litellm

<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>
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        <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">
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        <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'