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+++ b/README.md
@@ -1,119 +1,35 @@
-# FAQ Bot – ChromaDB + MCP-style Tool
+# Повторный экзамен: FAQ-бот — ChromaDB + один MCP-tool
 
-This project implements a simple FAQ bot that answers questions about a machine learning course.  
-The bot uses:
+Главная
+Мои задания
+Повторный экзамен: FAQ-бот — ChromaDB + один MCP-tool
+5Д
+EN
+Повторный экзамен: FAQ-бот — ChromaDB + один MCP-tool
+Зачёт
+Версия 2
+Дедлайн сдачи: 31.08.2026
 
-- **ChromaDB** to store and retrieve FAQ documents.
-- **Ollama** embeddings (`nomic-embed-text`) for vectorization.
-- **LangChain** to build an agent that routes queries to the appropriate tool.
-- **MCP-style HTTP tool** (`fetch_course_meta`) that returns course metadata from a local JSON file.
+В работе
 
-## Project Structure
+Требуется доработка
 
-```
-.
-├── chroma_faq/          # Persisted Chroma vector store
-├── data/
-│   ├── faq1.md
-│   ├── faq2.md
-│   ├── faq3.md
-│   └── course_meta.json
-├── src/
-│   ├── __init__.py
-│   ├── agent.py
-│   ├── cli.py
-│   ├── main.py
-│   └── tools.py
-├── requirements.txt
-└── README.md
-```
+Переделайте решение: используйте QDrant вместо текущего векторного хранилища.
 
-## Setup
+Редактирование ответа
 
-1. **Install Ollama**  
-   Download and install Ollama from https://ollama.ai/.  
-   Pull the required models:
+Заполните ответ и отправьте работу на проверку преподавателю.
 
-   ```bash
-   ollama pull nomic-embed-text
-   ollama pull llama3
-   ```
+Тип ответа
+Текст
+Ссылка
+Файлы
+Ссылка (URL)
+Прикреплённые файлы
+Загрузить файл
+Отправить на проверку
+Отменить
 
-2. **Create a virtual environment** (optional but recommended):
+Задание
 
-   ```bash
-   python -m venv venv
-   source venv/bin/activate   # On Windows: venv\Scripts\activate
-   ```
-
-3. **Install Python dependencies**:
-
-   ```bash
-   pip install -r requirements.txt
-   ```
-
-## Running the Bot
-
-### Preset Questions
-
-Run the script without arguments to execute three preset questions (two for the FAQ tool, one for the metadata tool):
-
-```bash
-python -m src.main
-```
-
-You should see output similar to:
-
-```
-Running preset questions:
-
-Q1: What is the deadline for Assignment 1?
-A1: The deadline for Assignment 1 is August 31, 2026. source: chroma
-
-Q2: How many lectures are there in the course?
-A2: There are 12 lectures in the course. source: chroma
-
-Q3: What is the course schedule for next week?
-A3: The course schedule for next week is:
-- 2026-09-01: Lecture 1 – Introduction to ML (Room 101)
-- 2026-09-08: Lecture 2 – Data Preprocessing (Room 102)
-- 2026-09-15: Lecture 3 – Linear Regression (Room 103)
-source: mcp_meta
-```
-
-### Interactive Mode
-
-Start an interactive session:
-
-```bash
-python -m src.main --interactive
-```
-
-You can type any question, and the bot will answer using the appropriate tool. Type `exit` or `Ctrl+C` to quit.
-
-## How It Works
-
-1. **Data Loading**  
-   `src/tools.py` contains `load_faq_to_chroma()` which reads all `.md` files in `data/`, chunks them, embeds them with `nomic-embed-text`, and persists the vector store in `chroma_faq/`.
-
-2. **Tools**  
-   - `search_course_docs(query, k)` – searches the Chroma vector store for relevant FAQ snippets.  
-   - `fetch_course_meta(query)` – reads `data/course_meta.json` and returns schedule or instructor information based on the query.
-
-3. **Agent**  
-   `src/agent.py` builds a LangChain agent that:
-   - Uses a system prompt to decide which tool to call.  
-   - Adds a `source:` tag to the final answer indicating whether the answer came from the FAQ (`chroma`) or the metadata tool (`mcp_meta`).
-
-4. **CLI**  
-   `src/cli.py` provides a simple command‑line interface to run preset questions or an interactive session.
-
-## Extending the Bot
-
-- **Add more FAQ documents** – Place additional `.md` files in `data/` and re‑run the script to rebuild the vector store.
-- **Add more metadata** – Update `data/course_meta.json` or modify `fetch_course_meta` to call a real HTTP endpoint.
-- **Change the LLM** – Replace `Ollama` with another LLM provider in `src/agent.py`.
-
-## License
-
-This project is provided as-is for educational purposes. Feel free to adapt and extend it for your own use cases.
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+Практичес
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