PatchPal — An Agentic Coding and Automation Assistant¶
Supporting both local and cloud LLMs, with autopilot mode and extensible tools.
PatchPal is an AI coding agent that helps you build software, debug issues, and automate tasks. It supports agent skills, tool use, and executable Python generation, enabling interactive workflows for tasks such as data analysis, visualization, web scraping, API interactions, and research with synthesized findings.
Most agent frameworks are built in TypeScript. PatchPal is Python-native, designed for developers who want both interactive terminal use (patchpal) and programmatic API access (agent.run("task")) in the same tool—without switching ecosystems.
Key Features
- Terminal Interface for interactive development
- Python SDK for flexibility and extensibility
- Built-In and Custom Tools
- Skills System
- Autopilot Mode using Ralph Wiggum loops
- Project Memory automatically loads project context from
~/.patchpal/repos/<repo-name>/MEMORY.mdat startup.
PatchPal prioritizes customizability: custom tools, custom skills, a flexible Python API, and support for any tool-calling LLM.
Quick Start¶
Model support: Any LiteLLM-supported model is can be used. Platform support: Linux, macOS, and Windows are all supported
Beyond Coding: General Problem-Solving¶
While originally designed for software development, PatchPal is also a general- purpose assistant. With web search, file operations, shell commands, and custom tools/skills, it can help with research, data analysis, document processing, log file analyses, etc.
FAQ¶
There are so many coding agent harnesses. Why build yet another one?
- Most agent harnesses are in TypeScript. We wanted something in Python that we could easily extend for our custom workflows.
- PatchPal includes a unique guardrails system that is better suited to privacy-conscious use cases involving sensitive data.
- We needed an agent harness that seamlessly works with both local and cloud models, including AWS GovCloud Bedrock models.