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# 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
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