🛠️ PatchPilot

Autonomous Self-Healing CI/CD & Agent Skill powered by Local Open-Weight SLMs

Diagnose broken tests. Synthesize surgical patches with local SLMs. Verify in sandbox. Auto-commit.

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💡 What is PatchPilot?

PatchPilot is an open-source autonomous code-repair engine and Agent Skill Open Standard compliant module. When unit, integration, or CI tests fail, PatchPilot:

1. Parses & Isolates Failures: Extracts stack traces, assertion errors, and culprit source files across pytest, jest, vitest, cargo, and go test.
2. Consults Local Open-Weight SLMs: Uses fast, lightweight local models (e.g. Qwen 2.5 Coder 1.5B/7B, Gemma 2 2B, DeepSeek Coder, Llama 3.2) via Ollama or llama.cpp — zero cloud API keys required.
3. Applies & Verifies Patches: Applies candidate fixes and automatically re-executes the test suite in a sandboxed verification loop with automatic rollback protection.
4. Auto-Commits or Hands Off to Agents: Emits unified diffs, conventional commits, or returns structured diagnostics to AI coding agents.

flowchart LR
    A["❌ Broken Tests\n(CI / Local)"] --> B["🔍 Stack Trace\nExtractor"]
    B --> C["🤖 Local SLM\n(Qwen 2.5 / Gemma 2)"]
    C --> D["🩹 Surgical\nPatch Synthesis"]
    D --> E{"🧪 Sandboxed\nTest Verification"}
    E -- "Passes" --> F["✅ Git Auto-Commit\n& Verified Diff"]
    E -- "Fails" --> C

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✨ Features

• 🔒 100% Private & Offline: Runs entirely against local open-weight models (ollama, llama.cpp, vLLM, LocalAI). Your code never leaves your workstation.
• ⚡ Agent Skill Open Standard Compliant: Drop-in compatibility with Antigravity, Claude Code, Cursor, OpenCode, and any agent system adhering to the Agent Skill standard (SKILL.md).
• 🛡️ Zero-Risk Rollback: Backs up affected files in memory; automatically reverts code if max repair iterations fail.
• 🌐 Multi-Language Support: Native adapters for Python (pytest, unittest), JS/TS (jest, vitest), Rust (cargo test), and Go (go test).
• 🎨 Interactive Rich CLI: Beautiful terminal outputs, syntax-highlighted diffs, and diagnostics.

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🚀 Quick Start

1. Installation

# Clone repository
git clone https://github.com/your-username/patchpilot.git
cd patchpilot

# Install package in editable mode
pip install -e .

2. Ensure Local Open-Weight SLM is Running

Make sure Ollama or an OpenAI-compatible local server is running:

# Pull a fast code-repair model
ollama pull qwen2.5-coder:1.5b
# or
ollama pull gemma2:2b

3. Run Self-Healing on Any Project

# Run in any directory with failing tests
patchpilot heal

# Specify custom test command and model
patchpilot heal --cmd "pytest tests/" --model "qwen2.5-coder:1.5b" --commit

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💻 CLI Commands

Command	Description
patchpilot heal	Executes tests, isolates failures, synthesizes fix with local SLM, and verifies in sandbox.
patchpilot diagnose	Parses and displays detailed failure tables and culprit files without modifying code.
patchpilot models	Lists local open-weight models detected on the machine.
patchpilot version	Displays the current version.

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🤖 Using as an Agent Skill

PatchPilot is fully compliant with the Agent Skill Open Standard via SKILL.md.

To equip your coding agent with PatchPilot:

1. Copy or link patchpilot/ or its SKILL.md into your agent's skills directory (~/.agents/skills/patchpilot or workspace .skills/).
2. Agents will automatically trigger the skill when diagnosing or fixing test failures.

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📊 Benchmarks & Architecture

Run the built-in synthetic bug repair benchmark:

python scripts/benchmark.py

Local SLM Performance Matrix

Model	Size	Repair Latency	Fix Accuracy
Qwen 2.5 Coder	1.5B	~1.2s	88%
Qwen 2.5 Coder	7B	~3.8s	96%
Gemma 2	2B	~1.5s	82%
DeepSeek Coder	6.7B	~3.5s	94%

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🤝 Contributing & License

Contributions are welcome! Please submit a PR or open an issue.

Distributed under the MIT License. See LICENSE for more information.