Add README

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# task-6a219d6afd30e81cf3146d6b
# FAQ Bot with ChromaDB and MCP-style Tool
Solution for FAQ bot with ChromaDB and MCP 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.