DEVELOPER.md

🛠️ Developer Documentation

📦 Project Structure

.
├── app.py                # Main Chainlit application
├── app_simple_rag.py     # Simplified RAG application 
├── pyproject.toml        # Project configuration and dependencies
├── pstuts_rag/           # Core package
│   └── pstuts_rag/       # Source code
│       ├── __init__.py
│       ├── datastore.py  # Vector database management
│       ├── loader.py     # Data loading utilities
│       ├── rag.py        # RAG implementation
│       ├── agents.py     # Team agent implementation
│       └── ...
├── data/                 # Dataset files
└── README.md             # User documentation

🧩 Dependency Structure

Dependencies are organized into logical groups:

• Core: Basic dependencies needed for the RAG system (includes Jupyter support)
• Dev: Development tools (linting, testing, etc.)
• Web: Dependencies for web server functionality
• Extras: Additional optional packages (numpy, ragas, tavily)

You can install different combinations using pip's extras syntax:

pip install -e ".[dev,web]"  # Install core + dev + web dependencies

🔧 Technical Details

The application uses LangChain, LangGraph, and Chainlit to create an agentic RAG system:

Key Components

• DatastoreManager: Manages the Qdrant vector store and document retrieval
• RAGChainFactory: Creates retrieval-augmented generation chains
• PsTutsTeamState: Manages the state of the agent-based system
• Langgraph: Implements the routing logic between different agents

🚀 Running Locally

1. Create a virtual environment (recommended):

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies:

pip install -e ".[dev]"  # Install with development tools

3. Set up API keys:

export OPENAI_API_KEY="your-openai-key"
export TAVILY_API_KEY="your-tavily-key"  # Optional, for web search

4. Run the application:

chainlit run app.py

🧪 Code Quality

To check for dependency issues:

deptry .

For linting:

black .
ruff check .
mypy .

📚 Resources

• Chainlit Documentation
• LangChain Documentation
• LangGraph Documentation