SzpakLabs pablo-astrobot-api .cursorrules file for TypeScript

# Pablo Astrobot API

### 🎯 **Goals:**
1. Set up a Fastify server within Firebase Cloud Functions.
2. Implement API routes for the chatbot and OCR functionalities:
   - `POST /api/analyze/ocr`: Use Tesseract.js to extract text from uploaded images.
   - `POST /api/analyze/vision`: Use OpenAI Vision API for advanced image analysis.
   - `POST /api/report/generate`: Generate and return a report based on OCR/OpenAI data.
3. Configure routes with proper JSON schema validation.
4. Enable file uploads using `@fastify/multipart`.
5. Store uploaded images in Firebase Storage (if needed).
6. Load environment variables from `.env` for API keys and configuration.
7. Add error handling and logging for each route.
8. Document the API endpoints using Swagger (`@fastify/swagger`).
9. Ensure CORS is enabled for cross-origin requests.
10. Provide a basic example of deployment to Firebase Functions.

### ⚙️ **Instructions:**
1. Set up a basic Fastify server in `app.js`.
2. Register CORS, Multipart, and Swagger plugins.
3. Add route registration for OCR, Vision API, and Report generation.
4. Create controllers for each route with asynchronous handlers.
5. Ensure environment variables (e.g., OpenAI API Key) are loaded from `.env`.
6. Add proper error handling for all routes.
7. Configure `index.js` to expose the Fastify app as a Firebase Cloud Function.
8. Test the API locally using ThunderClient or Firebase local emulator.
9. Deploy the application using `firebase deploy --only functions`.

### 📊 **Sample API Endpoints:**
- `POST /api/analyze/ocr` → Extract text from an uploaded image.
- `POST /api/analyze/vision` → Analyze images using OpenAI Vision API.
- `POST /api/report/generate` → Generate reports based on OCR/OpenAI data.

### 🔑 **Additional Notes:**
- Include validation schemas for incoming requests.
- Ensure secrets (API keys) are not hardcoded but securely accessed via `.env`.
- Document all endpoints using Swagger UI.
- Test error scenarios for each route (e.g., invalid images, missing parameters).

### 🚀 **Next Steps:**
1. Implement the server logic based on this structure.
2. Test endpoints locally using ThunderClient.
3. Deploy the application to Firebase Functions.
4. Verify functionality via deployed endpoints.

Make sure the deployment is optimized for Firebase's cold start behavior.