PyHealer: Agentic Self-Repair for Python Program Execution

PyHealer is an LLM-backed, agentic execution error repair pipeline for Python projects. It automatically analyzes execution failures, infers dependencies and Python versions, builds isolated Docker environments, and applies iterative fixes using specialized LLM agents.

The system is intended for research, experimentation, and automated program repair. Key features include:

LLM-driven API extraction

Automatic dependency and Python version inference

Docker-based isolated execution

Agentic feedback loop with specialized agents (Dependency, Code, Python, System)

Meta-Agent for failure classification

Iterative repair attempts

Structured JSON reports and metrics

The pipeline relies on pre-built knowledge artifacts for dependency resolution, Python feature mapping, and system error correction. Users can run PyHealer on target Python projects or benchmark datasets (e.g., Gistable Hg2.9k) to automatically detect and repair execution errors.

Prerequisites: Python 3.8+, Docker, and the Ollama local LLM runtime with the codellama:70b model.

License: (Specify your license here, e.g., MIT, Apache 2.0)

Repository / Files Structure:

PyHealer.py – main script

Example_Project/ – sample target project

Knowledge Data/ – knowledge artifacts for repair agents