litelm
litellm's routing + translation in ~2,900 lines and 2 dependencies (openai, httpx).
litellm routes LLM calls across providers and translates between message formats. That core is buried under 100k+ LOC of proxy servers, caching layers, cost tracking, and dozens of features most users never touch. litelm extracts just the call path — model routing, message translation, streaming, tool use, embeddings — and nothing else. No Router class, no proxy, no caching.
Install
pip install litelm # openai + httpx
pip install litelm[anthropic] # + anthropic SDK
pip install litelm[bedrock] # + boto3
pip install litelm[all] # everything
Usage
import litelm
# Basic completion
response = litelm.completion("openai/gpt-4o", messages=[{"role": "user", "content": "Hello!"}])
print(response.choices[0].message.content)
# Streaming
for chunk in litelm.completion("groq/llama-3.1-70b-versatile", messages=[...], stream=True):
print(chunk.choices[0].delta.content or "", end="")
# Embeddings
response = litelm.embedding("openai/text-embedding-3-small", input=["hello world"])
Every function has an async variant: acompletion, aembedding, aresponses, atext_completion.
The API mirrors litellm — same function names, same arguments, same response types. If you're using litellm today, switching is s/litellm/litelm/ in your imports.
What's in / what's out
| litellm | litelm | |
|---|---|---|
Model routing (provider/model → right endpoint) |
✓ | ✓ |
| Message translation (Anthropic, Bedrock, Cloudflare, Mistral) | ✓ | ✓ |
Streaming + stream_chunk_builder |
✓ | ✓ |
| Tool use (function calling) | ✓ | ✓ |
| Embeddings | ✓ | ✓ |
| Text completions | ✓ | ✓ |
| OpenAI Responses API | ✓ | ✓ |
| Mock responses | ✓ | ✓ |
| Router (load balancing, fallbacks) | ✓ | ✗ |
| Proxy server | ✓ | ✗ |
| Caching / budgeting / cost tracking | ✓ | ✗ |
| Token counting | ✓ | ✗ |
| Image gen, audio, OCR, fine-tuning | ✓ | ✗ |
| Agents, guardrails, scheduler | ✓ | ✗ |
Providers
Routes to 19 providers via "provider/model-name" syntax. Any OpenAI-compatible endpoint works via api_base.
| Provider | Env Var | Handler | Verified |
|---|---|---|---|
| OpenAI | OPENAI_API_KEY |
OpenAI SDK | Yes |
| Anthropic | ANTHROPIC_API_KEY |
Custom | Yes |
| Groq | GROQ_API_KEY |
OpenAI-compat | Yes |
| Mistral | MISTRAL_API_KEY |
Custom | Yes |
| xAI | XAI_API_KEY |
OpenAI-compat | Yes |
| OpenRouter | OPENROUTER_API_KEY |
OpenAI-compat | Yes |
| Azure | AZURE_API_KEY |
OpenAI SDK (Azure) | Yes |
| Bedrock | AWS_ACCESS_KEY_ID |
Custom | No |
| Cloudflare | CLOUDFLARE_API_TOKEN |
Custom | No |
| Together | TOGETHERAI_API_KEY |
OpenAI-compat | No |
| Fireworks | FIREWORKS_API_KEY |
OpenAI-compat | No |
| DeepSeek | DEEPSEEK_API_KEY |
OpenAI-compat | No |
| Perplexity | PERPLEXITYAI_API_KEY |
OpenAI-compat | No |
| DeepInfra | DEEPINFRA_API_TOKEN |
OpenAI-compat | No |
| Gemini | GEMINI_API_KEY |
OpenAI-compat | No |
| Cohere | COHERE_API_KEY |
OpenAI-compat | No |
| Ollama | — | OpenAI-compat | No |
| vLLM | — | OpenAI-compat | No |
| LM Studio | — | OpenAI-compat | No |
API Keys
Set the environment variable for your provider:
export OPENAI_API_KEY=sk-...
export ANTHROPIC_API_KEY=sk-ant-...
Or pass directly:
litelm.completion("openai/gpt-4o", messages=[...], api_key="sk-...")
litelm.completion("openai/gpt-4o", messages=[...], api_base="http://localhost:8000/v1")
Error Handling
All provider errors are mapped to litelm's exception hierarchy:
from litelm import ContextWindowExceededError, RateLimitError, AuthenticationError
try:
response = litelm.completion("openai/gpt-4o", messages=messages)
except ContextWindowExceededError:
# prompt too long — truncate and retry
pass
except RateLimitError:
# back off
pass
except AuthenticationError:
# bad API key
pass
Completion Callbacks
LiteLLM-compatible callbacks receive (kwargs, response, start_time, end_time):
def on_failure(kwargs, response, start_time, end_time):
error = kwargs["exception"]
print(kwargs["model"], error)
litelm.failure_callback.append(on_failure)
success_callback and failure_callback cover non-streaming completion and acompletion calls. Callback errors are logged without replacing the provider result or exception. Callback kwargs can contain messages and request metadata; observers should explicitly redact exported telemetry. Streaming lifecycle callbacks are not yet supported.
The older success_callbacks one-event-dict registry remains available for litelm 0.5.0 compatibility.
Tool Calling
tools = [{"type": "function", "function": {
"name": "get_weather",
"parameters": {"type": "object", "properties": {"city": {"type": "string"}}},
}}]
response = litelm.completion(
"openai/gpt-4o", messages=[{"role": "user", "content": "Weather in Paris?"}],
tools=tools, tool_choice="required",
)
tool_call = response.choices[0].message.tool_calls[0]
print(tool_call.function.name, tool_call.function.arguments)
Custom / Local Providers
Any OpenAI-compatible server works via api_base:
# vLLM
litelm.completion("openai/my-model", messages=[...], api_base="http://localhost:8000/v1")
# Ollama
litelm.completion("ollama/llama3", messages=[...], api_base="http://localhost:11434/v1")
# LM Studio
litelm.completion("openai/local-model", messages=[...], api_base="http://localhost:1234/v1")
Development transparency
litelm is human-directed, AI-assisted software. Much of the code was written with Claude Code using Claude Opus 4.6/4.7. Code written from 2026-05-14 onward is written through Pi using GPT-5.5. Compatibility claims are based on tests and maintainer review, not AI authorship.
Upstream attestation
Maintainer attestation, 2026-09-11: LiteLLM's routing/formatting changes were reviewed from 649eb2d through 9a715df2. The audit triaged 360 core-path commits, inspected upstream tests for potentially relevant behavior, and fixed the resulting compatibility gaps test-first. Local scoped tests: 262 passed, 55 skipped; all 45 available-provider live tests and all 10 DSPy smoke tests also passed with the current dependency lock.
This attests litelm's declared routing/formatting/DSPy surface only, not full litellm compatibility.
Status
Alpha. 265 own tests passing. The current scoped LiteLLM 9a715df2 baseline has 75 passing ported tests and no remaining actionable assertion/runtime failures.
DSPy drop-in verified — all 7 execution paths proven live (Predict, CoT, typed signatures, streaming, embeddings, tool use, multi-output).
Tests
uv run --extra all pytest tests/ -x --ignore=tests/ported --timeout=10 # 265 non-live tests
bash scripts/ported_contract.sh # 49 fast upstream contract tests
uv run --extra all pytest tests/test_live.py -m live --timeout=30 # 45 live provider tests
uv run pytest tests/test_dspy_smoke.py -m live --timeout=60 # 10 DSPy integration tests
Live tests require API keys in .env.test. Skipped by default; run with -m live.
Metadata
Release files for litelm 0.5.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| litelm-0.5.3.tar.gz | 298.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| litelm-0.5.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 334.3 kB
Release files / litelm-0.5.3.tar.gz
| Download URL | litelm-0.5.3.tar.gz |
|---|---|
| Size | 298.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7dcd10063e001fc801cc14276cdc61c43058f77a0288727035c772a7f8498edd
|
|
BLAKE2b-256 checksum How to use checksums |
214b5efd035bc19755ae63168484706dbe618f3596f017eb9e511d9bbb8b657e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 19, 2026.
Transparency logRelease files / litelm-0.5.3-py3-none-any.whl
| Download URL | litelm-0.5.3-py3-none-any.whl |
|---|---|
| Size | 35.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
796a8ea359f4a868ada6fd12aaac304121b6402f87decd08b9cc7a9b05379d1e
|
|
BLAKE2b-256 checksum How to use checksums |
c631c02c06335dd861bd94bff28c433fd4dadc4b85530decee35b8e471a503ae
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 19, 2026.
Transparency log