"""
COGNEXA ML Service - Endpoint Integration Checklist

This document tracks which endpoints need API patches to fix 422 validation errors.

Last Updated: March 28, 2026
Status: Ready for Integration

SUMMARY:
- Total endpoints: 30+
- Need fixing: 3 (currently return 422)
- Implementation guide: API_INTEGRATION_GUIDE.py
- Test file: test_api_endpoints.py
"""

# ============================================================================
# ENDPOINTS REQUIRING FIXES (422 Errors)
# ============================================================================

ENDPOINTS_TO_FIX = {
    
    # ✅ PRIORITY 1: HIGH - User-Facing Endpoints
    
    "/api/personality/analyze-responses": {
        "method": "POST",
        "priority": "HIGH",
        "current_issue": "422 - Strict Pydantic validation",
        "problem": "Fails on type mismatches: '4' vs 4, '3.5' vs 3.5",
        "solution": "Apply DynamicRequestValidator.validate_personality_responses()",
        "fix_status": "⏳ NOT APPLIED",
        "test_payload": {
            "responses": {"q1": 4, "q2": "3.5", "q3": 5},
            "response_scale_max": 5
        },
        "expected_response": {
            "status": 200,
            "body": {"analysis": {...}}
        }
    },
    
    "/api/productivity/forecast": {
        "method": "POST",
        "priority": "HIGH",
        "current_issue": "422 - Rigid field validation",
        "problem": "Fails on missing optional fields or type coercion",
        "solution": "Apply DynamicRequestValidator.validate_productivity_forecast()",
        "fix_status": "⏳ NOT APPLIED",
        "test_payload": {
            "user_id": "user123",
            "forecast_days": "7",
            "historical_data": [
                {"date": "2026-03-20", "completed_tasks": "5"}
            ]
        },
        "expected_response": {
            "status": 200,
            "body": {"forecast": {...}}
        }
    },
    
    "/api/personalization/predict-engagement": {
        "method": "POST",
        "priority": "HIGH",
        "current_issue": "422 - Strict schema validation",
        "problem": "Doesn't handle flexible input formats or type variations",
        "solution": "Apply DynamicRequestValidator.validate_engagement_prediction()",
        "fix_status": "⏳ NOT APPLIED",
        "test_payload": {
            "user_id": "user123",
            "task_id": "task456",
            "task": {
                "title": "Review notes",
                "category": "WORK",
                "priority": "MEDIUM"
            }
        },
        "expected_response": {
            "status": 200,
            "body": {"engagement_prediction": 0.78}
        }
    }
}

# ============================================================================
# ENDPOINTS ALREADY WORKING (No Fixes Needed)
# ============================================================================

ENDPOINTS_WORKING = {
    
    # ✅ Health & Status
    "/health": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    "/api/status": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    
    # ✅ Task & Completion
    "/api/tasks/predict": {
        "method": "POST",
        "status": "✅ WORKING",
        "uses": "dynamic_trainers (models correctly set up)"
    },
    "/api/v1/tasks": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    "/api/v1/tasks/analytics": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    "/api/tasks/batch-predict": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    
    # ✅ Behavioral & Personality
    "/api/v1/behavioral-personality/blended": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    "/api/v1/behavioral-personality/sync/overview": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    "/api/behavior/cross-device/analyze": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    
    # ✅ Wellbeing
    "/api/wellbeing/summary": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    "/api/wellbeing/recommendations": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    "/api/wellbeing/trends": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    
    # ✅ Gamification
    "/api/v1/gamification/stats": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    "/api/v1/gamification/achievements/user": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    
    # ✅ Notifications
    "/api/notifications/unread-count": {
        "method": "GET",
        "status": "✅ WORKING"
    },
    
    # ✅ Cognitive Theory
    "/ml/cognitive/analyze": {
        "method": "POST",
        "status": "✅ WORKING",
        "uses": "dynamic_trainers + cognitive theory"
    },
    "/ml/cognitive/cognitive-load": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    "/ml/cognitive/personality-fit": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    "/ml/cognitive/flow-state": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    "/ml/cognitive/motivation": {
        "method": "POST",
        "status": "✅ WORKING"
    },
    
    # ✅ Prediction & Explanation
    "/api/predict/explain": {
        "method": "POST",
        "status": "✅ WORKING"
    }
}

# ============================================================================
# IMPLEMENTATION STEPS
# ============================================================================

IMPLEMENTATION_STEPS = [
    {
        "step": 1,
        "title": "Import Required Modules",
        "location": "main.py (top of file)",
        "code": """
from fastapi import Body
from fastapi.responses import JSONResponse
from ML.dynamic_api_handler import DynamicRequestValidator
        """,
        "status": "⏳ PENDING"
    },
    {
        "step": 2,
        "title": "Update /api/personality/analyze-responses",
        "location": "main.py (personality endpoint)",
        "change": """
# BEFORE:
@app.post("/api/personality/analyze-responses")
async def analyze_responses(request: PersonalityResponse):
    ...

# AFTER:
@app.post("/api/personality/analyze-responses")
async def analyze_responses(request: dict = Body(...)):
    try:
        validated = DynamicRequestValidator.validate_personality_responses(request)
        result = analyze_personality_scores(
            responses=validated['responses'],
            response_scale_max=validated['response_scale_max']
        )
        return JSONResponse(status_code=200, content={"status": "success", "analysis": result})
    except ValueError as e:
        return JSONResponse(status_code=400, content={"error": str(e)})
        """,
        "status": "⏳ PENDING"
    },
    {
        "step": 3,
        "title": "Update /api/productivity/forecast",
        "location": "main.py (productivity endpoint)",
        "change": """
# BEFORE:
@app.post("/api/productivity/forecast")
async def forecast_productivity(request: ProductivityForecast):
    ...

# AFTER:
@app.post("/api/productivity/forecast")
async def forecast_productivity(request: dict = Body(...)):
    try:
        validated = DynamicRequestValidator.validate_productivity_forecast(request)
        forecast = generate_forecast(
            user_id=validated['user_id'],
            historical_data=validated['historical_data'],
            forecast_days=validated['forecast_days'],
            personality=validated.get('personality')
        )
        return JSONResponse(status_code=200, content={"status": "success", "forecast": forecast})
    except ValueError as e:
        return JSONResponse(status_code=400, content={"error": str(e)})
        """,
        "status": "⏳ PENDING"
    },
    {
        "step": 4,
        "title": "Update /api/personalization/predict-engagement",
        "location": "main.py (personalization endpoint)",
        "change": """
# BEFORE:
@app.post("/api/personalization/predict-engagement")
async def predict_engagement(request: EngagementPrediction):
    ...

# AFTER:
@app.post("/api/personalization/predict-engagement")
async def predict_engagement(request: dict = Body(...)):
    try:
        validated = DynamicRequestValidator.validate_engagement_prediction(request)
        engagement_score = predict_user_engagement(
            user_id=validated['user_id'],
            task_id=validated['task_id'],
            task=validated['task'],
            user_profile=validated.get('user_profile', {})
        )
        return JSONResponse(status_code=200, content={"engagement_prediction": engagement_score})
    except ValueError as e:
        return JSONResponse(status_code=400, content={"error": str(e)})
        """,
        "status": "⏳ PENDING"
    },
    {
        "step": 5,
        "title": "Test Fixes",
        "location": "Command line",
        "command": "python test_api_endpoints.py",
        "expected": "20+ endpoints tested, success rate > 95%",
        "status": "⏳ PENDING"
    }
]

# ============================================================================
# VALIDATION RULES (From dynamic_api_handler.py)
# ============================================================================

VALIDATION_RULES = {
    "personality_responses": {
        "Field": "responses",
        "Type": "dict",
        "Coercion": "Each value coerced to float (handles '4.5' → 4.5, '5' → 5.0)",
        "Required": True,
        "Default": None
    },
    "personality_responses_scale": {
        "Field": "response_scale_max",
        "Type": "int",
        "Coercion": "Coerces to int ('5' → 5)",
        "Required": False,
        "Default": 5
    },
    "productivity_user_id": {
        "Field": "user_id",
        "Type": "str",
        "Required": True
    },
    "productivity_forecast_days": {
        "Field": "forecast_days",
        "Type": "int",
        "Coercion": "Coerces to int ('7' → 7)",
        "Required": False,
        "Default": 7
    },
    "productivity_historical_data": {
        "Field": "historical_data",
        "Type": "list",
        "Required": True
    },
    "engagement_user_id": {
        "Field": "user_id",
        "Type": "str",
        "Required": True
    },
    "engagement_task_id": {
        "Field": "task_id",
        "Type": "str",
        "Required": True
    },
    "engagement_task": {
        "Field": "task",
        "Type": "dict",
        "Required": True
    }
}

# ============================================================================
# QUICK FIX SCRIPT
# ============================================================================

"""
To quickly apply all patches at once, run:

python -c "
import sys
from pathlib import Path

# This demonstrates automated patching (manual application recommended for safety)
print('🔧 ENDPOINT PATCH APPLICATION')
print('='*70)
print()
print('⚠️  RECOMMENDED: Apply patches manually to main.py')
print()
print('Steps:')
print('1. Open main.py in your editor')
print('2. Find the 3 problematic endpoints')
print('3. Follow the changes in IMPLEMENTATION_STEPS above')
print('4. Test with: python test_api_endpoints.py')
print()
print('This ensures you have full control and understand the changes.')
print()
"
"""

# ============================================================================
# ROLLBACK INSTRUCTIONS
# ============================================================================

ROLLBACK_INSTRUCTIONS = """
If you need to rollback changes:

1. Revert endpoint signatures:
   From: def endpoint(request: dict = Body(...)):
   To:   def endpoint(request: EndpointModel):

2. Revert validation:
   Remove: DynamicRequestValidator.validate_*()
   Add:    Original validation logic

3. Restore error handling:
   Remove: JSONResponse with custom errors
   Add:    Original Pydantic 422 responses

Or use git:
   git checkout main.py
"""

# ============================================================================
# DOCUMENTATION REFERENCES
# ============================================================================

DOCUMENTATION = {
    "API_INTEGRATION_GUIDE.py": "Step-by-step integration guide with examples",
    "dynamic_api_handler.py": "Validator implementation (500+ lines)",
    "QUICK_REFERENCE.md": "Quick reference for commands and troubleshooting",
    "test_api_endpoints.py": "Comprehensive API test suite",
    "test_ml_service.py": "Model loading and validation tests"
}

# ============================================================================
# COMPLETION CHECKLIST
# ============================================================================

CHECKLIST = """
PRE-IMPLEMENTATION:
  [ ] Read API_INTEGRATION_GUIDE.py
  [ ] Backup main.py: cp main.py main.py.backup
  [ ] Verify test_api_endpoints.py ready: ls test_api_endpoints.py

IMPLEMENTATION:
  [ ] Step 1: Add imports to main.py
  [ ] Step 2: Update /api/personality/analyze-responses
  [ ] Step 3: Update /api/productivity/forecast
  [ ] Step 4: Update /api/personalization/predict-engagement
  [ ] Verify no syntax errors: python -m py_compile main.py

TESTING:
  [ ] Restart ML service: python main.py
  [ ] Run endpoint tests: python test_api_endpoints.py
  [ ] Verify 422 errors → 400 errors (or 200 success)
  [ ] Test with cURL: curl -X POST http://localhost:8000/api/personality/analyze-responses
  [ ] Monitor logs for errors

POST-IMPLEMENTATION:
  [ ] All 3 endpoints returning success (not 422)
  [ ] Update team documentation
  [ ] Deploy to production
  [ ] Monitor error rates
"""

# ============================================================================
# PRINT SUMMARY
# ============================================================================

if __name__ == "__main__":
    print("="*70)
    print("COGNEXA ML SERVICE - ENDPOINT INTEGRATION CHECKLIST")
    print("="*70)
    
    print("\n📋 ENDPOINTS REQUIRING FIXES:")
    for endpoint, details in ENDPOINTS_TO_FIX.items():
        print(f"\n  {endpoint}")
        print(f"    Priority: {details['priority']}")
        print(f"    Status: {details['fix_status']}")
        print(f"    Issue: {details['current_issue']}")
    
    print(f"\n✅ ENDPOINTS ALREADY WORKING: {len(ENDPOINTS_WORKING)}")
    
    print("\n📚 DOCUMENTATION:")
    for file, desc in DOCUMENTATION.items():
        print(f"  - {file}: {desc}")
    
    print("\n" + "="*70)
    print("NEXT STEPS:")
    print("="*70)
    print("1. Read: API_INTEGRATION_GUIDE.py")
    print("2. Apply: 4 implementation steps (update 3 endpoints + imports)")
    print("3. Test: python test_api_endpoints.py")
    print("4. Verify: All endpoints return success (not 422)")
    print("="*70)