povtornyy-ekzamen-faq-bot-chromadb-odin-/README.md

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

# 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

# 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

# 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:

{
  "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:

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:

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!