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

README.md

@@ -1,42 +1,85 @@
 # FAQ Bot – ChromaDB + MCP-tool
 
-This project implements a simple FAQ bot that uses **ChromaDB** as the sole vector store and a single **Minimal Context‑Aware Prompt (MCP) tool** for prompt generation.
+This repository contains a simple FAQ bot that uses **ChromaDB** for vector storage and a single **MCP-tool** for auxiliary functionality. The bot answers user questions by retrieving relevant FAQ documents and generating responses with OpenAI’s LLM.
 
-## Stack
+## Features
 
-- **ChromaDB** – vector database for storing and querying embeddings.
-- **MCP-tool** – a lightweight function that creates a prompt from a user question.
-- **Node.js** – runtime environment.
-- **readline-sync** – simple CLI input.
+- **Vector search** with ChromaDB (persisted locally).
+- **OpenAI embeddings** (`text-embedding-ada-002`) for document indexing.
+- **OpenAI function calling** to invoke a single MCP-tool (`get_current_utc_time`).
+- Interactive command‑line interface.
 
-## How it works
+## Setup
 
-1. **Vector Store**  
-   - `src/vectorStore.js` wraps ChromaDB.  
-   - Documents are embedded using a deterministic 768‑dimensional vector derived from word hashes.  
-   - The collection is created (or fetched) on startup.
+1. **Clone the repository**
 
-2. **MCP-tool**  
-   - `src/bot.js` contains `generatePrompt` which formats the user question into a prompt.  
-   - The prompt is embedded and queried against the vector store.
+   ```bash
+   git clone https://git.brojs.ru/kuzakhmetovartur/povtornyy-ekzamen-faq-bot-chromadb-odin.git
+   cd povtornyy-ekzamen-faq-bot-chromadb-odin
+   ```
 
-3. **Bot Loop**  
-   - `src/index.js` loads a small FAQ dataset, populates the collection, and starts a REPL loop.  
-   - User input is processed, the best matching FAQ answer is returned.
+2. **Create a virtual environment**
 
-## Running the bot
+   ```bash
+   python -m venv .venv
+   source .venv/bin/activate   # On Windows: .venv\Scripts\activate
+   ```
+
+3. **Install dependencies**
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+4. **Set environment variables**
+
+   Create a `.env` file in the project root:
+
+   ```dotenv
+   OPENAI_API_KEY=your_openai_api_key
+   FAQ_FILE=data/faq.jsonl   # optional, defaults to data/faq.jsonl
+   ```
+
+5. **Prepare FAQ data**
+
+   Place your FAQ documents in `data/faq.jsonl`. Each line should be a JSON object:
+
+   ```json
+   {"id": "1", "text": "What is ChromaDB?", "metadata": {"category": "database"}}
+   {"id": "2", "text": "How to use the MCP-tool?", "metadata": {"category": "tool"}}
+   ```
+
+   If the file is missing, the bot will start without pre‑loaded documents.
+
+## Running the Bot
 
 ```bash
-npm install
-npm start
+python src/main.py
 ```
 
-Type a question and press Enter. Type `exit` to quit.
+You will see:
 
-## Notes
+```
+FAQ Bot (ChromaDB + MCP-tool). Type 'exit' to quit.
+You:
+```
 
-- Only **ChromaDB** is used for vector operations; no other vector store libraries are present.
-- Only **one MCP-tool** (`generatePrompt`) is integrated.
-- The code is fully self‑contained and can be extended with real embeddings or a larger dataset.
+Type a question, e.g.:
 
----
+```
+You: What is the current time?
+```
+
+The bot may invoke the MCP-tool and return the current UTC time.
+
+## Testing
+
+The repository includes no automated tests, but you can manually verify:
+
+- The bot can answer FAQ questions.
+- The MCP-tool is invoked when the model requests it.
+- ChromaDB persists data between runs (check the `chromadb/` directory).
+
+## License
+
+MIT License