Sam Rolfe
628ba96998
- Frontend: Vite + React + TypeScript chat interface - Backend: FastAPI gateway with LangGraph routing - Knowledge Service: ChromaDB RAG with Gitea scraper - LangGraph Service: Multi-agent orchestration - Airflow: Scheduled Gitea ingestion DAG - Documentation: Complete plan and implementation guides Architecture: - Modular Docker Compose per service - External ai-mesh network for communication - Fast rebuilds with /app/packages pattern - Intelligent agent routing (no hardcoded keywords) Services: - Frontend (5173): React chat UI - Chat Gateway (8000): FastAPI entry point - LangGraph (8090): Agent orchestration - Knowledge (8080): ChromaDB RAG - Airflow (8081): Scheduled ingestion - PostgreSQL (5432): Chat history Excludes: node_modules, .venv, chroma_db, logs, .env files Includes: All source code, configs, docs, docker files
108 lines
2.7 KiB
Markdown
108 lines
2.7 KiB
Markdown
# AboutMe AI Chat Demo
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A comprehensive AI agent system with multi-service architecture for personal knowledge management and intelligent query responses.
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## Architecture Overview
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```
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User Query → Chat Gateway → LangGraph Supervisor → [Librarian | Opencode | Brain]
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↓
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Knowledge Service (ChromaDB) ← Airflow ← Gitea API
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```
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## Services
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| Service | Port | Technology | Purpose |
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|---------|------|------------|---------|
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| Frontend | 5173 | Vite + React + TS | Chat UI |
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| Chat Gateway | 8000 | FastAPI | API entry point |
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| LangGraph | 8090 | FastAPI + LangGraph | Agent orchestration |
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| Knowledge | 8080 | FastAPI + ChromaDB | RAG / Vector search |
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| Airflow | 8081 | Apache Airflow | Scheduled ingestion |
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| PostgreSQL | 5432 | Postgres 15 | Chat history |
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## Quick Start
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```bash
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# 1. Ensure Docker network exists
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docker network create ai-mesh
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# 2. Start Knowledge Service
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cd knowledge_service && docker-compose up -d
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# 3. Start LangGraph Service
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cd ../langgraph_service && docker-compose up -d
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# 4. Start Chat Demo
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cd ../aboutme_chat_demo && docker-compose up -d
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# 5. Start Airflow (optional)
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cd ../airflow && docker-compose up -d
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```
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## Environment Variables
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Create `.env` files in each service directory:
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**knowledge_service/.env:**
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```
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OPENROUTER_API_KEY=your_key_here
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GITEA_URL=https://gitea.lab.audasmedia.com.au
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GITEA_TOKEN=your_token
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GITEA_USERNAME=sam
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```
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**langgraph_service/.env:**
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```
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OPENCODE_PASSWORD=sam4jo
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```
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**airflow/.env:**
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```
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AIRFLOW_UID=1000
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GITEA_TOKEN=your_token
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```
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## Project Structure
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```
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aboutme_chat_demo/
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├── frontend/ # React chat interface
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├── backend/ # FastAPI gateway (routes to LangGraph)
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├── plan.md # Full project roadmap
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└── code_1.md # Implementation guide
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knowledge_service/
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├── main.py # FastAPI + ChromaDB
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├── gitea_scraper.py # Gitea API integration
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└── docker-compose.yml
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langgraph_service/
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├── main.py # FastAPI entry point
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├── supervisor_agent.py # LangGraph orchestration
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└── docker-compose.yml
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airflow/
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├── dags/ # Workflow definitions
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│ └── gitea_ingestion_dag.py
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└── docker-compose.yml
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```
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## Technologies
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- **Frontend:** Vite, React 19, TypeScript, Tailwind CSS, TanStack Query
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- **Backend:** FastAPI, Python 3.11, httpx
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- **AI/ML:** LangGraph, LangChain, ChromaDB, OpenRouter API
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- **Orchestration:** Apache Airflow (CeleryExecutor)
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- **Infrastructure:** Docker, Docker Compose
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## Documentation
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- `plan.md` - Complete project roadmap (7 phases)
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- `code_1.md` - Modular implementation guide
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- `code.md` - Legacy implementation reference
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## License
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MIT
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