feat: solution for 'Повторный экзамен: FAQ-бот — ChromaDB + один MCP-tool'

README.md

@@ -1,45 +1,71 @@
-# FAQ Bot with ChromaDB
+# FAQ Bot – ChromaDB + MCP-tool
 
-This project implements a simple FAQ bot that uses **ChromaDB** as the vector store and **MCP-tool** for generating embeddings. The bot indexes a set of FAQ entries and can answer user questions by retrieving the most relevant entries from the vector store.
+This repository contains a lightweight FAQ bot that uses **ChromaDB** as the vector store and a single **MCP-tool** for generating embeddings.  
+The bot loads FAQ documents, stores them in ChromaDB, and answers user questions by retrieving the most relevant documents.
 
-## Architecture
+## Features
 
-- **ChromaDB** – the sole vector storage stack used for persisting embeddings and performing similarity queries.
-- **MCP-tool** – the only MCP-tool used for generating embeddings from text. No other vector store libraries or MCP-tools are included.
+- **Single vector store stack** – ChromaDB
+- **One MCP-tool** for embeddings (OpenAI or deterministic fallback)
+- Interactive command‑line interface
+- Easy to add new FAQ documents
 
-## Setup
+## Requirements
+
+- Python 3.10+
+- An OpenAI API key (optional – a deterministic dummy embedding is used if not provided)
+
+## Installation
 
 ```bash
-# Install dependencies
-npm install
-
-# Run the bot
-npm start
+git clone https://git.brojs.ru/kuzakhmetovartur/povtornyy-ekzamen-faq-bot-chromadb-odin.git
+cd povtornyy-ekzamen-faq-bot-chromadb-odin
+python -m venv .venv
+source .venv/bin/activate   # Windows: .venv\Scripts\activate
+pip install -r requirements.txt
 ```
 
-## How It Works
+## Configuration
 
-1. **VectorStore**  
-   - Connects to a local ChromaDB instance.  
-   - Adds documents with embeddings generated by MCP-tool.  
-   - Queries the collection for the top‑k most similar documents.  
-
-2. **Bot**  
-   - Initializes the vector store.  
-   - Indexes a predefined list of FAQs.  
-   - Answers user questions by querying the vector store and returning the top results.
-
-## Example
-
-Running the bot will output:
+Create a `.env` file in the project root with your OpenAI key:
 
 ```
-Answer:
- What is ChromaDB?
-ChromaDB is a vector database designed for storing and querying embeddings efficiently.
----
-How do I use MCP-tool?
-MCP-tool is a utility that generates embeddings from text using a chosen model.
+OPENAI_API_KEY=sk-...
 ```
 
-Feel free to extend the FAQ list or integrate the bot into a larger application.
+If the key is missing, the bot will use a deterministic dummy embedding.
+
+## Usage
+
+Place your FAQ documents as plain text files in the `data/` directory (one file per FAQ).
+
+```bash
+python src/faq_bot.py
+```
+
+You will see a prompt:
+
+```
+FAQ Bot is ready. Type your question (or 'exit' to quit).
+Q:
+```
+
+Type a question and press Enter. The bot will display the top 3 most relevant answers.
+
+## Project Structure
+
+```
+src/
+├── faq_bot.py      # Main entry point
+├── vector_store.py # Wrapper around ChromaDB
+└── mcp_tool.py     # Embedding generation
+```
+
+## Extending
+
+- **Adding new documents** – drop new `.txt` files into `data/` and restart the bot.
+- **Changing the embedding model** – modify `mcp_tool.get_embedding` to use a different provider.
+
+## License
+
+MIT License