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CodeX is an AI-powered coding assistant built with LangGraph. It works like a multi-agent development team that can take a natural language request and transform it into a complete, working project — file by file — using real developer workflows.

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🛠️ CodeX

CodeX is an AI-powered coding assistant built with LangGraph.
It works like a multi-agent development team that can take a natural language request and transform it into a complete, working project — file by file — using real developer workflows.


🏗️ Architecture

  • Planner Agent – Analyzes your request and generates a detailed project plan.
  • Architect Agent – Breaks down the plan into specific engineering tasks with explicit context for each file.
  • Coder Agent – Implements each task, writes directly into files, and uses available tools like a real developer.
Coder Agent Architecture

🚀 Getting Started

Prerequisites

  • Ensure that you have created a groq account and have your API key ready. Create an API key here.

⚙️ Instsllstion and Startup

  • Create a virtual environment using: python venv and activate it using source .venv/bin/activate
  • Install the dependencies using: pip install -r requirements.txt
  • Create a .env file and add the variables and their respective values mentioned in the .sample_env file

Now that we are done with all the set-up & installation steps we can start the application using the following command:

  python main.py

🧪 Example Prompts

  • Create a to-do list application using html, css, and javascript.
  • Create a simple calculator web application.
  • Create a simple blog API in FastAPI with a SQLite database.

Important Notice:
This project is licensed under the MIT License.
According to the license terms, any redistribution (including compiled or modified versions), you must retain the original copyright notice and the full license text. Copyright © 2025 Rohith Gowda R. All rights reserved.

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CodeX is an AI-powered coding assistant built with LangGraph. It works like a multi-agent development team that can take a natural language request and transform it into a complete, working project — file by file — using real developer workflows.

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