povtornyy-ekzamen-graf-s-refleksiey-i-do/README.md

LangGraph Agent with OpenAI Integration

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.

Requirements

• Python 3.10+
• langchain-openai (automatically installed via requirements.txt)
• langgraph
• langchain
• openai

Install the dependencies:

pip install -r requirements.txt

Configuration

Set your OpenAI API key as an environment variable:

export OPENAI_API_KEY="your-openai-api-key"

Alternatively, you can create a .env file in the project root with the following content:

OPENAI_API_KEY=your-openai-api-key

Running the Agent

You can run the agent from the command line:

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!