from a2a.utils.constants import TransportProtocol from uuid import uuid4

base_url = "http://localhost:4000/a2a/my-agent" # LiteLLM proxy + agent name headers = {"Authorization": "Bearer sk-1234"} # LiteLLM Virtual Key

async with httpx.AsyncClient(headers=headers, timeout=60.0) as http_client: resolver = A2ACardResolver(httpx_client=http_client, base_url=base_url) agent_card = await resolver.get_agent_card() config = ClientConfig( httpx_client=http_client, streaming=False, supported_protocol_bindings=[TransportProtocol.JSONRPC, TransportProtocol.HTTP_JSON], ) client = ClientFactory(config).create(agent_card)

request = SendMessageRequest( message=Message( message_id=uuid4().hex, role=Role.ROLE_USER, parts=[Part(text="Hello!")], ) ) async for event in client.send_message(request): populated = event.ListFields() if populated and populated[0][0].name in ("message", "msg"): print("".join(getattr(p, "text", "") or "" for p in populated[0][1].parts)) ```

[**Docs: A2A Agent Gateway**](https://docs.litellm.ai/docs/a2a)

</details>

<details> <summary><b>MCP Tools</b> - Connect MCP servers to any LLM (Python SDK + AI Gateway)</summary>

### Python SDK - MCP Bridge

```python from mcp import ClientSession, StdioServerParameters from mcp.client.stdio import stdio_client from litellm import experimental_mcp_client import litellm

server_params = StdioServerParameters(command="python", args=["mcp_server.py"])

async with stdio_client(server_params) as (read, write): async with ClientSession(read, write) as session: await session.initialize()

# Load MCP tools in OpenAI format tools = await experimental_mcp_client.load_mcp_tools(session=session, format="openai")

# Use with any LiteLLM model response = await litellm.acompletion( model="gpt-4o", messages=[{"role": "user", "content": "What's 3 + 5?"}], tools=tools ) ```

### AI Gateway - MCP Gateway

**Step 1.** [Add your MCP Server to the AI Gateway](https://docs.litellm.ai/docs/mcp#adding-your-mcp)

**Step 2.** Call MCP tools via `/chat/completions`

```bash curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \ -H 'Authorization: Bearer sk-1234' \ -H 'Content-Type: application/json' \ -d '{ "model": "gpt-4o", "messages": [{"role": "user", "content": "Summarize the latest open PR"}], "tools": [{ "type": "mcp", "server_url": "litellm_proxy/mcp/github", "server_label": "github_mcp", "require_approval": "never" }] }' ```

### Use with Cursor IDE

```json { "mcpServers": { "LiteLLM": { "url": "http://localhost:4000/mcp/", "headers": { "x-litellm-api-key": "Bearer sk-1234" } } } } ```

[**Docs: MCP Gateway**](https://docs.litellm.ai/docs/mcp)

</details>

### Supported Providers ([Website Supported Models](https://models.litellm.ai/) | [Docs](https://docs.litellm.ai/docs/providers))

| Provider | `/chat/completions` | `/messages` | `/responses` | `/embeddings` | `/image/generations` | `/audio/transcriptions` | `/audio/speech` | `/moderations` | `/batches` | `/rerank` | |-------------------------------------------------------------------------------------|---------------------|-------------|--------------|---------------|----------------------|-------------------------|-----------------|----------------|-----------|-----------| | [Abliteration (`abliteration`)](https://docs.litellm.ai/docs/providers/abliteration) | ✅ | | | | | | | | | | | [AI/ML API (`aiml`)](https://docs.litellm.ai/docs/providers/aiml) | ✅ | ✅ | ✅ | ✅ | ✅ | | | | | | | [AI21 (`ai21`)](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ | | | | | | | | | [AI21 Chat (`ai21_chat`)](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ | | | | | | | | | [Aleph Alpha](https://docs.litellm.ai/docs/providers/aleph_alpha) | ✅ | ✅ | ✅ | | | | | | | | | [Amazon Nova](https://docs.litellm.ai/docs/providers/amazon_nova) | ✅ | ✅ | ✅ | | | | | | | | | [Anthropic (`anthropic`)](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ | | | | | | ✅ | | | [Anthropic Text (`anthropic_text`)](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ | | | | | | ✅ | | | [Anyscale](https://docs.litellm.ai/docs/providers/anyscale) | ✅ | ✅ | ✅ | | | | | | | | | [AssemblyAI (`assemblyai`)](https://docs.litellm.ai/docs/pass_through/assembly_ai) | ✅ | ✅ | ✅ | | | ✅ | | | | | | [Auto Router (`auto_router`)](https://docs.litellm.ai/docs/proxy/auto_routing) | ✅ | ✅ | ✅ | | | | | | | | | [AWS - Bedrock (`bedrock`)](https://docs.litellm.ai/docs/providers/bedrock) | ✅ | ✅ | ✅ | ✅ | | | | | | ✅ | | [AWS - Sagemaker (`sagemaker`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ | ✅ | | | | | | | | [Azure (`azure`)](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | | [Azure AI (`azure_ai`)](https://docs.litellm.ai/docs/providers/azure_ai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | | [Azure Text (`azure_text`)](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ | | | ✅ | ✅ | ✅ | ✅ | | | [Baseten (`baseten`)](https://docs.litellm.ai/docs/providers/baseten) | ✅ | ✅ | ✅ | | | | | | | | | [Bytez (`bytez`)](https://docs.litellm.ai/docs/providers/bytez) | ✅ | ✅ | ✅ | | | | | | | | | [Cerebras (`cerebras`)](https://docs.litellm.ai/docs/providers/cerebras) | ✅ | ✅ | ✅ | | | | | | | | | [Clarifai (`clarifai`)](https://docs.litellm.ai/docs/providers/clarifai) | ✅ | ✅ | ✅ | | | | | | | | | [Cloudflare AI Workers (`cloudflare`)](https://docs.litellm.ai/docs/providers/cloudflare_workers) | ✅ | ✅ | ✅ | | | | | | | | | [Codestral (`codestral`)](https://docs.litellm.ai/docs/providers/codestral) | ✅ | ✅ | ✅ | | | | | | | | | [Cohere (`cohere`)](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ | ✅ | | | | | | ✅ | | [Cohere Chat (`cohere_chat`)](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ | | | | | | | | | [CometAPI (`cometapi`)](https://docs.litellm.ai/docs/providers/cometapi) | ✅ | ✅ | ✅ | ✅ | | | | | | | | [CompactifAI (`compactifai`)](https://docs.litellm.ai/docs/providers/compactifai) | ✅ | ✅ | ✅ | | | | | | | | | [Custom (`custom`)](https://docs.litellm.ai/docs/providers/custom_llm_server) | ✅ | ✅ | ✅ | | | | | | | | | [Custom OpenAI (`custom_openai`)](https://docs.litellm.ai/docs/providers/openai_compatible) | ✅ | ✅ | ✅ | | | ✅ | ✅ | ✅ | ✅ | | | [Dashscope (`dashscope`)](https://docs.litellm.ai/docs/providers/dashscope) | ✅ | ✅ | ✅ | ✅ | | | | | | ✅ | | [Databricks (`databricks`)](https://docs.litellm.ai/docs/providers/databricks) | ✅ | ✅ | ✅ | | | | | | | | | [DataRobot (`datarobot`)](https://docs.litellm.ai/docs/providers/datarobot) | ✅ | ✅ | ✅ | | | | | | | | | [Deepgram (`deepgram`)](https://docs.litellm.ai/docs/providers/deepgram) | ✅ | ✅ | ✅ | | | ✅ | | | | | | [DeepInfra (`deepinfra`)](https://docs.litellm.ai/docs/providers/deepinfra) | ✅ | ✅ | ✅ | | | | | | | | | [Deepseek (`deepseek`)](https://docs.litellm.ai/docs/providers/deepseek) | ✅ | ✅ | ✅ | | | | | | | | | [ElevenLabs (`elevenlabs`)](https://docs.litellm.ai/docs/providers/elevenlabs) | ✅ | ✅ | ✅ | | | ✅ | ✅ | | | | | [Empower (`empower`)](https://docs.litellm.ai/docs/providers/empower) | ✅ | ✅ | ✅ | | | | | | | | | [Fal AI (`fal_ai`)](https://docs.litellm.ai/docs/providers/fal_ai) | ✅ | ✅ | ✅ | | ✅ | | | | | | | [Featherless AI (`featherless_ai`)](https://docs.litellm.ai/docs/providers/featherless_ai) | ✅ | ✅ | ✅ | | | | | | | | | [Fireworks AI (`fireworks_ai`)](https://docs.litellm.ai/docs/providers/fireworks_ai) | ✅ | ✅ | ✅ | | | | | | | | | [FriendliAI (`friendliai`)](https://docs.litellm.ai/docs/providers/friendliai) | ✅ | ✅ | ✅ | | | | | | | | | [Galadriel (`galadriel`)](https://docs.litellm.ai/docs/providers/galadriel) | ✅ | ✅ | ✅ | | | | | | | | | [GitHub Copilot (`github_copilot`)](https://docs.litellm.ai/docs/providers/github_copilot) | ✅ | ✅ | ✅ | ✅ | | | | | | | | [GitHub Models (`github`)](https://docs.litellm.ai/docs/providers/github) | ✅ | ✅ | ✅ | | | | | | | | | [Google - PaLM](https://docs.litellm.ai/docs/providers/palm) | ✅ | ✅ | ✅ | | | | | | | | | [Google - Vertex AI (`vertex_ai`)](https://docs.litellm.ai/docs/providers/vertex) | ✅ | ✅ | ✅ | ✅ | ✅ | | | | | | | [Google AI Studio - Gemini (`gemini`)](https://docs.litellm.ai/docs/providers/gemini) | ✅ | ✅ | ✅ | | | | | | | | | [GradientAI (`gradient_ai`)](https://docs.litellm.ai/docs/providers/gradient_ai) | ✅ | ✅ | ✅ | | | | | | | | | [Groq AI (`groq`)](https://docs.litellm.ai/docs/providers/groq) | ✅ | ✅ | ✅ | | | | | | | | | [Heroku (`heroku`)](https://docs.litellm.ai/docs/providers/heroku) | ✅ | ✅ | ✅ | | | | | | | | | [Hosted VLLM (`hosted_vllm`)](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ | | | | | | | | | [Huggingface (`huggingface`)](https://docs.litellm.ai/docs/providers/huggingface) | ✅ | ✅ | ✅ | ✅ | | | | | | ✅ | | [Hyperbolic (`hyperbolic`)](https://docs.litellm.ai/docs/providers/hyperbolic) | ✅ | ✅ | ✅ | | | | | | | | | [IBM - Watsonx.ai (`watsonx`)](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ | ✅ | | | | | | | | [Infinity (`infinity`)](https://docs.litellm.ai/docs/providers/infinity) | | | | ✅ | | | | | | | | [Jina AI (`jina_ai`)](https://docs.litellm.ai/docs/providers/jina_ai) | | | | ✅ | | | | | | | | [Lambda AI (`lambda_ai`)](https://docs.litellm.ai/docs/providers/lambda_ai) | ✅ | ✅ | ✅ | | | | | | | | | [Lemonade (`lemonade`)](https://docs.litellm.ai/docs/providers/lemonade) | ✅ | ✅ | ✅ | | | | | | | | | [LiteLLM Proxy (`litellm_proxy`)](https://docs.litellm.ai/docs/providers/litellm_proxy) | ✅ | ✅ | ✅ | ✅ | ✅ | | | | | | | [Llamafile (`llamafile`)](https://docs.litellm.ai/docs/providers/llamafile) | ✅ | ✅ | ✅ | | | | | | | | | [LM Studio (`lm_studio`)](https://docs.litellm.ai/docs/providers/lm_studio) | ✅ | ✅ | ✅ | | | | | | | | | [Maritalk (`maritalk`)](https://docs.litellm.ai/docs/providers/maritalk) | ✅ | ✅ | ✅ | | | | | | | | | [Meta - Llama API (`meta_llama`)](https://docs.litellm.ai/docs/providers/meta_llama) | ✅ | ✅ | ✅ | | | | | | | | | [Mistral AI API (`mistral`)](https://docs.litellm.ai/docs/providers/mistral) | ✅ | ✅ | ✅ | ✅ | | | | | | | | [ModelScope (`modelscope`)](https://docs.litellm.ai/docs/providers/modelscope) | ✅ | ✅ | ✅ | | ✅ | | | | | | | [Moonshot (`moonshot`)](https://docs.litellm.ai/docs/providers/moonshot) | ✅ | ✅ | ✅ | | | | | | | | | [Morph (`morph`)](https://docs.litellm.ai/docs/providers/morph) | ✅ | ✅ | ✅ | | | | | | | | | [Nebius AI Studio (`nebius`)](https://docs.litellm.ai/docs/providers/nebius) | ✅ | ✅ | ✅ | ✅ | | | | | | | | [NLP Cloud (`nlp_cloud`)](https://docs.litellm.ai/docs/providers/nlp_cloud) | ✅ | ✅ | ✅ | | | | | | | | | [Novita AI (`novita`)](https://novita.ai/models/llm?utm_source=github_litellm&utm_medium=github_readme&utm_campaign=github_link) | ✅ | ✅ | ✅ | | | | | | | | | [Nscale (`nscale`)](https://docs.litellm.ai/docs/providers/nscale) | ✅ | ✅ | ✅ | | | | | | | | | [Nvidia NIM (`nvidia_nim`)](https://docs.litellm.ai/docs/providers/nvidia_nim) | ✅ | ✅ | ✅ | | | | | | | | | [OCI (`oci`)](https://docs.litellm.ai/docs/providers/oci) | ✅ | ✅ | ✅ | | | | | | | | | [Ollama (`ollama`)](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ | ✅ | | | | | | | | [Ollama Chat (`ollama_chat`)](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ | | | | | | | | | [Oobabooga (`oobabooga`)](https://docs.litellm.ai/docs/providers/openai_compatible) | ✅ | ✅ | ✅ | | | ✅ | ✅ | ✅ | ✅ | | | [OpenAI (`openai`)](https://docs.litellm.ai/docs/providers/openai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | | [OpenAI-like (`openai_like`)](https://docs.litellm.ai/docs/providers/openai_compatible) | | | | ✅ | | | | | | | | [OpenRouter (`openrouter`)](https://docs.litellm.ai/docs/providers/openrouter) | ✅ | ✅ | ✅ | | | | | | | | | [OVHCloud AI Endpoints (`ovhcloud`)](https://docs.litellm.ai/docs/providers/ovhcloud) | ✅ | ✅ | ✅ | | | | | | | | | [Perplexity AI (`perplexity`)](https://docs.litellm.ai/docs/providers/perplexity) | ✅ | ✅ | ✅ | | | | | | | | | [Petals (`petals`)](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ | | | | | | | | | [Pinstripes (`pinstripes`)](https://docs.litellm.ai/docs/providers/pinstripes) | ✅ | ✅ | ✅ | | | | | | | | | [Predibase (`predibase`)](https://docs.litellm.ai/docs/providers/predibase) | ✅ | ✅ | ✅ | | | | | | | | | [Recraft (`recraft`)](https://docs.litellm.ai/docs/providers/recraft) | | | | | ✅ | | | | | | | [Replicate (`replicate`)](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ | | | | | | | | | [Sagemaker Chat (`sagemaker_chat`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ | | | | | | | | | [Sambanova (`sambanova`)](https://docs.litellm.ai/docs/providers/sambanova) | ✅ | ✅ | ✅ | | | | | | | | | [Snowflake (`snowflake`)](https://docs.litellm.ai/docs/providers/snowflake) | ✅ | ✅ | ✅ | | | | | | | | | [Text Completion Codestral (`text-completion-codestral`)](https://docs.litellm.ai/docs/providers/codestral) | ✅ | ✅ | ✅ | | | | | | | | | [Text Completion OpenAI (`text-completion-openai`)](https://docs.litellm.ai/docs/providers/text_completion_openai) | ✅ | ✅ | ✅ | | | ✅ | ✅ | ✅ | ✅ | | | [Together AI (`together_ai`)](https://docs.litellm.ai/docs/providers/togetherai) | ✅ | ✅ | ✅ | | | | | | | | | [Topaz (`topaz`)](https://docs.litellm.ai/docs/providers/topaz) | ✅ | ✅ | ✅ | | | | | | | | | [Triton (`triton`)](https://docs.litellm.ai/docs/providers/triton-inference-server) | ✅ | ✅ | ✅ | | | | | | | | | [V0 (`v0`)](https://docs.litellm.ai/docs/providers/v0) | ✅ | ✅ | ✅ | | | | | | | | | [Vercel AI Gateway (`vercel_ai_gateway`)](https://docs.litellm.ai/docs/providers/vercel_ai_gateway) | ✅ | ✅ | ✅ | | | | | | | | | [VLLM (`vllm`)](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ | | | | | | | | | [Volcengine (`volcengine`)](https://docs.litellm.ai/docs/providers/volcano) | ✅ | ✅ | ✅ | | | | | | | | | [Voyage AI (`voyage`)](https://docs.litellm.ai/docs/providers/voyage) | | | | ✅ | | | | | | | | [WandB Inference (`wandb`)](https://docs.litellm.ai/docs/providers/wandb_inference) | ✅ | ✅ | ✅ | | | | | | | | | [Watsonx Text (`watsonx_text`)](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ | | | | | | | | | [xAI (`xai`)](https://docs.litellm.ai/docs/providers/xai) | ✅ | ✅ | ✅ | | | | | | | | | [Xinference (`xinference`)](https://docs.litellm.ai/docs/providers/xinference) | | | | ✅ | | | | | | |

[**Read the Docs**](https://docs.litellm.ai/docs/)

---

## Get Started

You can use LiteLLM through either the Proxy Server or Python SDK. Both give you a unified interface to access multiple LLMs (100+ LLMs). Choose the option that best fits your needs:

<table style={{width: '100%', tableLayout: 'fixed'}}> <thead> <tr> <th style={{width: '14%'}}></th> <th style={{width: '43%'}}><strong><a href="https://docs.litellm.ai/docs/simple_proxy">LiteLLM AI Gateway</a></strong></th> <th style={{width: '43%'}}><strong><a href="https://docs.litellm.ai/docs/">LiteLLM Python SDK</a></strong></th> </tr> </thead> <tbody> <tr> <td style={{width: '14%'}}><strong>Use Case</strong></td> <td style={{width: '43%'}}>Central service (LLM Gateway) to access multiple LLMs</td> <td style={{width: '43%'}}>Use LiteLLM directly in your Python code</td> </tr> <tr> <td style={{width: '14%'}}><strong>Who Uses It?</strong></td> <td style={{width: '43%'}}>Gen AI Enablement / ML Platform Teams</td> <td style={{width: '43%'}}>Developers building LLM projects</td> </tr> <tr> <td style={{width: '14%'}}><strong>Key Features</strong></td> <td style={{width: '43%'}}>Centralized API gateway with authentication and authorization, multi-tenant cost tracking and spend management per project/user, per-project customization (logging, guardrails, caching), virtual keys for secure access control, admin dashboard UI for monitoring and management</td> <td style={{width: '43%'}}>Direct Python library integration in your codebase, Router with retry/fallback logic across multiple deployments (e.g. Azure/OpenAI) - <a href="https://docs.litellm.ai/docs/routing">Router</a>, application-level load balancing and cost tracking, exception handling with OpenAI-compatible errors, observability callbacks (Lunary, MLflow, Langfuse, etc.)</td> </tr> </tbody> </table>

**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+).

### Deploy on AWS or GCP with Terraform

Run the LiteLLM proxy as a production-ready componentized stack (gateway, backend, UI on separate services; managed Postgres + Redis + object store) using the published Terraform modules. Both modules are on the [public Terraform Registry](https://registry.terraform.io/namespaces/BerriAI) — no auth needed.

#### AWS — ECS Fargate + Aurora + ElastiCache + ALB

[![Launch in AWS CloudShell](https://img.shields.io/badge/Launch-AWS_CloudShell-FF9900?logo=amazon-aws&logoColor=white)](https://console.aws.amazon.com/cloudshell/home) — opens an in-browser shell, already authenticated to your AWS account. Once inside, run:

```bash git clone https://github.com/BerriAI/litellm.git cd litellm/terraform/litellm/aws/examples/default cp terraform.tfvars.example terraform.tfvars # edit region/tenant/env terraform init && terraform apply ```

[Module page →](https://registry.terraform.io/modules/BerriAI/litellm/aws/latest)

Or call the module from your own root config:

```hcl # main.tf terraform { required_version = ">= 1.6.0" required_providers { aws = { source = "hashicorp/aws", version = "~> 5.60" } } }

provider "aws" { region = "us-west-2" }

module "litellm" { source = "BerriAI/litellm/aws" version = "~> 1.89"

region = "us-west-2" azs = ["us-west-2a", "us-west-2b"] tenant = "acme" env = "prod"

# Production: provide an ACM cert. Without one, set allow_plaintext_alb = true # (dev/trial only). # acm_certificate_arn = "arn:aws:acm:us-west-2:111122223333:certificate/..." allow_plaintext_alb = true }

output "litellm_url" { value = module.litellm.alb_dns_name } ```

```bash terraform init terraform apply ```

Provider API keys live in AWS Secrets Manager; reference ARNs via `gateway_extra_secrets`. Full input list and architecture diagram on the [registry page](https://registry.terraform.io/modules/BerriAI/litellm/aws/latest?tab=inputs).

#### GCP — Cloud Run + Cloud SQL + Memorystore + HTTPS LB

[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.png)](https://ssh.cloud.google.com/cloudshell/editor?cloudshell_git_repo=https%3A%2F%2Fgithub.com%2FBerriAI%2Flitellm&cloudshell_workspace=terraform%2Flitellm%2Fgcp%2Fexamples%2Fdefault&cloudshell_tutorial=TUTORIAL.md&cloudshell_image=gcr.io/ds-artifacts-cloudshell/deploystack_custom_image&shellonly=true)

Real 1-click. Opens Cloud Shell, clones this repo, and walks you through `terraform apply` via a built-in [DeployStack tutorial](./terraform/litellm/gcp/examples/default/TUTORIAL.md) — pick the project, the tutorial sets up the Artifact Registry remote repo, writes `terraform.tfvars` from your answers, and runs apply.

[Module page →](https://registry.terraform.io/modules/BerriAI/litellm/google/latest)

To call the module from your own config instead, Cloud Run can't pull from `ghcr.io` directly, so first set up a one-time Artifact Registry remote repo backed by GHCR:

```bash gcloud artifacts repositories create litellm \ --location=us-central1 \ --repository-format=docker \ --mode=remote-repository \ --remote-docker-repo=https://ghcr.io \ --project=my-gcp-project ```

Then:

```hcl # main.tf terraform { required_version = ">= 1.6.0" required_providers { google = { source = "hashicorp/google", version = "~> 6.10" } google-beta = { source = "hashicorp/google-beta", version = "~> 6.10" } } }

provider "google" { project = "my-gcp-project"; region = "us-central1" } provider "google-beta" { project = "my-gcp-project"; region = "us-central1" }

module "litellm" { source = "BerriAI/litellm/google" version = "~> 1.89"

project_id = "my-gcp-project" region = "us-central1" tenant = "acme" env = "prod"

# Replace my-gcp-project with your GCP project ID (same value as project_id above). image_registry = "us-central1-docker.pkg.dev/my-gcp-project/litellm/berriai"

# Production: provide DNS already pointing at the LB IP for Google-managed certs. # Without one, set allow_plaintext_lb = true (dev/trial only). # lb_domains = ["proxy.example.com"] allow_plaintext_lb = true }

output "litellm_url" { value = module.litellm.load_balancer_url } ```

```bash terraform init terraform apply ```

Provider API keys live in Secret Manager; reference resource IDs (e.g. `projects/my-gcp-project/secrets/openai-api-key`) via `gateway_extra_secrets`. Full input list and architecture diagram on the [registry page](https://registry.terraform.io/modules/BerriAI/litellm/google/latest?tab=inputs).

#### Both stacks include

- The full componentized split (gateway / backend / UI as independent services) - Managed Postgres (writer + reader) and Redis - Versioned object store for proxy state + file uploads - An auto-generated `LITELLM_MASTER_KEY` in your cloud's secret manager - A one-off migration job that runs `prisma migrate deploy` before the proxy starts - The same `proxy_config` surface as the [Helm chart](./helm/litellm/) — pass YAML as a typed map

The Terraform modules live at [`terraform/litellm/aws/`](./terraform/litellm/aws/) and [`terraform/litellm/gcp/`](./terraform/litellm/gcp/) in this repo; the registry entries are read-only mirrors updated on each release.

### Run in Developer Mode #### Services 1. Setup .env file in root 2. Run dependent services `docker-compose up db prometheus`

#### Backend 1. Run `make bootstrap` 2. Start proxy backend: `uv run python litellm/proxy/proxy_cli.py`

#### Frontend 1. Navigate to `ui/litellm-dashboard` (dependencies were already installed w/ `make bootstrap`) 2. Start dashboard: `npm run dev`

### Verify Docker Image Signatures

All LiteLLM Docker images published to GHCR are signed with [cosign](https://docs.sigstore.dev/cosign/overview/). Every release is signed with the same key introduced in [commit `0112e53`](https://github.com/BerriAI/litellm/commit/0112e53046018d726492c814b3644b7d376029d0).

**Verify using the pinned commit hash (recommended):**

A commit hash is cryptographically immutable, so this is the strongest way to ensure you are using the original signing key:

```bash cosign verify \ --key https://raw.githubusercontent.com/BerriAI/litellm/0112e53046018d726492c814b3644b7d376029d0/cosign.pub \ ghcr.io/berriai/litellm:<release-tag> ```

**Verify using a release tag (convenience):**

Tags are protected in this repository and resolve to the same key. This option is easier to read but relies on tag protection rules:

```bash cosign verify \ --key https://raw.githubusercontent.com/BerriAI/litellm/<release-tag>/cosign.pub \ ghcr.io/berriai/litellm:<release-tag> ```

Replace `<release-tag>` with the version you are deploying (e.g. `v1.83.0-stable`).

---

# Enterprise For companies that need better security, user management and professional support

[Get an Enterprise License](https://litellm.ai/enterprise) [Talk to founders](https://enterprise.litellm.ai/demo)

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 uv 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).

> **📖 Contributing to documentation?** The LiteLLM docs have moved to a separate repository: [BerriAI/litellm-docs](https://github.com/BerriAI/litellm-docs). Please open doc PRs there. Docs are served at [docs.litellm.ai](https://docs.litellm.ai).

## 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://www.litellm.ai/support) - Our emails ✉️ ishaan@berri.ai / krrish@berri.ai

# Contributors

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<a href="https://github.com/BerriAI/litellm/graphs/contributors"> <img src="https://contrib.rocks/image?repo=BerriAI/litellm" /> </a>

дальше в дело
Собрать это в маршрут
все маршруты →
не хочешь разбираться сам
Сделаю это под задачу
форматы и цены →
ещё разборы