Update README.md

README.md

@@ -1,45 +1,29 @@
-# Deep Agent
+# Deep Agent from Scratch
 
-This repository contains a minimal implementation of a **Deep Agent** inspired by the *Deep Agents from Scratch* course. The agent can:
+This repository contains a minimal implementation of a deep agent that can:
 
-1. Search the web (DuckDuckGo).
-2. Create, read and combine virtual files.
+1. Search the web using DuckDuckGo.
+2. Create virtual files in memory.
 3. Export the virtual files to the real file system.
-4. Use LangChain + Ollama for LLM inference.
 
-## Setup
+The agent is built using the new LangChain 1.x and LangGraph 1.x APIs.
+
+## Prerequisites
+
+- Python 3.11 or newer
+- Ollama running locally with a model such as `llama3.1`
+- `pip install -r requirements.txt`
+
+## Running the Agent
 
 ```bash
-# Install dependencies
-pip install -r requirements.txt
+python agent.py
 ```
 
-## Usage
+The script will run the agent with a sample prompt, create a virtual file `report.txt`, and export it to the `exported_files` directory.
 
-```bash
-python deep_agent.py "Write a summary of the latest Python release and store it in summary.txt"
-```
+## File Structure
 
-The agent will perform the task, create virtual files, and export them to `output_files/`.
-
-## Architecture
-
-- `DeepAgent` class implements the agent logic.
-- `search` uses DuckDuckGo HTML API.
-- `write_file`, `read_file`, `combine` manage a simple in‑memory virtual filesystem.
-- `export_files` writes the virtual files to disk.
-- The agent loop uses a JSON‑based action protocol.
-
-## Requirements
-
-- Python 3.10+
-- LangChain >= 1.0.0
-- LangGraph >= 1.0.0
-- langchain_ollama
-- langchain_text_splitters
-- langchain_chroma
-- requests
-
----
-
-Feel free to extend the agent with more actions or integrate other LLM providers.
+- `agent.py` – Main implementation.
+- `requirements.txt` – Python dependencies.
+- `README.md` – This file.