devops-agent

# LangGraph Multi-Agent DevOps App This project implements a multi-agent system using LangGraph to create a "DevOps Copilot." The system is composed of a supervisor agent that delegates tasks to specialized agents for planning, diagramming, and Terraform operations. For a detailed walkthrough of the implementation, check out my Substack post: [Building a DevOps Copilot with LangGraph](https://sumantthakur.substack.com/p/from-idea-to-infrastructure-building?r=17szhe). ## Prerequisites Before you begin, ensure you have the following installed: - Python 3.10+ - Install GraphViz https://www.graphviz.org/ ## 🚀 Getting Started Follow these steps to set up and run the project locally. ### 1. Clone the Repository ```bash git clone git@github.com:blissfulldev/devops-agent.git cd DevOps-Platform ``` ### 2. Set Up the Python Environment ```bash # Create and activate a virtual environment python3 -m venv venv source venv/bin/activate # Navigate to the application directory and install dependencies cd devops-app pip install poetry poetry install ``` ### 3. Configure Environment Variables Create a `.env` file from the example template and add your API keys. ```bash # Make sure you are in the `devops-app` directory cp env.example .env ``` Now, open the `.env` file and add the necessary secret keys (e.g., `GOOGLE_API_KEY`). ## ▶️ Running the Application The application consists of several services that must be run simultaneously. It is highly recommended to **open a new terminal for each step and activate venv in every terminal before running any command**. ### 1. Start the MCP Servers These servers provide the specialized tools for each agent. * **Core MCP Server:** ```bash cd devops-app/mcp/core-mcp-server/ poetry install ``` ```bash python -m awslabs.core-mcp-server.server --transport streamable-http --host 0.0.0.0 --port 8000 ``` * **Diagraming MCP Server:** ```bash cd devops-app/mcp/aws-diagram-mcp-server/ poetry install ``` ```bash python -m awslabs.aws-diagram-mcp-server.server --transport streamable-http --host 0.0.0.0 --port 8001 ``` * **Terraform MCP Server:** ```bash cd devops-app/mcp/terraform-mcp-server/ poetry install ``` ```bash python -m awslabs.terraform-mcp-server.server --transport streamable-http --host 0.0.0.0 --port 8002 ``` ### 2. Start the FastAPI Backend This server orchestrates the agents and provides the streaming API. ```bash # From the `devops-app` directory poetry run uvicorn server:app --host 0.0.0.0 --port 8080 --reload ``` ### 3. Start the Streamlit Frontend This is the user interface for interacting with the copilot. ```bash # From the `devops-app` directory streamlit run app.py ``` You can now access the chat interface at `http://localhost:8501`.