Autoresearch for Agents (hwchase17): Autonomous Optimization via Evals

Optimize AI agents autonomously using an experiment loop driven by LangSmith evals and automated code iteration.

Optimize AI agents autonomously using an experiment loop driven by LangSmith evals and automated code iteration.

Learn how SheetAgent uses LLMs to transform Excel workflows into reusable, zero-cost Power Query and pandas recipes. Train once, run forever.

Upgrade OpenAI Whisper with WhisperX for word-level timestamps, speaker diarization, and up to 70x faster transcription speeds.

Generate holistic, privacy-first documentation for large codebases locally with CodeWiki's Python CLI. Supports 9 languages and Mermaid diagrams.

Don't risk your local machine with untrusted LLM code. Use E2B cloud sandboxes to provide secure, isolated execution environments for your AI agents.

Tired of brittle prompts? Learn how Stanford's DSPy framework allows you to program, optimize, and compile language model pipelines using Python.

Discover Hugging Face's smolagents. A lightweight library using Python-based code agents for more expressive and token-efficient AI workflows.