codefabric 0.2.2

CodeFabric is an AI-powered code generation framework that spins up full projects from natural language requirements using LangGraph workflows.

🚀 CodeFabric: AI Code Generation Package

Welcome to CodeFabric, your AI-powered coding assistant that generates full projects from plain English! Feed it your idea, and it crafts clean code like a digital artisan 🧙‍♂️—powered by LangGraph for agentic reasoning and execution.

⚠️ Before You Start: If you are using CLI version, you must set your OpenAI API key in your environment variables or .env file as: OPENAI_API_KEY=your_openai_api_key_here

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Features 🌟

• 🧑‍💻 Interactive CLI with beautiful UI (Rich-based) to generate projects quickly
• 🔁 Programmatic API for power users and automation
• 🧠 LLM-driven reasoning, powered by LangGraph
• ⚙️ Supports multiple technologies via the Technologies enum
• 🧩 Pluggable LLM support (use OpenAI or your custom one)
• 📦 Auto setup with logging and task breakdowns

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Prerequisites 🛠️

• Python 3.8+
• pip installed
• Project-specific tools (Node.js for JS projects, etc.)
• Set OPENAI_API_KEY in your environment or .env file

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📦 Installation

pip install codefabric

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🖥️ Option 1: CLI (Recommended)

Launch the interactive CLI to generate a full-stack project with guided input:

codefabric

You'll be prompted to:

• 📝 Enter project name
• 💡 Describe what the project does
• 💻 Choose a technology stack (e.g., Python, Node.js, etc.)
• ✅ Confirm creation

Once confirmed, CodeFabric will automatically generate your full project folder based on your inputs using LangGraph-powered AI agents.

Example CLI Output:

📝 Project Name: portfolio-app
💡 Description: A personal portfolio site with blog and contact form
💻 Technology: Next.js

Your project will be generated and saved into portfolio-app-any/. Logs are printed during generation.

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🧠 Option 2: Programmatic API Usage

You can use CodeFabric inside your own Python script for advanced or automated workflows:

from codefabric.graph.developer_agent import DeveloperAgent
from codefabric.types.models import Requirements
from codefabric.types.enums import Technologies

process_id = "leetcode-agent"
project_description = """Build a python AI agent that takes LeetCode DSA questions, identifies patterns, explains how to solve, and builds a Streamlit app."""

dev_agent = DeveloperAgent(
    process_id=process_id,
    requirements=Requirements(
        project_name="leetcode-agent",
        project_description=project_description,
        packages=[],
        technology=Technologies.PYTHON.value,
    ),
)

dev_agent.run()

Run it:

python run_agent.py

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🔑 Setting Up API Key

To use OpenAI models, add your key to a .env file:

OPENAI_API_KEY=your_openai_api_key_here

Or set it in your shell:

export OPENAI_API_KEY=your_openai_api_key_here

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🗺️ Project Flow

Here’s how CodeFabric works internally:

1. Parses your idea into structured requirements
2. Generates folder structure, code files, and dependencies
3. Generate each planned file with accuracy and correct context from already generated files and description
4. Final project is ready-to-run 🚀

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🐞 Troubleshooting

• ModuleNotFoundError? → Run pip install codefabric
• OPENAI_API_KEY error? → Set it in your environment or .env
• Still stuck? → Check terminal logs

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🤝 Contributing

Pull requests welcome! Fork the repo, make your changes, and help improve CodeFabric.

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📜 License

MIT License. Use freely, build responsibly. Don’t unleash rogue AI without giving us a high-five. 🤖✋

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Happy coding! ✨ May your agents be smart, and your bugs be few.