This project is a powerful demonstration of a modern, tool-based AI agent built with CrewAI and LangChain. The agent acts as an autonomous DevOps assistant, capable of analyzing a public GitHub repository's infrastructure configuration, identifying best-practice violations, and automatically creating detailed issues with AI-generated suggestions for fixes.
This project showcases a practical application of Large Language Models (LLMs) to solve a real-world software engineering problem, bridging the gap between AI and DevOps.
The application features a simple Streamlit UI where a user can input a GitHub repository URL. The agent then begins its analysis, and its final report and actions (the created GitHub issues) can be seen in the target repository.
- Python 3.10+
- A Groq API Key.
- A GitHub Personal Access Token (PAT) with
reposcope.
- Clone this repository to your local machine.
- Create a file named
.envin the root of the project. - Add your secret keys to the
.envfile like this:GROQ_API_KEY="gsk_..." GITHUB_PAT="ghp_..."
From the project's root directory, install all the required Python libraries.
pip install -r requirements.txt
Step 3: Launch the Application Run the Streamlit app from your terminal.
streamlit run app.py
A new browser tab will open with the AutoInfraOp dashboard, ready for you to use!