Graph with Reflection on Code

A lightweight Python project that demonstrates how to build a LangGraph workflow powered by LangChain and the OpenAI API.
The graph processes a piece of code, generates a reflection on it, and returns a concise summary.

Repository: https://git.brojs.ru/kuzakhmetovartur/povtornyy-ekzamen-2-graf-s-refleksiey-na

📌 Overview

LangGraph – orchestrates the flow of data between nodes.
LangChain – provides the language model wrappers and utilities.
OpenAI – the LLM that performs code analysis and reflection.

The workflow consists of three main nodes:

Input Node – receives raw code.
Analysis Node – calls the OpenAI model to analyze the code.
Reflection Node – generates a reflection and summary.

The graph is defined in graph.py and can be executed via the CLI or imported as a library.

🚀 Features

Code Analysis – extracts key functions, classes, and comments.
Reflection Generation – produces a human‑readable reflection on the code quality, style, and potential improvements.
Modular Design – each node can be replaced or extended independently.
OpenAI Integration – uses the gpt-4o-mini model by default (configurable).

🛠️ Installation

# Clone the repository
git clone https://git.brojs.ru/kuzakhmetovartur/povtornyy-ekzamen-2-graf-s-refleksiey-na.git
cd povtornyy-ekzamen-2-graf-s-refleksiey-na

# Create a virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate   # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Requirements

Python 3.10+

langgraph, langchain, openai (listed in requirements.txt)

An OpenAI API key set as the environment variable OPENAI_API_KEY.

📦 Usage

Command‑Line

python main.py --file path/to/your_code.py

The script will:

Load the file content.
Run it through the LangGraph workflow.
Print the reflection and summary to the console.

Programmatic

from graph import CodeReflectionGraph

graph = CodeReflectionGraph()
result = graph.run(code="def hello():\n    print('Hello, world!')")
print(result["reflection"])

📁 Project Structure

povtornyy-ekzamen-2-graf-s-refleksiey-na/
├── graph.py          # LangGraph workflow definition
├── main.py           # CLI entry point
├── requirements.txt  # Python dependencies
├── README.md         # This file
└── tests/
    └── test_graph.py # Unit tests

🤝 Contributing

Feel free to open issues or submit pull requests.
Please follow the existing coding style and add tests for new features.

📄 License

MIT License – see the LICENSE file for details.

📞 Contact

Author: Artur Kuzakhmetov
Email: artur.kuzakhmetov@example.com

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