docs/API_MODELS_SUMMARY.md

# 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