FrameForge

FrameForge is an AI-powered PC building assistant that helps users create custom computer builds based on their budget and requirements. Using advanced component matching and compatibility checking, FrameForge ensures optimal part selection while maximizing performance within your budget constraints.

Live Demo

[https://abc.com](Live App Demo)

Features

• Smart budget allocation across components
• Real-time compatibility checking
• AI-powered component recommendations
• Interactive part selection interface
• Comprehensive component database with 18,000+ parts
• Price tracking and performance scoring
• Customizable build preferences

Technologies Used

• Next.js 15 with App Router
• Tailwind CSS and Shadcn UI
• Zustand for state management
• Pinecone for vector database
• LangChain for AI processing
• OpenAI for component analysis

Use Cases

• Create custom PC builds within specific budget constraints
• Compare component options with detailed specifications
• Verify compatibility between selected parts
• Get AI-powered recommendations for optimal component matching
• Track prices and performance metrics across different builds

Installation Steps

1. Clone the repository

git clone https://github.com/0xmetaschool/FrameForge.git
cd frameforge

2. Install dependencies

npm install

3. Configure environment variables Create a .env.local file:

PINECONE_API_KEY=
OPENAI_API_KEY=

4. Start development server

npm run dev

5. Open http://localhost:3000

Screenshots

How to Use

1. Set your total budget
2. Select component preferences (CPU/GPU brand, cooling requirements)
3. Choose components with AI-guided recommendations
4. Review compatibility and performance metrics
5. Optimize build based on AI suggestions
6. Save or share your completed build

Component Database

• CPUs: 1,188 entries
• GPUs: 5,165 entries
• Motherboards: 93 entries
• Memory: 1,093 entries
• Storage: 3,790 entries
• Cases: 3,698 entries
• Power Supplies: 2,478 entries
• CPU Coolers: 1,296 entries

Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/NewFeature)
3. Commit changes (git commit -m 'Add NewFeature')
4. Push to branch (git push origin feature/NewFeature)
5. Open Pull Request

License

MIT License - see LICENSE file

Contact

Open an issue in the GitHub repository for support or questions.