README.md

metadata

title: PromptAid Vision
emoji: 🚀
colorFrom: blue
colorTo: red
sdk: docker
sdk_version: 4.0.0
app_file: app.py
pinned: false

PromptAid Vision

An AI-powered platform for crisis mapping and drone image analysis.

Overview

PromptAid Vision combines multiple AI vision models (GPT-4V, Gemini, Hugging Face) to analyze imagery for crisis response and humanitarian mapping. The platform provides automated image analysis, metadata extraction, and comprehensive reporting capabilities.

Architecture

• Frontend: React + TypeScript with Tailwind CSS
• Backend: FastAPI + Python with PostgreSQL
• AI Models: Multi-model support with intelligent fallbacks
• Storage: Flexible local/S3 storage with image processing
• Testing: Unit, integration, and E2E test coverage

Quick Start

Prerequisites

• Node.js 20+
• Python 3.11+
• PostgreSQL 16+

Development Setup

1. Backend

   cd py_backend
   python -m venv .venv
   source .venv/bin/activate  # Windows: .venv\Scripts\activate
   pip install -r requirements.txt
   alembic upgrade head
   uvicorn app.main:app --reload --port 7860
   

2. Frontend

   cd frontend
   npm install
   npm run dev
   

3. Access

   • Application: http://localhost:5173
   • API: http://localhost:7860
   • Documentation: http://localhost:7860/docs

Deployment

Local Production

cd frontend && npm run build
cd py_backend && uvicorn app.main:app --host 0.0.0.0 --port 7860

Docker

docker-compose up --build

Hugging Face Spaces

Automatically deployed via GitHub Actions workflow. Configure environment variables in Space settings.

Environment Variables

DATABASE_URL=postgresql://user:password@localhost:5432/promptaid
STORAGE_PROVIDER=local  # or s3
OPENAI_API_KEY=your-key
ANTHROPIC_API_KEY=your-key
GOOGLE_API_KEY=your-key
HUGGINGFACE_API_KEY=your-key

Testing

# Backend
cd py_backend && python -m pytest tests/ -v

# Frontend
cd frontend && npm run test:unit

# E2E
cd e2e && ./run_e2e_tests.sh

Project Structure

├── frontend/          # React frontend
├── py_backend/        # FastAPI backend
├── e2e/              # End-to-end tests
└── .github/workflows/ # CI/CD pipelines

Contributing

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Submit a pull request

License

MIT License