feat: solution for 'Повторный экзамен: Граф с рефлексией и доработкой'

README.md

@@ -1,19 +1,60 @@
-# Project Title
+# LangGraph Agent with OpenAI Integration
 
-This project demonstrates a simple usage of the `langgraph` library.
+This project demonstrates a simple LangGraph agent that integrates with the OpenAI LLM via the `langchain-openai` package. The agent processes a single prompt and returns the model's response.
 
-## Setup
+## Requirements
+
+- Python 3.10+
+- `langchain-openai` (automatically installed via `requirements.txt`)
+- `langgraph`
+- `langchain`
+- `openai`
+
+Install the dependencies:
 
 ```bash
 pip install -r requirements.txt
 ```
 
-## Run
+## Configuration
+
+Set your OpenAI API key as an environment variable:
 
 ```bash
-python main.py
+export OPENAI_API_KEY="your-openai-api-key"
 ```
 
-## Notes
+Alternatively, you can create a `.env` file in the project root with the following content:
 
-The `langgraph` package is required for this project. It is specified in `requirements.txt` with a minimum version of 0.0.1.
+```
+OPENAI_API_KEY=your-openai-api-key
+```
+
+## Running the Agent
+
+You can run the agent from the command line:
+
+```bash
+python -m src.agent "Hello, how are you?"
+```
+
+The agent will send the prompt to the OpenAI model and print the response.
+
+## Project Structure
+
+```
+├── requirements.txt
+├── src
+│   └── agent.py
+└── README.md
+```
+
+- `requirements.txt` – lists all Python package dependencies.
+- `src/agent.py` – contains the LangGraph agent implementation and a simple CLI.
+- `README.md` – this documentation file.
+
+## Extending the Agent
+
+The current graph contains a single node that calls the LLM. You can extend it by adding more nodes (e.g., for tool usage, memory, or custom logic) and connecting them in the graph.
+
+Happy coding!