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## Overview
Enhanced all API endpoints with comprehensive logging, profiling, and error handling for production-ready operation.
## ✅ Completed Enhancements
### 1. **Request Logging Middleware**
- ✅ Added `RequestLoggingMiddleware` to log all HTTP requests/responses
- ✅ Automatic request ID generation and tracking
- ✅ Logs request method, path, client IP, query params
- ✅ Logs response status code and duration
- ✅ Adds request ID to response headers
### 2. **Enhanced Error Handling**
- ✅ Global exception handler for unhandled exceptions
- ✅ Validation error handler (Pydantic) with detailed messages
- ✅ Specific handlers for `FileNotFoundError`, `PermissionError`, `ValueError`
- ✅ Structured error responses with error types and request IDs
- ✅ Full traceback logging for debugging
### 3. **Enhanced CLI Command Execution**
- ✅ Comprehensive logging in `run_cli_command()`
- ✅ Execution timing tracking
- ✅ Error classification (Exit codes, KeyboardInterrupt, Exceptions)
- ✅ Full traceback capture
- ✅ Output length tracking (stdout/stderr)
- ✅ Duration tracking for performance monitoring
### 4. **Background Task Enhancement**
- ✅ Pre-execution input validation (path existence checks)
- ✅ Structured logging with job_id, request_id, timestamps
- ✅ Error context capture (error type, message, traceback)
- ✅ Job metadata tracking (duration, created_at, completed_at)
- ✅ Profiling integration with `profile_context`
- ✅ Specific error handling for common exceptions
### 5. **Endpoint Enhancements**
#### ✅ Health Endpoint (`/health`)
- Request ID tracking
- Profiler status information
- Timestamp in response
#### ✅ Models Endpoint (`/models`)
- Request/response logging
- Error handling with detailed messages
- Duration tracking
#### ✅ Sequence Validation (`/api/v1/validate/sequence`)
- Input validation (path existence)
- Comprehensive logging
- Error handling for all failure modes
- Job metadata tracking
- Profiling integration
#### ✅ ARKit Validation (`/api/v1/validate/arkit`)
- Input validation (path existence)
- Comprehensive logging
- Error handling for all failure modes
- Job metadata tracking
- Profiling integration
- Validation statistics extraction with error handling
### 6. **Request ID Tracking**
- ✅ Automatic generation if not provided
- ✅ Included in all log entries
- ✅ Added to response headers
- ✅ Trackable across request lifecycle
### 7. **Structured Logging**
- ✅ All logs use structured data with `extra` parameter
- ✅ Consistent log levels (INFO, WARNING, ERROR, DEBUG)
- ✅ Context-rich logging (request_id, job_id, durations, etc.)
### 8. **Profiling Integration**
- ✅ Automatic profiling context for API endpoints
- ✅ Background task profiling
- ✅ Profiler initialization on startup
- ✅ Conditional profiling (graceful fallback if unavailable)
## 📊 Logging Structure
### Log Format
```
%(asctime)s - %(name)s - %(levelname)s - %(message)s
```
### Structured Data Fields
- `request_id`: Unique request identifier
- `job_id`: Background job identifier
- `duration` / `duration_ms`: Execution time
- `status_code`: HTTP status code
- `error` / `error_type`: Error information
- `method`, `path`, `client_ip`: Request information
## 🔍 Example Log Output
### Request Start
```
2025-12-06 15:30:00 - ylff.api - INFO - Request started: POST /api/v1/validate/arkit
Extra: {"request_id": "req_123", "method": "POST", "path": "/api/v1/validate/arkit", "client_ip": "192.168.1.1"}
```
### Job Execution
```
2025-12-06 15:30:01 - ylff.api - INFO - Starting ARKit validation job: job_456
Extra: {"job_id": "job_456", "arkit_dir": "assets/examples/ARKit", "duration": 125.3}
```
### Error
```
2025-12-06 15:32:06 - ylff.api - ERROR - ARKit validation job failed: job_456
Extra: {"job_id": "job_456", "error": "File not found", "error_type": "FileNotFoundError"}
```
## 🎯 Error Response Format
All errors return structured JSON:
```json
{
"error": "ErrorType",
"message": "Human-readable message",
"request_id": "req_123",
"details": {...} // Optional
}
```
## 📝 Key Files Modified
1. **`ylff/api.py`**:
- Added middleware
- Enhanced all endpoints
- Enhanced `run_cli_command()`
- Enhanced background task functions
- Added exception handlers
2. **`ylff/api_middleware.py`** (NEW):
- Middleware utilities
- Decorator for endpoint logging
- Error handling decorators
3. **`docs/API_ENHANCEMENTS.md`** (NEW):
- Comprehensive documentation
- Examples and usage patterns
## 🚀 Benefits
1. **Debugging**: Full tracebacks and context in logs
2. **Monitoring**: Request IDs enable log correlation
3. **Performance**: Timing information for all operations
4. **Reliability**: Comprehensive error handling prevents crashes
5. **Observability**: Structured logs enable better analysis
6. **User Experience**: Clear, actionable error messages
## 🔄 Next Steps
The remaining endpoints (dataset build, training, evaluation, visualization) can be enhanced following the same pattern. The structure is now in place for easy replication.
## 📚 Usage
### Viewing Logs
- Logs output to stdout/stderr
- View in RunPod logs dashboard
- Filter by `request_id` or `job_id` for debugging
### Request ID
Include custom request ID for tracking:
```bash
curl -H "X-Request-ID: my-custom-id" https://api.example.com/health
```
### Error Debugging
1. Extract `request_id` from error response
2. Search logs for that `request_id`
3. See full execution trace and error details
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