DigestAI news desk

Cut through the AI noise.

Agents & Tools2 min read

Litelm releases lightweight LiteLLM alternative with 2,900 lines of code

A new open-source library named litelm has emerged as a streamlined alternative to the popular LiteLLM framework. While LiteLLM is a comprehensive suite featuring proxy servers, caching, and cost tracking that exceeds 100,000 lines of code, litelm focuses exclusively on the core functionality: routing LLM calls and translating message formats. The project achieves this with approximately 2,900…

1 source primary source HN 94

Key points

  • litelm reduces LiteLLM's 100k+ LOC to ~2,900 lines by removing proxy, caching, and cost tracking features.
  • The library supports 19 providers and maintains API compatibility with LiteLLM for easy drop-in replacement.
  • Development was AI-assisted using Claude and GPT-5.5, with 262 local tests passing in the current alpha release.

The library supports 19 providers, including OpenAI, Anthropic, and Bedrock, using a syntax that mirrors LiteLLM for easy migration. It handles completions, streaming, embeddings, and tool use, with async variants available for all functions. The project is currently in alpha status, with 262 local tests passing and verified compatibility with DSPy execution paths. Notably, the codebase was developed with significant assistance from AI models, including Claude Opus and GPT-5.5, though the maintainer attests to manual review of critical routing and formatting changes to ensure reliability.

Full story from github.com · via Hacker News primary sourceOpen source ↗

Litelm: LiteLLM Without the Bloat

github.com · 11 September 2026

Loading the full article…

This text was published by github.com. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

Coverage and discussion

1source
Topics · follow one to build your own front page
OpenAIAnthropicBedrockGPT-4oLlama-3.1-70b-versatiletext-embedding-3-smallClaude Opus 4.6GPT-5.5

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

Comments

via GitHub Discussions

More in Agents & Tools

All →

Related stories