Developer Docs

Create a new Next.js 14 application with the following specifications:

**Tech Stack:**
- Next.js 14 with App Router
- TypeScript for type safety
- Tailwind CSS for styling
- Prisma with PostgreSQL for database
- NextAuth.js for authentication

**Project Structure:**
- `/app` directory structure with proper layouts
- `/components` for reusable UI components
- `/lib` for utilities and database configuration
- `/types` for TypeScript definitions

**Initial Features:**
- Landing page with hero section and navigation
- User authentication (sign up, login, logout)
- Protected dashboard route
- Responsive design with dark mode support

Set up the basic project structure and create placeholder components.

Design a component architecture for a [describe app type] application:

**Component Categories:**
- UI components (buttons, inputs, cards)
- Layout components (header, sidebar, footer)
- Feature components (user profile, product listing)
- Page components (home, dashboard, settings)

**Requirements:**
- TypeScript interfaces for all props
- Compound component patterns where appropriate
- Accessibility features (ARIA labels, keyboard navigation)
- Consistent styling with Tailwind CSS variants

Include examples of 2-3 components with proper TypeScript typing.

Create a FastAPI application with the following requirements:

**Features:**
- RESTful API with CRUD operations
- User authentication with JWT tokens
- Database integration with SQLAlchemy
- Input validation with Pydantic
- Automated API documentation

**Structure:**
- `/models` for database models
- `/routers` for API endpoints
- `/schemas` for Pydantic models
- `/auth` for authentication logic

Include user registration, login, and protected endpoints.

Build a data processing pipeline that:

**Input Sources:**
- CSV files from uploads
- Database queries
- API endpoints

**Processing Steps:**
- Data cleaning and validation
- Statistical analysis
- Visualization generation
- Export to multiple formats

**Output:**
- Processed datasets
- Summary statistics
- Interactive charts
- Automated reports

Use pandas, numpy, and plotly for implementation.

Create a Gradio interface for [ML model type]:

**Interface Components:**
- File upload for input data
- Parameter sliders for model tuning
- Real-time prediction display
- Confidence scores and explanations
- Download results functionality

**Features:**
- Batch processing capabilities
- Model comparison tools
- Performance metrics display
- Error handling and validation

Include examples with sample data and clear instructions.

Build a Gradio dashboard for data exploration:

**Components:**
- Dataset upload and preview
- Interactive charts and plots
- Statistical summary tables
- Filter and search capabilities
- Export functionality

**Visualizations:**
- Distribution plots
- Correlation matrices
- Time series analysis
- Geographic mapping (if applicable)

Make it responsive and user-friendly for non-technical users.

Create a comprehensive analytics dashboard using Streamlit:

**Data Sources:**
- Multiple data source connections (CSV, database, API)
- Real-time data refresh capabilities
- Data caching for performance
- Error handling for data loading

**Dashboard Layout:**
- Multi-page application structure
- Sidebar navigation and filters
- Responsive grid layout
- Customizable date ranges
- Export functionality

**Visualizations:**
- KPI metrics with st.metric()
- Interactive charts with Plotly
- Data tables with filtering/sorting
- Geographic visualizations

Include caching and performance optimization.

Build a complete ML application with Streamlit:

**Features:**
- Model training interface
- Hyperparameter tuning
- Performance evaluation
- Prediction interface
- Model deployment options

**Components:**
- Data upload and preprocessing
- Model selection and training
- Results visualization
- Model comparison tools
- Export trained models

Include proper error handling and user guidance.