microsoft/Trace

End-to-end Generative Optimization for AI Agents

48
/ 100
Emerging

This project helps AI developers and researchers train complex AI systems, especially those built with large language models (LLMs), by optimizing their behavior based on various types of feedback like numerical scores or natural language text. It takes in Python code defining an AI system's actions and feedback signals, then outputs an optimized version of the system's trainable components. This is for AI practitioners who build and refine AI agents.

711 stars.

Use this if you are developing AI agents and need a flexible way to optimize their performance using diverse feedback, beyond just numerical gradients.

Not ideal if you are looking for a pre-built, ready-to-deploy AI solution rather than a development tool for creating and optimizing AI systems.

AI-agent-development LLM-fine-tuning AI-system-optimization Generative-AI-engineering AI-research
No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

711

Forks

55

Language

Python

License

MIT

Last pushed

Dec 10, 2025

Commits (30d)

0

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