SearchUS

A web application for searching San Francisco Street View images using semantic search powered by Cohere embeddings and Pinecone vector database.

Project Structure

SearchUS/
├── backend/              # FastAPI backend
│   ├── app/
│   │   ├── api/         # API endpoints
│   │   ├── services/    # Business logic
│   │   └── utils/       # Utility functions
│   └── requirements.txt
├── frontend/            # Next.js frontend
│   ├── app/            # Next.js App Router pages
│   ├── components/     # React components
│   ├── lib/            # API client
│   ├── types/          # TypeScript types
│   └── utils/          # Utility functions
├── embed/              # Embedding pipeline (existing)
└── GoogleScraper/       # Street View scraper (existing)

Features

• Text Search: Search Street View images using natural language queries
• Image Search: Upload an image to find similar Street View images
• Interactive Results: View results with similarity scores and metadata
• Google Maps Integration: Direct links to locations and Street View
• Responsive Design: Works on desktop and mobile devices

Setup

Backend Setup

1. Navigate to backend directory:

cd backend

2. Create virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Set up environment variables:

cp .env.example .env
# Edit .env and add your API keys

5. Run the backend:

uvicorn app.main:app --reload --port 8000

The API will be available at http://localhost:8000

Frontend Setup

1. Navigate to frontend directory:

cd frontend

2. Install dependencies:

bun install

3. Set up environment variables:

cp .env.local.example .env.local
# Edit .env.local and configure API URL

4. Run the frontend:

bun run dev

The app will be available at http://localhost:3000

Environment Variables

Backend (.env)

• COHERE_API_KEY: Your Cohere API key
• PINECONE_API_KEY: Your Pinecone API key

Frontend (.env.local)

• NEXT_PUBLIC_API_URL: Backend API URL (default: http://localhost:8000)
• NEXT_PUBLIC_GOOGLE_MAPS_API_KEY: (Optional) Google Maps API key for embedded maps

API Endpoints

POST /api/search/text

Search by text query.

Request:

{
  "query": "urban street scene",
  "top_k": 10
}

Response:

{
  "results": [...],
  "query_type": "text",
  "total_results": 10
}

POST /api/search/image

Search by image upload.

Request: multipart/form-data

• file: Image file
• top_k: Number of results (optional, default: 10)

Response:

{
  "results": [...],
  "query_type": "image",
  "total_results": 10
}

Development

Backend

cd backend
uvicorn app.main:app --reload --port 8000

Frontend

cd frontend
npm run dev

License

MIT