feat: solution for 'Практическое задание: AI-агент на LangChain'

README.md

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+# Shopping List AI Agent
+
+This project demonstrates a simple hierarchical AI agent built with LangChain that helps plan a shopping list, fetches prices for each item using a sub‑agent, and calculates the total cost.
+
+## Prerequisites
+
+- Python 3.10+
+- A local LLM server (e.g., LM Studio) running at `http://localhost:1234/v1`.  
+  The server must expose an OpenAI‑compatible API.
+
+## Installation
+
+bash
+# Clone the repository
+git clone https://github.com/your-username/shopping-list-agent.git
+cd shopping-list-agent
+
+# Create a virtual environment (optional but recommended)
+python -m venv venv
+source venv/bin/activate   # On Windows use `venv\\Scripts\\activate`
+
+# Install dependencies
+pip install -r requirements.txt
+
+
+## Running the Agent
+
+bash
+python src/main.py
+
+
+The script will ask the agent to plan a shopping list for the following request:
+
+
+Помоги составить список покупок: молоко, хлеб, яблоки. Я нахожусь в Казани.
+
+
+The agent will:
+
+1. Parse the list of products and the city.
+2. For each product, invoke the `get_price` tool, which internally creates a sub‑agent that generates a realistic price table.
+3. Sum the prices and output the final total.
+
+All intermediate tool calls and the final answer are printed to the console.
+
+## Customization
+
+- **Model**: Change the `model` parameter in `src/main.py` to match the model name exposed by your LM Studio instance.
+- **Temperature**: Adjust the `temperature` argument to control the randomness of the responses.
+
+## License
+
+MIT License