# API Models Implementation Summary ## Overview Created a dedicated, rigorously defined Pydantic models module (`ylff/api_models.py`) for all API request/response schemas with comprehensive validation, documentation, and type safety. ## ✅ Completed ### 1. **Created `ylff/api_models.py`** - ✅ All API models extracted and enhanced - ✅ Comprehensive field validation - ✅ Detailed descriptions and examples - ✅ Custom validators for complex rules - ✅ Type-safe enums - ✅ JSON schema examples ### 2. **Model Categories** #### Enums (Type Safety) - ✅ `JobStatus`: Job execution status values - ✅ `DeviceType`: Device selection (CPU, CUDA, MPS) - ✅ `UseCase`: Use case for model selection #### Request Models - ✅ `ValidateSequenceRequest`: Sequence validation - ✅ `ValidateARKitRequest`: ARKit validation - ✅ `BuildDatasetRequest`: Dataset building - ✅ `TrainRequest`: Model fine-tuning - ✅ `PretrainRequest`: Model pre-training (ARKit-specific) - ✅ `EvaluateBAAgreementRequest`: BA agreement evaluation - ✅ `VisualizeRequest`: Result visualization #### Response Models - ✅ `JobResponse`: Standard job-based response - ✅ `ValidationStats`: BA validation statistics - ✅ `HealthResponse`: Health check response - ✅ `ModelsResponse`: Models list response - ✅ `ErrorResponse`: Standard error response ### 3. **Validation Features** #### Range Constraints - ✅ Numeric ranges: `ge`, `le`, `gt`, `lt` - ✅ String lengths: `min_length` - ✅ Angle ranges: 0-180 degrees - ✅ Quality ranges: 0.0-1.0 #### Custom Validators - ✅ `reject_threshold > accept_threshold` validation - ✅ Path format validation - ✅ Non-empty string validation #### Type Safety - ✅ Enums for categorical values - ✅ Optional fields clearly marked - ✅ Required fields explicitly defined ### 4. **Documentation** - ✅ Field descriptions for all fields - ✅ Examples for every field - ✅ JSON schema examples in `model_config` - ✅ Comprehensive model documentation ### 5. **Updated `ylff/api.py`** - ✅ Removed inline model definitions - ✅ Import all models from `api_models` - ✅ All endpoints use imported models - ✅ Maintained backward compatibility ## Model Features ### Field Validation Examples ```python # Range validation accept_threshold: float = Field( 2.0, ge=0.0, # Greater than or equal to 0 le=180.0, # Less than or equal to 180 ) # String validation sequence_dir: str = Field( ..., min_length=1, # Cannot be empty ) # Custom validator @field_validator("reject_threshold") @classmethod def reject_greater_than_accept(cls, v, info): if v <= info.data["accept_threshold"]: raise ValueError("reject_threshold must be > accept_threshold") return v ``` ### Enum Usage ```python # Type-safe device selection device: DeviceType = Field( DeviceType.CPU, examples=["cpu", "cuda", "mps"], ) # Type-safe use case use_case: UseCase = Field( UseCase.BA_VALIDATION, examples=["ba_validation", "mono_depth"], ) ``` ## Benefits 1. **Type Safety**: Catch errors at request validation time 2. **Documentation**: Auto-generated API docs with examples 3. **Validation**: Comprehensive input validation before processing 4. **Consistency**: Standardized request/response formats 5. **Maintainability**: Centralized model definitions 6. **Developer Experience**: Clear error messages and examples 7. **API Discovery**: JSON schema examples enable client generation ## File Structure ``` ylff/ ├── api.py # API endpoints (imports models) ├── api_models.py # All Pydantic models (NEW) └── api_middleware.py # Middleware utilities docs/ ├── API_MODELS.md # Comprehensive model documentation └── API_MODELS_SUMMARY.md # This file ``` ## Next Steps The models are now: - ✅ Rigorously defined with validation - ✅ Well-documented with examples - ✅ Type-safe with enums - ✅ Ready for API documentation generation - ✅ Ready for client SDK generation Future enhancements: - [ ] Add response models for all endpoints - [ ] Add pagination models for list endpoints - [ ] Add filter/sort models for query parameters - [ ] Generate OpenAPI schema from models - [ ] Create client SDK from models