Implement persona generation system with platform-specific adaptations

Co-authored-by: ajay.calsoft <ajay.calsoft@gmail.com>

backend/api/persona.py

@@ -0,0 +1,385 @@
+"""
+Persona API endpoints for ALwrity.
+Handles writing persona generation, management, and platform-specific adaptations.
+"""
+
+from fastapi import HTTPException, Depends
+from pydantic import BaseModel, Field
+from typing import Dict, Any, List, Optional
+from datetime import datetime
+from loguru import logger
+
+from services.persona_analysis_service import PersonaAnalysisService
+from services.database import get_db
+
+class PersonaGenerationRequest(BaseModel):
+    """Request model for persona generation."""
+    onboarding_session_id: Optional[int] = Field(None, description="Specific onboarding session ID to use")
+    force_regenerate: bool = Field(False, description="Force regeneration even if persona exists")
+
+class PersonaResponse(BaseModel):
+    """Response model for persona data."""
+    persona_id: int
+    persona_name: str
+    archetype: str
+    core_belief: str
+    confidence_score: float
+    platforms: List[str]
+    created_at: str
+
+class PlatformPersonaResponse(BaseModel):
+    """Response model for platform-specific persona."""
+    platform_type: str
+    sentence_metrics: Dict[str, Any]
+    lexical_features: Dict[str, Any]
+    content_format_rules: Dict[str, Any]
+    engagement_patterns: Dict[str, Any]
+    platform_best_practices: Dict[str, Any]
+
+class PersonaGenerationResponse(BaseModel):
+    """Response model for persona generation result."""
+    success: bool
+    persona_id: Optional[int] = None
+    message: str
+    confidence_score: Optional[float] = None
+    data_sufficiency: Optional[float] = None
+    platforms_generated: List[str] = []
+
+# Dependency to get persona service
+def get_persona_service() -> PersonaAnalysisService:
+    """Get the persona analysis service instance."""
+    return PersonaAnalysisService()
+
+async def generate_persona(user_id: int, request: PersonaGenerationRequest):
+    """Generate a new writing persona from onboarding data."""
+    try:
+        logger.info(f"Generating persona for user {user_id}")
+        
+        persona_service = get_persona_service()
+        
+        # Check if persona already exists and force_regenerate is False
+        if not request.force_regenerate:
+            existing_personas = persona_service.get_user_personas(user_id)
+            if existing_personas:
+                return PersonaGenerationResponse(
+                    success=False,
+                    message="Persona already exists. Use force_regenerate=true to create a new one.",
+                    persona_id=existing_personas[0]["id"]
+                )
+        
+        # Generate new persona
+        result = persona_service.generate_persona_from_onboarding(
+            user_id=user_id,
+            onboarding_session_id=request.onboarding_session_id
+        )
+        
+        if "error" in result:
+            return PersonaGenerationResponse(
+                success=False,
+                message=result["error"]
+            )
+        
+        return PersonaGenerationResponse(
+            success=True,
+            persona_id=result["persona_id"],
+            message="Persona generated successfully",
+            confidence_score=result["analysis_metadata"]["confidence_score"],
+            data_sufficiency=result["analysis_metadata"].get("data_sufficiency", 0.0),
+            platforms_generated=list(result["platform_personas"].keys())
+        )
+        
+    except Exception as e:
+        logger.error(f"Error generating persona: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to generate persona: {str(e)}")
+
+async def get_user_personas(user_id: int):
+    """Get all personas for a user."""
+    try:
+        persona_service = get_persona_service()
+        personas = persona_service.get_user_personas(user_id)
+        
+        return {
+            "personas": personas,
+            "total_count": len(personas)
+        }
+        
+    except Exception as e:
+        logger.error(f"Error getting user personas: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to get personas: {str(e)}")
+
+async def get_persona_details(user_id: int, persona_id: int):
+    """Get detailed information about a specific persona."""
+    try:
+        from services.database import get_db_session
+        from models.persona_models import WritingPersona, PlatformPersona
+        
+        session = get_db_session()
+        
+        # Get persona
+        persona = session.query(WritingPersona).filter(
+            WritingPersona.id == persona_id,
+            WritingPersona.user_id == user_id,
+            WritingPersona.is_active == True
+        ).first()
+        
+        if not persona:
+            raise HTTPException(status_code=404, detail="Persona not found")
+        
+        # Get platform adaptations
+        platform_personas = session.query(PlatformPersona).filter(
+            PlatformPersona.writing_persona_id == persona_id,
+            PlatformPersona.is_active == True
+        ).all()
+        
+        result = persona.to_dict()
+        result["platform_adaptations"] = [pp.to_dict() for pp in platform_personas]
+        
+        session.close()
+        return result
+        
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting persona details: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to get persona details: {str(e)}")
+
+async def get_platform_persona(user_id: int, platform: str):
+    """Get persona adaptation for a specific platform."""
+    try:
+        persona_service = get_persona_service()
+        platform_persona = persona_service.get_persona_for_platform(user_id, platform)
+        
+        if not platform_persona:
+            raise HTTPException(status_code=404, detail=f"No persona found for platform {platform}")
+        
+        return platform_persona
+        
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting platform persona: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to get platform persona: {str(e)}")
+
+async def update_persona(user_id: int, persona_id: int, update_data: Dict[str, Any]):
+    """Update an existing persona."""
+    try:
+        from services.database import get_db_session
+        from models.persona_models import WritingPersona
+        
+        session = get_db_session()
+        
+        persona = session.query(WritingPersona).filter(
+            WritingPersona.id == persona_id,
+            WritingPersona.user_id == user_id
+        ).first()
+        
+        if not persona:
+            raise HTTPException(status_code=404, detail="Persona not found")
+        
+        # Update allowed fields
+        updatable_fields = [
+            'persona_name', 'archetype', 'core_belief', 'brand_voice_description',
+            'linguistic_fingerprint', 'platform_adaptations'
+        ]
+        
+        for field in updatable_fields:
+            if field in update_data:
+                setattr(persona, field, update_data[field])
+        
+        persona.updated_at = datetime.utcnow()
+        session.commit()
+        session.close()
+        
+        return {
+            "message": "Persona updated successfully",
+            "persona_id": persona_id,
+            "updated_at": persona.updated_at.isoformat()
+        }
+        
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error updating persona: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to update persona: {str(e)}")
+
+async def delete_persona(user_id: int, persona_id: int):
+    """Delete a persona (soft delete by setting is_active=False)."""
+    try:
+        from services.database import get_db_session
+        from models.persona_models import WritingPersona, PlatformPersona
+        
+        session = get_db_session()
+        
+        persona = session.query(WritingPersona).filter(
+            WritingPersona.id == persona_id,
+            WritingPersona.user_id == user_id
+        ).first()
+        
+        if not persona:
+            raise HTTPException(status_code=404, detail="Persona not found")
+        
+        # Soft delete persona and platform adaptations
+        persona.is_active = False
+        persona.updated_at = datetime.utcnow()
+        
+        platform_personas = session.query(PlatformPersona).filter(
+            PlatformPersona.writing_persona_id == persona_id
+        ).all()
+        
+        for pp in platform_personas:
+            pp.is_active = False
+            pp.updated_at = datetime.utcnow()
+        
+        session.commit()
+        session.close()
+        
+        return {
+            "message": "Persona deleted successfully",
+            "persona_id": persona_id
+        }
+        
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error deleting persona: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to delete persona: {str(e)}")
+
+async def validate_persona_generation_readiness(user_id: int):
+    """Check if user has sufficient onboarding data for persona generation."""
+    try:
+        persona_service = get_persona_service()
+        
+        # Get onboarding data
+        onboarding_data = persona_service._collect_onboarding_data(user_id)
+        
+        if not onboarding_data:
+            return {
+                "ready": False,
+                "message": "No onboarding data found. Please complete onboarding first.",
+                "missing_steps": ["All onboarding steps"],
+                "data_sufficiency": 0.0
+            }
+        
+        data_sufficiency = persona_service._calculate_data_sufficiency(onboarding_data)
+        
+        missing_steps = []
+        if not onboarding_data.get("website_analysis"):
+            missing_steps.append("Website Analysis (Step 2)")
+        if not onboarding_data.get("research_preferences"):
+            missing_steps.append("Research Preferences (Step 3)")
+        
+        ready = data_sufficiency >= 50.0  # Require at least 50% data sufficiency
+        
+        return {
+            "ready": ready,
+            "message": "Ready for persona generation" if ready else "Insufficient data for reliable persona generation",
+            "missing_steps": missing_steps,
+            "data_sufficiency": data_sufficiency,
+            "recommendations": [
+                "Complete website analysis for better style detection",
+                "Provide research preferences for content type optimization"
+            ] if not ready else []
+        }
+        
+    except Exception as e:
+        logger.error(f"Error validating persona generation readiness: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to validate readiness: {str(e)}")
+
+async def generate_persona_preview(user_id: int):
+    """Generate a preview of what the persona would look like without saving."""
+    try:
+        persona_service = get_persona_service()
+        
+        # Get onboarding data
+        onboarding_data = persona_service._collect_onboarding_data(user_id)
+        
+        if not onboarding_data:
+            raise HTTPException(status_code=400, detail="No onboarding data available")
+        
+        # Generate core persona (without saving)
+        core_persona = persona_service._generate_core_persona(onboarding_data)
+        
+        if "error" in core_persona:
+            raise HTTPException(status_code=400, detail=core_persona["error"])
+        
+        # Generate sample platform adaptation (just one for preview)
+        sample_platform = "linkedin"
+        platform_preview = persona_service._generate_single_platform_persona(
+            core_persona, sample_platform, onboarding_data
+        )
+        
+        return {
+            "preview": {
+                "identity": core_persona.get("identity", {}),
+                "linguistic_fingerprint": core_persona.get("linguistic_fingerprint", {}),
+                "tonal_range": core_persona.get("tonal_range", {}),
+                "sample_platform": {
+                    "platform": sample_platform,
+                    "adaptation": platform_preview
+                }
+            },
+            "confidence_score": core_persona.get("confidence_score", 0.0),
+            "data_sufficiency": persona_service._calculate_data_sufficiency(onboarding_data)
+        }
+        
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error generating persona preview: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to generate preview: {str(e)}")
+
+async def get_supported_platforms():
+    """Get list of supported platforms for persona generation."""
+    return {
+        "platforms": [
+            {
+                "id": "twitter",
+                "name": "Twitter/X",
+                "description": "Microblogging platform optimized for short, engaging content",
+                "character_limit": 280,
+                "optimal_length": "120-150 characters"
+            },
+            {
+                "id": "linkedin",
+                "name": "LinkedIn",
+                "description": "Professional networking platform for thought leadership content",
+                "character_limit": 3000,
+                "optimal_length": "150-300 words"
+            },
+            {
+                "id": "instagram",
+                "name": "Instagram",
+                "description": "Visual-first platform with engaging captions",
+                "character_limit": 2200,
+                "optimal_length": "125-150 words"
+            },
+            {
+                "id": "facebook",
+                "name": "Facebook",
+                "description": "Social networking platform for community engagement",
+                "character_limit": 63206,
+                "optimal_length": "40-80 words"
+            },
+            {
+                "id": "blog",
+                "name": "Blog Posts",
+                "description": "Long-form content optimized for SEO and engagement",
+                "word_count": "800-2000 words",
+                "seo_optimized": True
+            },
+            {
+                "id": "medium",
+                "name": "Medium",
+                "description": "Publishing platform for storytelling and thought leadership",
+                "word_count": "1000-3000 words",
+                "storytelling_focus": True
+            },
+            {
+                "id": "substack",
+                "name": "Substack",
+                "description": "Newsletter platform for building subscriber relationships",
+                "format": "email newsletter",
+                "subscription_focus": True
+            }
+        ]
+    }