Cool Shot Systems

Dockerfile (1).txt

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+FROM python:3.11-slim
+
+# Set environment variables
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+
+# Create non-root user for security
+RUN useradd -m -u 1000 appuser
+
+WORKDIR /app
+
+# Install dependencies first for better caching
+COPY requirements.txt .
+RUN pip install --no-cache-dir --upgrade pip && \
+    pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY --chown=appuser:appuser . .
+
+# Switch to non-root user
+USER appuser
+
+# Hugging Face Spaces runs on port 7860 by default
+EXPOSE 7860
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
+    CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:7860/health')" || exit 1
+
+# Run the application
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

README (4).md

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+---
+title: Image Prediction API
+emoji: 🖼️
+colorFrom: purple
+colorTo: pink
+sdk: docker
+pinned: false
+license: mit
+app_port: 7860
+---
+
+# Image Prediction API
+
+AI-powered image prediction service built with FastAPI.
+
+## Features
+
+- 🔐 **Secure Authentication** - JWT Bearer token verification
+- 🚀 **Fast Performance** - Built on FastAPI with async support
+- 📊 **Health Monitoring** - Built-in health check endpoint
+- 🐳 **Docker Ready** - Optimized for Hugging Face Spaces deployment
+
+## API Endpoints
+
+### Health Check
+```
+GET /health
+```
+Returns the service health status.
+
+### Prediction
+```
+POST /predict
+Authorization: Bearer <token>
+Content-Type: application/json
+
+{
+  "image_url": "https://example.com/image.jpg"
+}
+```
+
+**Response:**
+```json
+{
+  "prediction": "Object detected",
+  "confidence": 0.92,
+  "labels": ["object", "scene", "outdoor"],
+  "image_url": "https://example.com/image.jpg"
+}
+```
+
+## Environment Variables
+
+| Variable | Description | Required |
+|----------|-------------|----------|
+| `JWT_SECRET` | Secret key for JWT token verification | Yes |
+| `ALLOWED_ORIGINS` | Comma-separated list of allowed CORS origins | No |
+
+## Local Development
+
+```bash
+# Install dependencies
+pip install -r requirements.txt
+
+# Set environment variables
+export JWT_SECRET=your_secret_key
+
+# Run the server
+uvicorn main:app --reload --port 8002
+```
+
+## Deployment
+
+This service is designed to run on Hugging Face Spaces with Docker SDK.
+
+1. Create a new Space with Docker SDK
+2. Set the `JWT_SECRET` secret in Space settings
+3. Push this code to the Space repository

auth.py

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+import os
+from fastapi import Depends, HTTPException, status
+from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
+from jose import jwt, JWTError
+
+security = HTTPBearer()
+
+def get_jwt_secret() -> str:
+    """Get JWT secret from environment variable."""
+    secret = os.getenv("JWT_SECRET")
+    if not secret:
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="JWT_SECRET not configured"
+        )
+    return secret
+
+
+def verify_token(credentials: HTTPAuthorizationCredentials = Depends(security)) -> dict:
+    """
+    Verify Bearer token signature.
+    Returns the decoded token payload if valid.
+    Raises HTTPException if invalid.
+    """
+    token = credentials.credentials
+    jwt_secret = get_jwt_secret()
+
+    try:
+        # Decode and verify the JWT token
+        payload = jwt.decode(
+            token,
+            jwt_secret,
+            algorithms=["HS256"],
+            options={"verify_aud": False}  # Clerk tokens may not have standard audience
+        )
+        return payload
+    except JWTError as e:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail=f"Invalid token: {str(e)}",
+            headers={"WWW-Authenticate": "Bearer"},
+        )
+
+
+def get_current_user(token_payload: dict = Depends(verify_token)) -> dict:
+    """
+    Extract user information from verified token.
+    """
+    user_id = token_payload.get("sub")
+    if not user_id:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="Invalid token: missing user ID",
+            headers={"WWW-Authenticate": "Bearer"},
+        )
+    
+    return {
+        "user_id": user_id,
+        "email": token_payload.get("email"),
+        "claims": token_payload
+    }

main.py

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+import os
+
+from fastapi import FastAPI, Depends, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from auth import get_current_user
+
+app = FastAPI(
+    title="Image Prediction API",
+    description="AI-powered image prediction service",
+    version="0.1.0"
+)
+
+# Configure CORS - use environment variable for allowed origins in production
+allowed_origins = os.getenv("ALLOWED_ORIGINS", "").split(",") if os.getenv("ALLOWED_ORIGINS") else ["*"]
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=allowed_origins,
+    allow_credentials=False,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+class ImagePredictRequest(BaseModel):
+    image_url: str
+
+
+class ImagePredictResponse(BaseModel):
+    prediction: str
+    confidence: float
+    labels: list[str]
+    image_url: str
+
+
+@app.get("/")
+async def root():
+    """Health check endpoint."""
+    return {"status": "healthy", "service": "image-api"}
+
+
+@app.get("/health")
+async def health():
+    """Health check endpoint."""
+    return {"status": "healthy"}
+
+
+@app.post("/predict", response_model=ImagePredictResponse)
+async def predict(
+    request: ImagePredictRequest,
+    current_user: dict = Depends(get_current_user)
+):
+    """
+    Protected endpoint for image prediction.
+    Requires valid Bearer token.
+    """
+    # Placeholder prediction logic
+    # In a real application, this would call an ML model
+    image_url = request.image_url
+    
+    # Simple mock prediction
+    prediction = "Object detected"
+    confidence = 0.92
+    labels = ["object", "scene", "outdoor"]
+    
+    return ImagePredictResponse(
+        prediction=prediction,
+        confidence=confidence,
+        labels=labels,
+        image_url=image_url
+    )
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8002)

requirements.txt

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+fastapi>=0.109.0
+uvicorn>=0.27.0
+python-jose[cryptography]>=3.3.0
+httpx>=0.26.0
+pydantic>=2.5.0