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Jerry — AI Agent Framework
CLI tool that turns any local directory into an AI-powered workspace by indexing its documents into a vector store and exposing a LangGraph-backed, tool-using agent.
PythonLangGraphRAG with vector store (`.md` and `.txt` ingestion)Extensible ToolProvider systemState stored in hidden `.jerry/` folder
⚡ Keeping vector store state fresh when project files change w…⚡ Scoping agent memory to the directory while supporting neste…
Portfolio Highlights
- →Built a Python CLI that converts any project directory into a context-aware AI workspace using LangGraph and document RAG.
- →Designed a modular ToolProvider system enabling extensible tool registration with isolated per-directory state.
Snapshot
- Period: October 2025
- Source: `github.com/josegibson/Jerry`
- Domain: AI agents, RAG, developer tooling
- Status: Public release
Stack
- Python
- LangGraph
- RAG with vector store (`.md` and `.txt` ingestion)
- Extensible ToolProvider system
- State stored in hidden `.jerry/` folder
What I Built
- Directory-scoped agent instantiation: run `jerry` in any folder to spin up a context-aware agent.
- Auto-indexing pipeline that vectorizes readable documents at startup.
- Modular ToolProvider architecture allowing new tools to be registered without touching core agent logic.
- State isolation so each workspace keeps its own `.jerry/` data — no cross-project bleed.
- Full documentation suite: INSTALL, QUICKSTART, USER_GUIDE, CONTRIBUTING.
Development Timeline
- Implemented initial directory-scoped agent with basic RAG indexing.
- GoalAdd extensible ToolProvider architecture
- FixedDesigning a ToolProvider interface that is extensible without requiring boilerplate for simple tools.
- Added public entry
- Another public entry