RAG Agent with ChromaDB and Tavily

This repository contains a simple RAG agent that uses ChromaDB as a local vector store and Tavily for web search. The agent automatically selects the appropriate source (local knowledge base or the web) based on the query.

Structure

• vectorstore.py – utilities for creating and loading the vector store.
• tools.py – LangChain tools for local and web search.
• agent.py – agent definition with routing logic.
• main.py – interactive CLI.
• init_db.py – helper script to load documents from documents/ into the vector store.
• requirements.txt – dependencies.
• documents/ – folder with sample .txt/.md files.

Usage

# Install dependencies
pip install -r requirements.txt

# Load documents into the vector store
python init_db.py

# Run the chat interface
python main.py

Environment

• TAVILY_API_KEY – required for web search.
• OLLAMA_BASE_URL – optional, defaults to http://localhost:11434.