add README.md

README.md

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-# task-6997111cd6d3a5544a3deffd
+# Simple Hierarchical AI Shopping‑List Agent
 
+## What it does
+This repository contains a minimal example of a **hierarchical LangChain agent** that helps you plan a shopping list. The main agent:
+
+1. Accepts a natural‑language request with a list of products and a city.
+2. Calls an internal tool `get_price(product, city)` which itself creates a tiny sub‑agent to generate realistic price tables for the requested product in the specified city.
+3. Aggregates the prices and prints a final summary.
+
+The example demonstrates:
+- Connecting to a local LLM via LM Studio (OpenAI‑compatible API).
+- Using `@tool` to expose a function that internally runs another agent.
+- Running the main agent with `create_agent` and printing all intermediate tool calls.
+
+## File structure
+| File | Purpose |
+|------|---------|
+| `requirements.txt` | Pinning LangChain, langchain‑openai and dotenv dependencies |
+| `main.py` | Full implementation of the hierarchical agent and demo usage |
+| `README.md` | This documentation |
+
+## Installation
+```bash
+python -m venv .venv
+source .venv/bin/activate   # Windows: .venv\Scripts\activate
+pip install -r requirements.txt
+```
+Make sure LM Studio is running on `http://localhost:1234/v1` (or set `LM_BASE_URL` and `LM_MODEL`).
+
+## Running the demo
+```bash
+python main.py
+```
+The script will:
+- Run the main agent with a hard‑coded prompt.
+- Print each tool call (`get_price`) and its output.
+- Show aggregated price tables and total cost.
+
+Feel free to modify `user_prompt` in `main.py` or pass input from stdin for interactive use.