# FAQ Bot – ChromaDB + Ollama

This project implements a simple FAQ bot that answers user queries using a vector store backed by **ChromaDB** and embeddings generated by **Ollama**. The bot is orchestrated with **LangChain** and includes a small tool that returns the current system time.

## Features

- **Vector Store**: ChromaDB for persistent storage of FAQ embeddings.
- **Embeddings**: Generated with Ollama (e.g., `llama3`).
- **LLM**: Ollama LLM for generating responses.
- **RetrievalQA**: LangChain chain that retrieves relevant FAQ answers.
- **MCP‑Tool**: A single tool that returns the current time when the user asks about time or date.
- **CLI**: Simple command‑line interface to ask questions or ingest data.
- **Web API**: FastAPI endpoint (`POST /ask`) for programmatic access.

## Prerequisites

- Python 3.10+
- Docker (optional, for running Ollama locally)
- Ollama server running locally (default port 11434)

## Installation

```bash
# Clone the repository
git clone https://git.brojs.ru/kuzakhmetovartur/povtornyy-ekzamen-faq-bot-chromadb-odin.git
cd povtornyy-ekzamen-faq-bot-chromadb-odin

# Create a virtual environment
python -m venv .venv
source .venv/bin/activate   # On Windows use `.venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt
```

## Environment Variables

Create a `.env` file in the project root (a template is provided):

```
OLLAMA_MODEL=llama3
CHROMA_DB_PATH=./chromadb
```

- `OLLAMA_MODEL`: Name of the Ollama model to use (e.g., `llama3`).
- `CHROMA_DB_PATH`: Directory where ChromaDB will store its data.

## FAQ Data

Place your FAQ data in `data/faq.csv`. The file must contain two columns:

| question | answer |
|----------|--------|

A sample file is included in the repository.

## Usage

### CLI

```bash
# Ingest FAQ data (if not already ingested)
python -m src.main ask "What is the return policy?" --init

# Ask a question
python -m src.main ask "How do I track my order?"
```

The `--init` flag forces re‑ingestion of the FAQ data. If the vector store is empty, it will be ingested automatically.

### Web API

```bash
# Start the server
python -m src.main serve

# Send a request
curl -X POST http://localhost:8000/ask \
     -H "Content-Type: application/json" \
     -d '{"question":"What payment methods are accepted?"}'
```

The response will be a JSON object:

```json
{
  "answer": "We accept credit cards, debit cards, and PayPal."
}
```

### Adding New FAQ Entries

1. Append new rows to `data/faq.csv`.
2. Re‑index the vector store:

```bash
python -m src.main ask "dummy" --init
```

The `--init` flag will ingest all entries, overwriting the existing collection.

## MCP‑Tool

The bot includes a simple tool that returns the current system time. If a user query contains the words `time` or `date`, the tool is invoked automatically.

Example:

```bash
python -m src.main ask "What time is it?"
```

Output:

```
Answer: 2026-08-01 14:32:07
```

## Development

- **Testing**: Run the CLI or API locally to verify functionality.
- **Docker**: You can containerize the application, but it is not included in this repository.

## Known Limitations

- Requires a local Ollama server; no external API calls are made.
- ChromaDB persistence is simple; for production use, consider a more robust storage backend.
- The MCP‑tool is minimal; replace or extend it as needed.

## License

MIT License
--- 
Happy coding!