mirror of
https://github.com/BerriAI/litellm.git
synced 2026-10-12 03:48:56 +00:00
* Add ScaleDown model pricing Registers the five ScaleDown models in the pricing map. ScaleDown bills on input tokens only, so output_cost_per_token is zero for every entry. The classify and decisions models bill at $0.04 per million input tokens, and extract, summarize, and compress bill at $0.05 per million. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> * Price all ScaleDown models at $0.04 per million and drop unverified context limits Every ScaleDown model now bills $0.04 per million input tokens. The 32000-token max_input_tokens/max_output_tokens values were not confirmed against the service, so they are removed rather than registered. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Price all ScaleDown models at $0.05 per million input tokens This is the standard rate in ScaleDown's billing and matches the usage dashboard. The Decisions usage.cost field is not used for pricing. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Add regression tests for the ScaleDown pricing entries Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Cite the source of the ScaleDown rate in the pricing tests and type them Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Add ScaleDown as a chat provider ScaleDown serves five models over two wire protocols. extract, summarize, and compress speak OpenAI chat on /v1/chat/completions, while classify and decisions implement the Jev Decisions API on /v1/scaledown, taking a state object plus a questions map and returning one typed answer per question. The provider authenticates with x-api-key rather than a bearer token, and the decisions models need a non-chat request body, so it routes through the HTTP handler instead of the OpenAI passthrough. Malformed decisions requests are rejected locally with a message naming the problem, so callers do not have to decode an opaque 422 from upstream. Decisions bills one model call per question, so the cost upstream reports is passed through rather than re-estimated from token counts. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> * Route ScaleDown domain models to the native API and stop trusting usage.cost The /v1/chat/completions and /v1/models routes return 403 on api.scaledown.xyz, so extract, summarize and compress now call the native /extract, /summarization/abstractive and /compress/raw/ endpoints. The default api_base is the bare host; a trailing /v1 is stripped and re-added only for decisions. The Decisions usage.cost field was about 600x the dashboard amount, so it is no longer passed through; cost is computed from input tokens at the registered rate. Native responses are returned unchanged as JSON, including the _value/_span_anchor wrappers on nested extraction. They carry no output token count, so completion_tokens is reported as 0 and documented as unmeasured. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Move ScaleDown translation into llms/ and address review findings - Dispatch moves to llms/scaledown/chat/handler.py; main.py keeps a thin call and get_llm_provider_logic.py no longer has a ScaleDown branch, since the config resolves key and base URL itself. - questions passed via extra_body are merged and validated after the shared merge (sign_request), so the documented extra_body path works. - extra_body can no longer change the upstream model, and decisions state may carry a document but not text, so guardrails always see the text. - A custom api_base requires its own api_key; the environment key is only sent to the default host or SCALEDOWN_API_BASE. - Image content parts become the decisions document; max_completion_tokens maps to max_tokens; stream is served as one chunk for every model. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Refuse prompt-bearing extra_body keys and empty-key fallback to the env credential extra_body is merged after guardrails inspect the messages, so each model now accepts only option keys there (extract threshold/top_n, compress compression_rate, decisions questions/state); text, instructions, prompt, context and model are rejected. An empty api_key no longer lets the SCALEDOWN_API_KEY from the environment go to a custom api_base. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Read compress token usage from the real response shape /compress/raw/ nests the per-prompt counts under results and reports the total as a top-level input_tokens; the provider read a top-level original_prompt_tokens that is not there, so compress reported zero tokens and zero cost. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Accept the router's max_retries and word the extra_body error clearly The proxy adds max_retries to every call, which map_openai_params rejected, so every proxied ScaleDown request failed with a 400. It is now accepted and not forwarded. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Return extracted fields from extract, follow schema refs, and meet the type-discipline gate - extract content is now the extracted fields (span anchors dropped, wrappers unwrapped), so it validates against the caller's response_format; the raw payload stays on _hidden_params['scaledown_response']. - Local $ref/$defs in the response_format schema are resolved. - The adapter is rewritten with Final locals, read-only annotations, one raising helper and a typed handler; check_type_discipline reports no violations. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Fix stream_options, schema-guided extract cleaning, document input and multi-image handling - stream_options is accepted and not sent upstream, so include_usage streams work. - Extract output is cleaned against the requested entities, so a field named _value or *_span_anchor is no longer dropped. - Extract and summarize send an image or PDF as the native document fields. - More than one image is rejected instead of silently using the first. - The cost test derives its rate from the cost map. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Cut recursive schema refs at the cycle and cap the expanded entity count A small response_format schema with a self-referencing $def expanded to 4^16 leaves before any request was sent. Refs that point back into themselves are now cut off at that point, and the total expanded entities are capped at 1000 so repeated acyclic refs are rejected with a clear error. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * Bound ref chains and schema nesting so long schemas fail cleanly Resolving a chain of thousands of distinct $refs recursed until RecursionError. Ref resolution is now an iterative walk capped at 32 hops, and nested properties are capped at 32 levels; both raise a clear 400 instead. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> * fix(scaledown): support native classify and preserve extraction results * test(scaledown): include provider regressions in CI shard * fix(scaledown): pass registry typing and bounded recursion checks * docs(scaledown): capture provider setup before and after * fix(scaledown): preserve nullable schemas and reject malformed requests * fix(scaledown): isolate provider dispatch from existing providers * fix(scaledown): preserve the shared dispatch return contract * fix(scaledown): preserve failure logging and reject lossy schemas * fix(scaledown): keep timeout typing annotation on its expression * fix(scaledown): resolve escaped extraction schema references * fix(scaledown): annotate the bounded reference walk * chore(scaledown): remove unused loop suppression --------- Co-authored-by: Claude Opus 5 <noreply@anthropic.com> Co-authored-by: moe-berri <moe@berri.ai>
713 lines
38 KiB
Markdown
713 lines
38 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
|
|
```
|
|
|
|
An independent `litellm-core` distribution provides the Python SDK with the same
|
|
`import litellm` API and runtime dependencies. It has no optional extras, CLI entry
|
|
points, or bundled dashboard. Install one SDK distribution per environment because
|
|
`litellm` and `litellm-core` own overlapping Python files. Use `litellm` for the
|
|
proxy, CLI, and optional extras
|
|
|
|
Build and install core from this checkout while its release integration is pending:
|
|
|
|
```shell
|
|
python scripts/build_core_distribution.py --out-dir dist/core
|
|
python -m pip install dist/core/litellm_core-*.whl
|
|
```
|
|
|
|
The builder requires Git, `uv` and the Rust build toolchain. It reads the release version
|
|
from the root `pyproject.toml`, leaves source files unchanged, and produces a wheel
|
|
and a self-contained sdist in `dist/core`. Run installation in a fresh environment
|
|
without `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 <your-master-key>"} # LiteLLM master key or a 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 <your-master-key>' \
|
|
-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 <your-master-key>"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
```
|
|
|
|
For MCP OAuth, an upstream may advertise dynamic client registration but refuse requests with HTTP 401 or 403. If the provider requires a pre-registered OAuth app, configure its `credentials.client_id` and, when required, `credentials.client_secret` on the MCP server. This skips dynamic registration in the gateway sign-in flow. The provider must approve the app for MCP access; reaching its authorization page does not establish that login or tool calls will succeed
|
|
|
|
[**Docs: MCP Gateway**](https://docs.litellm.ai/docs/mcp)
|
|
|
|
</details>
|
|
|
|
<details>
|
|
<summary><b>Agents</b> - Run Claude Code, Codex, OpenCode or Deep Agents on any model (Python SDK)</summary>
|
|
|
|
### Python SDK - Agents
|
|
|
|
```python
|
|
import litellm
|
|
from litellm import Harness, sandbox
|
|
|
|
result = litellm.agent(
|
|
Harness.CLAUDE_CODE, # or Harness.CODEX, Harness.OPENCODE, Harness.DEEPAGENTS
|
|
"Find why tests/test_router.py is flaky and fix it.",
|
|
sandbox=sandbox.local("./repo"),
|
|
model="litellm_proxy/claude-sonnet-4-5", # a model group on your AI Gateway
|
|
)
|
|
|
|
print(result.text, result.cost, [f.path for f in result.files])
|
|
```
|
|
|
|
Set `LITELLM_PROXY_API_BASE` and `LITELLM_PROXY_API_KEY` and every model call the agent makes goes through your AI Gateway, tagged `harness,claude_code`. Drop the `litellm_proxy/` prefix to call a provider directly. Install `starlette uvicorn` plus the agent's CLI (`claude`, `codex` or `opencode`), or `deepagents langchain-litellm` for Deep Agents.
|
|
|
|
[**Docs: Agent Harnesses**](https://docs.litellm.ai/docs/harness)
|
|
|
|
</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) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [Cognition (`cognition`)](https://docs.litellm.ai/docs/providers/cognition) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [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) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [Eden AI (`edenai`)](https://docs.litellm.ai/docs/providers/edenai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | | |
|
|
| [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) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [Qianwen AI Platform (`qwen_ai_platform`)](https://docs.litellm.ai/docs/providers/qwencloud) | ✅ | ✅ | ✅ | ✅ | ✅ | | | | | ✅ |
|
|
| [QwenCloud (`qwencloud`)](https://docs.litellm.ai/docs/providers/qwencloud) | ✅ | ✅ | ✅ | ✅ | ✅ | | | | | ✅ |
|
|
| [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) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [Sail (`sail`)](https://docs.litellm.ai/docs/providers/sail) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [Sambanova (`sambanova`)](https://docs.litellm.ai/docs/providers/sambanova) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [ScaleDown (`scaledown`)](https://docs.litellm.ai/docs/providers/scaledown) | ✅ | | | | | | | | | |
|
|
| [Snowflake (`snowflake`)](https://docs.litellm.ai/docs/providers/snowflake) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [Strands Decider (`strands_decider`)](https://docs.litellm.ai/docs/providers) | | | | | | | | | | |
|
|
| [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) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [Typesafe Decisions API (`typesafe`)](https://docs.litellm.ai/docs/providers) | | | | | | | | | | |
|
|
| [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) | ✅ | ✅ | ✅ | | | | | | | |
|
|
| [VoyageAI by MongoDB (`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
|
|
|
|
[](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
|
|
|
|
[](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:
|
|
- **Ruff** for formatting, linting, and code quality
|
|
- **basedpyright** 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>
|