# Opus Magnum Submission API Usage

## Overview

The API is built with Django Ninja and provides endpoints for managing puzzle submissions with OCR validation and S3 file storage.

## Base URL
- Development: `http://localhost:8000/api/`
- API Documentation: `http://localhost:8000/api/docs/`

## Authentication
Most endpoints support both authenticated and anonymous submissions. Admin endpoints require staff permissions.

## Environment Variables

### Required for S3 Storage
```bash
USE_S3=true
AWS_ACCESS_KEY_ID=your_access_key
AWS_SECRET_ACCESS_KEY=your_secret_key
AWS_STORAGE_BUCKET_NAME=your_bucket_name
AWS_S3_REGION_NAME=us-east-1
```

### Optional
```bash
STEAM_API_KEY=your_steam_api_key
```

## API Endpoints

### 1. Get Available Puzzles
```http
GET /api/submissions/puzzles
```

Response:
```json
[
  {
    "id": 1,
    "steam_item_id": "3479143948",
    "title": "P41-FLOC",
    "author_name": "Flame Legrems",
    "description": "A challenging puzzle...",
    "tags": ["puzzle", "chemistry"],
    "order_index": 0,
    "steam_url": "https://steamcommunity.com/workshop/filedetails/?id=3479143948",
    "created_at": "2025-05-29T11:19:24Z",
    "updated_at": "2025-05-30T22:15:09Z"
  }
]
```

### 2. Create Submission
```http
POST /api/submissions/submissions
Content-Type: multipart/form-data
```

Form Data:
- `data`: JSON with submission data
- `files`: Array of uploaded files

Example data:
```json
{
  "notes": "My best solutions so far",
  "responses": [
    {
      "puzzle_id": 1,
      "puzzle_name": "P41-FLOC",
      "cost": "150",
      "cycles": "89", 
      "area": "12",
      "needs_manual_validation": false,
      "ocr_confidence_score": 0.95
    }
  ]
}
```

Response:
```json
{
  "id": "123e4567-e89b-12d3-a456-426614174000",
  "user": null,
  "notes": "My best solutions so far",
  "responses": [
    {
      "id": 1,
      "puzzle": 1,
      "puzzle_name": "P41-FLOC",
      "cost": "150",
      "cycles": "89",
      "area": "12",
      "needs_manual_validation": false,
      "files": [
        {
          "id": 1,
          "original_filename": "solution.gif",
          "file_size": 1024000,
          "content_type": "image/gif",
          "file_url": "https://bucket.s3.amazonaws.com/media/submissions/123.../file.gif",
          "ocr_processed": false,
          "created_at": "2025-10-29T00:00:00Z"
        }
      ],
      "final_cost": "150",
      "final_cycles": "89", 
      "final_area": "12"
    }
  ],
  "total_responses": 1,
  "needs_validation": false,
  "is_validated": false,
  "created_at": "2025-10-29T00:00:00Z"
}
```

### 3. List Submissions
```http
GET /api/submissions/submissions?limit=20&offset=0
```

### 4. Get Submission Details
```http
GET /api/submissions/submissions/{submission_id}
```

### 5. Admin: Validate Response (Staff Only)
```http
PUT /api/submissions/responses/{response_id}/validate
Content-Type: application/json
```

Body:
```json
{
  "validated_cost": "150",
  "validated_cycles": "89",
  "validated_area": "12"
}
```

### 6. Admin: List Responses Needing Validation (Staff Only)
```http
GET /api/submissions/responses/needs-validation
```

### 7. Admin: Validate Entire Submission (Staff Only)
```http
POST /api/submissions/submissions/{submission_id}/validate
```

### 8. Get Statistics
```http
GET /api/submissions/stats
```

Response:
```json
{
  "total_submissions": 150,
  "total_responses": 300,
  "needs_validation": 25,
  "validated_submissions": 120,
  "validation_rate": 0.8
}
```

## OCR Validation Logic

The system automatically flags responses for manual validation when:

1. **Incomplete OCR Data**: Missing cost, cycles, or area values
2. **Low Confidence**: OCR confidence score below threshold
3. **Manual Flag**: Explicitly marked by frontend OCR processing

### Manual Validation Workflow

1. Admin views responses needing validation: `GET /responses/needs-validation`
2. Admin reviews the uploaded files and OCR results
3. Admin provides corrected values: `PUT /responses/{id}/validate`
4. System updates `validated_*` fields and clears validation flag
5. Optional: Mark entire submission as validated: `POST /submissions/{id}/validate`

## File Storage

- **Development**: Files stored locally in `media/submissions/`
- **Production**: Files stored in S3 with path structure: `submissions/{submission_id}/{uuid}_{filename}`
- **Supported Formats**: JPEG, PNG, GIF, MP4, WebM
- **Size Limit**: 10MB per file

## Error Handling

The API returns standard HTTP status codes:

- `200`: Success
- `400`: Bad Request (validation errors)
- `401`: Unauthorized
- `403`: Forbidden (admin required)
- `404`: Not Found
- `500`: Internal Server Error

Error Response Format:
```json
{
  "detail": "Error message",
  "code": "error_code"
}
```

## Frontend Integration

The Vue frontend should:

1. Upload files with OCR data extracted client-side
2. Group files by detected puzzle name
3. Create one submission with multiple responses
4. Handle validation flags and display admin feedback
5. Show file upload progress and S3 URLs

## Admin Interface

Django Admin provides:

- **Submission Management**: View, validate, and manage submissions
- **Response Validation**: Bulk actions for validation workflow
- **File Management**: View uploaded files and OCR data
- **Statistics Dashboard**: Track validation rates and submission metrics
