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

README.md

@@ -1,92 +1,87 @@
 # FAQ Bot – ChromaDB + Ollama
 
-This project implements a simple FAQ bot that uses **ChromaDB** as the vector store and **Ollama** for embeddings and language generation.  
-The bot is built with **LangChain** and relies on a single **MCPTool** to retrieve relevant documents and generate answers.
+This repository contains a simple FAQ chatbot that uses:
+
+- **Ollama** for embeddings (`nomic-embed-text`) and text generation.
+- **ChromaDB** as the vector store.
+- **LangChain** to orchestrate the retrieval and generation pipeline.
 
 ## Features
 
-- **Embeddings**: Uses the `nomic-embed-text` model from Ollama.
-- **Vector Store**: Stores embeddings in a persistent ChromaDB collection.
-- **LLM**: Generates answers with the `llama3` model from Ollama.
-- **MCPTool**: A single tool that handles retrieval and generation in one step.
-- **CLI**: Interactive command‑line interface for quick testing.
+- Loads a small set of FAQ questions and answers.
+- Generates embeddings with the `nomic-embed-text` model.
+- Stores embeddings in a persistent ChromaDB collection.
+- Retrieves the most relevant answer to a user query.
+- Generates a natural language response using an Ollama LLM.
 
-## Setup
+## Requirements
+
+- Python 3.10+
+- Ollama server running locally (default port 11434).  
+  Install from https://ollama.ai/ and pull the required models:
+  ```bash
+  ollama pull nomic-embed-text
+  ollama pull llama3   # or any other generation model you prefer
+  ```
+
+## 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
+git clone https://github.com/your-username/faq-bot.git
+cd faq-bot
 
 # Create a virtual environment (optional but recommended)
 python -m venv .venv
-source .venv/bin/activate  # On Windows: .venv\\Scripts\\activate
+source .venv/bin/activate   # On Windows: .venv\Scripts\activate
 
 # Install dependencies
 pip install -r requirements.txt
 ```
 
-### Data
-
-Place your FAQ documents as plain text files (`*.txt`) in the `data/` directory.  
-Each file will be loaded, embedded, and stored in ChromaDB.
-
-## Running the Bot
+## Usage
 
 ```bash
-python -m src.main
+python src/main.py
 ```
 
 You will see a prompt:
 
 ```
-FAQ Bot powered by ChromaDB and Ollama.
-Type 'exit' to quit.
-
-Your question:
+FAQ Bot is ready. Type your question (or 'exit' to quit).
 ```
 
-Type a question and press Enter. The bot will return an answer.
-
-## Testing
-
-Run the unit tests to verify that the bot uses the correct components:
-
-```bash
-python -m unittest discover -s tests
-```
-
-All tests should pass, confirming that:
-
-- The embeddings are from `OllamaEmbeddings`.
-- The vector store is a `Chroma` instance.
-- No OpenAI modules are imported.
-- Answers are returned as strings.
+Type any of the predefined FAQ questions or any other question, and the bot will respond with the most relevant answer.
 
 ## Project Structure
 
 ```
-├── data/                # FAQ documents (plain text)
-├── chroma_db/           # Persisted ChromaDB collection
+faq-bot/
 ├── src/
-│   └── main.py          # Bot implementation
-├── tests/
-│   └── test_main.py     # Unit tests
-├── requirements.txt
-└── README.md
+│   └── main.py          # Main application script
+├── requirements.txt     # Python dependencies
+└── README.md            # This file
 ```
 
-## Notes
+## Customizing the FAQ
 
-- The bot requires an Ollama server running locally.  
-  Ensure that the `nomic-embed-text` and `llama3` models are available:
+The FAQ data is currently hard‑coded in `src/main.py`. To add more questions:
 
-  ```bash
-  ollama pull nomic-embed-text
-  ollama pull llama3
-  ```
+1. Open `src/main.py`.
+2. Edit the `faq_pairs` list inside the `load_faq_data()` function.
+3. Restart the bot.
 
-- The vector store is persisted in the `chroma_db/` directory.  
-  If you add new documents, delete this folder and rerun the bot to rebuild the index.
+## Persistence
 
-Enjoy building your FAQ bot!
+The vector store is persisted in the `chroma_db/` directory. The next time you run the bot, it will reuse the existing embeddings instead of recomputing them.
+
+## Troubleshooting
+
+- **Ollama not found**: Ensure the Ollama server is running and accessible at `http://localhost:11434`.  
+- **Embedding errors**: Verify that the `nomic-embed-text` model is pulled (`ollama list`).  
+- **Vector store errors**: Delete the `chroma_db/` directory if you suspect corruption.
+
+## License
+
+MIT License
+---