Zero-dependency LiteLLM-compatible facade for OpenAI, Anthropic, and OpenRouter
Project description
slimllm
Zero-dependency Python facade for OpenAI, Anthropic, and OpenRouter — designed for AWS Lambda.
Why
- No external dependencies — uses only Python stdlib (
http.client,ssl,json,asyncio) - LiteLLM-compatible API — same
completion()call signature, swap without rewriting callers - Lambda-friendly — tiny cold start, no bloat
- Supports streaming, tool use, and JSON mode
Supported providers
| Model prefix | Provider | Env var |
|---|---|---|
gpt-*, o1-*, o3-* |
OpenAI | OPENAI_API_KEY |
claude-*, anthropic/… |
Anthropic | ANTHROPIC_API_KEY |
openrouter/… |
OpenRouter | OPENROUTER_API_KEY |
Install
pip install slimllm
Usage
import slimllm
# Non-streaming
resp = slimllm.completion(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello!"}],
)
print(resp.content)
# Streaming
stream = slimllm.completion("claude-3-5-sonnet-20241022", messages, stream=True)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="", flush=True)
final = stream.get_final_response()
# Async
resp = await slimllm.acompletion("gpt-4o", messages)
# Async streaming
async for chunk in slimllm.astream("claude-3-5-sonnet-20241022", messages):
print(chunk.choices[0].delta.content or "", end="")
# Tool use (OpenAI format — auto-converted for Anthropic)
tools = [{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get current weather",
"parameters": {
"type": "object",
"properties": {"city": {"type": "string"}},
"required": ["city"],
},
},
}]
resp = slimllm.completion("claude-3-5-sonnet-20241022", messages, tools=tools)
# OpenRouter
resp = slimllm.completion("openrouter/meta-llama/llama-3.3-70b-instruct", messages)
API key resolution
Keys are looked up in this order:
- Explicit
api_key=kwarg - Environment variable (
OPENAI_API_KEY,ANTHROPIC_API_KEY,OPENROUTER_API_KEY)
Response shape
All providers return the same OpenAI-shaped types:
resp.content # str | None
resp.tool_calls # list[ToolCall] | None
resp.choices[0].finish_reason # "stop" | "length" | "tool_calls"
resp.usage.prompt_tokens
resp.usage.completion_tokens
License
MIT
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
slimllm-1.3.1.tar.gz
(25.3 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
slimllm-1.3.1-py3-none-any.whl
(24.4 kB
view details)
File details
Details for the file slimllm-1.3.1.tar.gz.
File metadata
- Download URL: slimllm-1.3.1.tar.gz
- Upload date:
- Size: 25.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a55205b4e3c7c424b0a9c1156d8ea197ea60d3a997aedd72c2f12a10db9b72d3
|
|
| MD5 |
8711d3d86da4876843022d17fbd145fd
|
|
| BLAKE2b-256 |
12a4cfb16fa7fb8b3b743fcd18233c433d024b8e462663f8d792e65a74e70b16
|
File details
Details for the file slimllm-1.3.1-py3-none-any.whl.
File metadata
- Download URL: slimllm-1.3.1-py3-none-any.whl
- Upload date:
- Size: 24.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
dc4efbb1433558d29d371f66edb54f83a4ad06c8864ba53868ab1a7eec3008a2
|
|
| MD5 |
e0661ce75d2cc7e5340083eddf5ec764
|
|
| BLAKE2b-256 |
b587fbc1267097068bb823bd2a0fc8887162b26e8d55c4fe59dfcf04c7e9cbf3
|