# FAQ Bot with ChromaDB and MCP-style Tool

## Overview

This repository implements a FAQ bot that answers questions about course materials using a local **ChromaDB** vector store and, when needed, a single **MCP-style tool** that fetches course metadata.

## Features

* **ChromaDB** for semantic search over lecture markdown files.
* **MCP-style tool** (`fetch_course_meta`) that simulates an external MCP service.
* **LangGraph**‑based agent that routes queries to the appropriate tool and prefixes the answer with the source.
* CLI with preset questions and an interactive mode.

## Setup

```bash
# Pull embeddings model
ollama pull nomic-embed-text

# Install dependencies
pip install -r requirements.txt

# Run a simple HTTP server to serve meta.json (for the MCP tool)
# In a separate terminal:
#   python -m http.server 8000
```

## Running the Bot

```bash
python main.py
```

The script will load the FAQ data, build the ChromaDB index, and then run the demo questions followed by an interactive prompt.

## Project Structure

```
├── data/          # Markdown files with lecture notes
├── main.py        # Entry point
├── requirements.txt
└── README.md
```

## Notes

* The MCP tool currently points to `http://localhost:8000/meta.json`. Replace with your actual endpoint if needed.
* The agent uses `ChatOpenAI` via OpenRouter; set `OPENAI_API_KEY` in your environment.