litellm/README.md
ishaan-berri 0a17c7c39f
feat: add LiteLLM Rust workspace with Mistral OCR bridge (#31033)
* docs(readme): add Deploy on AWS/GCP with Terraform section

Adds a quickstart for the two published Terraform modules on the public
registry (BerriAI/litellm/aws and BerriAI/litellm/google). Copy-paste
main.tf for each cloud, the one-time GCP Artifact Registry remote-repo
command, and pointers to the registry pages for the full input surface.

Sits inside the Get Started section, between the gateway/SDK table and
Run in Developer Mode -- where someone scanning the README for "how do I
deploy this" will land.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* docs(readme): add 1-click deploy buttons for AWS + GCP

GCP gets the real 1-click: Open in Cloud Shell badge that clones the repo
and walks through `terraform apply` via the existing DeployStack
tutorial (already shipped at terraform/litellm/gcp/examples/default/
TUTORIAL.md). User just picks a project.

AWS gets a soft 1-click: a Launch in AWS CloudShell badge that opens an
in-browser, already-authenticated shell. User runs four commands
(clone + cd + cp tfvars + terraform apply) once inside. There's no
native AWS deeplink that pre-clones a repo + runs a tutorial -- CFN
"Launch Stack" + CodeBuild would be needed for that, and that's a
separate piece of work.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* docs(readme): move AWS + GCP deploy buttons next to Render button

* docs(readme): unify deploy button sizes and badge styles

* docs(readme): bump deploy button height to 48 to match Render/Railway

* docs(readme): bump AWS/GCP badge height to compensate for SVG padding

* docs(readme): bump AWS/GCP badge height to 72

* docs(readme): bump AWS/GCP badge height to 84

* fix(readme): make deploy buttons same height (48px)

https://claude.ai/code/session_01MxQRMHSDXbqJh74rF86UBc

* docs(readme): flag GCP project ID substitution in image_registry

* docs(readme): equalize deploy button heights and fix Cloud Shell button font

GitHub rewrites an image's height attribute to "height: auto; max-height: Npx", which only caps and never stretches, so each image renders at its intrinsic height. The AWS/GCP shields badges are intrinsically 28px while the Render/Railway buttons are 40px, leaving the row uneven regardless of the height="48" we set. Replace the two shields badges with committed 40px PNGs so all four header buttons render at the same 40px.

Also swap the Cloud Shell button from open-btn.svg to open-btn.png. The SVG renders its label as live text with font-family "Roboto, Sans" and no generic fallback; since neither font exists in GitHub's render environment, the text fell back to a serif (Times New Roman). The PNG bakes in the correct typeface.

* docs(readme): collapse Railway deploy anchor to a single line

The Railway button wrapped its img across indented lines, so the anchor contained leading and trailing whitespace. GitHub underlines link content, rendering that whitespace as a small blue underline beside the button. Put the anchor on one line like the other three buttons so there is no inner whitespace to underline.

* Add Claude Fable 5 cost map entries as a data-only hotfix

Backports only the model map changes from #30064 so deployments on
released litellm versions pick up Fable 5 pricing, context window, and
the adaptive thinking flag through the hosted cost map fetch without
upgrading. Includes the supports_sampling_params flag on the 28
Fable 5 / Opus 4.7 / Opus 4.8 entries (ignored by released code, read
by the gating that ships with the next release) and the matching
one-line schema declaration so the map validation test passes.

https://claude.ai/code/session_01MZarYYT3aS7DxaNjoax6Gm

* Add litellm rust workspace with mistral ocr bridge

* address greptile rust ocr feedback

* Simplify rust ocr entrypoint

* rust(core): add Auth/Http/Network error variants

* rust: add reqwest (rustls-tls) workspace dependency

* rust(providers): depend on reqwest

* rust(mistral): add complete_url + resolve_api_key helpers

* rust(providers): end-to-end run_ocr orchestrator with shared client + timeout

* rust(bridge): depend on litellm-core

* rust(bridge): add GIL release accounting

* rust(bridge): end-to-end ocr() + gil_stats(), GIL released for HTTP

* ocr: add minimal Rust bridge (use_litellm_rust + rust_ocr)

* ocr: route mistral to Rust when enabled; keep bare-str file rejection

* litellm: export use_litellm_rust()

* test(ocr): cover Rust OCR routing + toggle

* rust: stop ignoring Cargo.lock

* rust: commit Cargo.lock for reproducible builds

* ci(rust): build with --locked to enforce the lockfile

* Potential fix for pull request finding 'CodeQL / Module-level cyclic import'

Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>

* Potential fix for pull request finding 'CodeQL / Module-level cyclic import'

Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>

* ocr: lazily import rust bridge inside ocr() to break the import cycle the CodeQL autofix mangled

* ocr: guard OCRResponse under TYPE_CHECKING so the annotation resolves

* ocr: modernize rust_bridge typing (PEP 604, drop typing.Any/Dict) to satisfy strict-rule gate

* ci: re-trigger checks

* ci: re-trigger checks

* Potential fix for pull request finding 'CodeQL / Cyclic import'

Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>

* Potential fix for pull request finding 'CodeQL / Cyclic import'

Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>

* ocr: make rust_bridge a leaf (return raw dict, no litellm import) so the CodeQL autofix stops re-breaking it

* ocr: wrap rust bridge dict into OCRResponse at the call site

* test(ocr): assert rust_ocr returns the raw bridge dict

* test(interactions): add budget_exceeded to expected status enum (Google updated the published spec)

* ocr: resolve mistral key via get_secret_str before the rust path (secret-manager parity)

* test(ocr): assert rust path resolves key via secret manager

* rust(mistral): document that secret-manager resolution happens on the Python side

* fix(ocr): honor timeout, logging, and missing-bridge fallback on Rust OCR path

- Forward the caller's timeout into the Rust bridge so the fixed 600s client
  ceiling no longer overrides shorter deadlines or the library default.
- Run update_from_kwargs and pre_call before invoking the Rust shortcut so
  observability, callbacks, and spend tracking match the Python path.
- Fall back to the Python OCR path when litellm_python_bridge isn't importable
  instead of raising ImportError to callers.
- Truncate upstream Mistral OCR error bodies before they cross the host
  boundary to avoid leaking document or prompt contents in CoreError::Http.

* fix(ocr): log resolved api_base and headers on Rust path

* refactor(ocr): inject the rust bridge via a typed seam, drop the importlib cycle dodge

The rust OCR path was reached through importlib.import_module both for the
bridge module and for probing the native extension, purely to keep CodeQL from
flagging a cyclic import. rust_bridge has no litellm imports, so it is a leaf
and main.py can import it statically without any cycle; the dance is gone

Bridge selection now goes through a typed RustOcr Protocol and a load_rust_ocr()
seam. use_litellm_rust() takes an optional injected bridge, so an embedder (or a
test) can supply an alternative without reaching into sys.modules. The rust-path
body moves into _run_rust_ocr(), which receives its dependencies (the bridge
callable, the logging object, the key resolver) as arguments and is unit-tested
by passing fakes in rather than monkeypatching class methods or module globals

The tests are rewritten around that injection: the bridge is provided via
use_litellm_rust(ocr=...), pre_call is observed through a spy logging object, and
the missing-extension fallback is covered by load_rust_ocr() returning None when
no wheel is built. Types were tightened along the way (a cast for the logging
object, OCRResponse.model_validate for the bridge result) so no basedpyright
per-rule count increases

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* fix(ocr): preserve injected rust bridge across toggle calls

use_litellm_rust() unconditionally assigned the keyword default of None to
_rust_ocr_impl, so any call without ocr= silently dropped a previously
injected bridge. Use a sentinel default so omission preserves the impl
while ocr=None still clears it explicitly.

* ci: run tests/test_litellm/ocr in the misc unit-test group

The OCR test directory was not wired into any CI test group, so its
coverage never uploaded to Codecov and patch coverage failed for new
OCR lines. Add it to the misc group.

* test(ocr): cover compiled-extension load and Python fallback paths

Adds two tests so the Rust bridge module hits 100% and the ocr()
fallback-to-Python branch is exercised:
- load_rust_ocr() returning the compiled extension's ocr callable
- ocr() degrading to the HTTP handler when no bridge is available

* style(ocr): use PEP 604 X | None annotations in rust_bridge

Converts Optional[X]/Union[...] to the X | None form so the new OCR
code stays under the UP045 strict-rule budget gate (lint job). Safe at
runtime — the module already has 'from __future__ import annotations'.

---------

Co-authored-by: shin-berri <shin-laptop@berri.ai>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Krrish Dholakia <krrish+github@berri.ai>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-06-23 13:16:47 -07:00

660 lines
34 KiB
Markdown

<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)
**Step 2.** Call Agent via A2A SDK
```python
from a2a.client import A2ACardResolver, A2AClient
from a2a.types import MessageSendParams, SendMessageRequest
from uuid import uuid4
import httpx
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) as httpx_client:
resolver = A2ACardResolver(httpx_client=httpx_client, base_url=base_url)
agent_card = await resolver.get_agent_card()
client = A2AClient(httpx_client=httpx_client, agent_card=agent_card)
request = SendMessageRequest(
id=str(uuid4()),
params=MessageSendParams(
message={
"role": "user",
"parts": [{"kind": "text", "text": "Hello!"}],
"messageId": uuid4().hex,
}
)
)
response = await client.send_message(request)
```
[**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. (In root) create virtual environment `python -m venv .venv`
2. Activate virtual environment `source .venv/bin/activate`
3. Install dependencies `uv sync --all-extras --group proxy-dev`
4. `uv run prisma generate`
5. `prisma generate`
6. Start proxy backend `python litellm/proxy/proxy_cli.py`
#### Frontend
1. Navigate to `ui/litellm-dashboard`
2. Install dependencies `npm install`
3. Run `npm run dev` to start the dashboard
### 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
<!-- 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>