codefabric 0.1.3

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. Constructs LangGraph agent flow
3. Generates folder structure, code files, and dependencies
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.