feat: Auto-adapt content to platform limits when creating posts
- Add adapt_with_ai() method to PlatformAdapter that uses DeepSeek to condense content when it exceeds platform character limits - Add adapt_for_all_platforms_smart() for batch adaptation - Modify create_post endpoint to auto-generate content_x, content_threads, content_instagram, content_facebook with adapted versions - Modify update_post to re-adapt content when main content changes - If content fits within limit, use as-is (no AI call) - If content exceeds limit, AI condenses while preserving message - Fallback to rule-based truncation if DeepSeek API unavailable Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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@@ -10,6 +10,7 @@ from pydantic import BaseModel
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from app.core.database import get_db
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from app.models.post import Post
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from app.services.ai.platform_adapter import platform_adapter
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router = APIRouter()
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@@ -122,7 +123,14 @@ async def get_post(post_id: int, db: Session = Depends(get_db)):
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@router.post("/", response_model=PostResponse)
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async def create_post(post_data: PostCreate, db: Session = Depends(get_db)):
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"""Crear un nuevo post."""
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"""Crear un nuevo post con auto-adaptación de contenido por plataforma."""
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# Adaptar contenido para cada plataforma
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adapted_content = await platform_adapter.adapt_for_all_platforms_smart(
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post_data.content,
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post_data.platforms
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)
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post = Post(
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content=post_data.content,
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content_type=post_data.content_type,
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@@ -131,7 +139,12 @@ async def create_post(post_data: PostCreate, db: Session = Depends(get_db)):
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image_url=post_data.image_url,
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approval_required=post_data.approval_required,
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hashtags=post_data.hashtags,
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status="pending_approval" if post_data.approval_required else "scheduled"
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status="pending_approval" if post_data.approval_required else "scheduled",
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# Contenido adaptado por plataforma
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content_x=adapted_content.get("x"),
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content_threads=adapted_content.get("threads"),
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content_instagram=adapted_content.get("instagram"),
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content_facebook=adapted_content.get("facebook"),
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)
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db.add(post)
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@@ -143,12 +156,30 @@ async def create_post(post_data: PostCreate, db: Session = Depends(get_db)):
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@router.put("/{post_id}")
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async def update_post(post_id: int, post_data: PostUpdate, db: Session = Depends(get_db)):
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"""Actualizar un post."""
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"""Actualizar un post con re-adaptación automática si cambia el contenido."""
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post = db.query(Post).filter(Post.id == post_id).first()
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if not post:
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raise HTTPException(status_code=404, detail="Post no encontrado")
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update_data = post_data.dict(exclude_unset=True)
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# Si cambia el contenido principal, re-adaptar para todas las plataformas
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if "content" in update_data:
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platforms = update_data.get("platforms", post.platforms)
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adapted_content = await platform_adapter.adapt_for_all_platforms_smart(
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update_data["content"],
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platforms
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)
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# Solo actualizar campos de plataforma si no vienen explícitos en la request
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if "content_x" not in update_data and "x" in platforms:
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update_data["content_x"] = adapted_content.get("x")
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if "content_threads" not in update_data and "threads" in platforms:
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update_data["content_threads"] = adapted_content.get("threads")
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if "content_instagram" not in update_data and "instagram" in platforms:
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update_data["content_instagram"] = adapted_content.get("instagram")
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if "content_facebook" not in update_data and "facebook" in platforms:
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update_data["content_facebook"] = adapted_content.get("facebook")
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for field, value in update_data.items():
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setattr(post, field, value)
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@@ -369,6 +369,112 @@ Responde SOLO con el contenido adaptado, sin explicaciones."""
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return prompt
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# === Adaptación con IA ===
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async def adapt_with_ai(
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self,
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content: str,
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platform: str
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) -> AdaptedContent:
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"""
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Adaptar contenido usando IA si excede el límite.
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Si el contenido cabe en el límite, lo retorna tal cual.
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Si excede, usa DeepSeek para condensar manteniendo el mensaje.
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Args:
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content: Contenido a adaptar
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platform: Plataforma destino
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Returns:
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AdaptedContent con el contenido adaptado
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"""
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limits = self.get_limits(platform)
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max_chars = limits.get("max_characters", 2000)
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# Si cabe, solo aplicar formato básico
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if len(content) <= max_chars:
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return AdaptedContent(
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content=content,
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platform=platform,
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original_content=content,
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truncated=False,
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hashtags_adjusted=False,
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changes_made=[]
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)
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# Excede límite: usar IA para condensar
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from openai import OpenAI
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from app.core.config import settings
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if not settings.DEEPSEEK_API_KEY:
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# Fallback a adaptación por reglas si no hay API
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return self.adapt(content, platform)
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client = OpenAI(
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api_key=settings.DEEPSEEK_API_KEY,
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base_url=settings.DEEPSEEK_BASE_URL or "https://api.deepseek.com"
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)
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# Dejar margen de 10 chars para seguridad
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target_chars = max_chars - 10
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prompt = f"""Condensa este contenido a máximo {target_chars} caracteres para {platform}.
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CONTENIDO ORIGINAL:
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{content}
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REGLAS:
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- Máximo {target_chars} caracteres (incluyendo hashtags y espacios)
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- Mantén la esencia y mensaje principal
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- Conserva el call-to-action si existe
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- Incluye hashtags relevantes (máximo {limits.get('max_hashtags', 2)})
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- NO uses emojis a menos que estén en el original
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- Tono profesional
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Responde SOLO con el contenido adaptado, sin explicaciones."""
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response = client.chat.completions.create(
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model="deepseek-chat",
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7,
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max_tokens=500
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)
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adapted_content = response.choices[0].message.content.strip()
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return AdaptedContent(
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content=adapted_content,
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platform=platform,
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original_content=content,
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truncated=True,
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hashtags_adjusted=False,
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changes_made=[f"Contenido adaptado con IA: {len(content)} → {len(adapted_content)} caracteres"]
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)
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async def adapt_for_all_platforms_smart(
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self,
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content: str,
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platforms: List[str]
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) -> Dict[str, str]:
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"""
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Adaptar contenido para múltiples plataformas usando IA cuando sea necesario.
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Args:
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content: Contenido base
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platforms: Lista de plataformas
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Returns:
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Dict de plataforma -> contenido adaptado
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"""
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results = {}
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for platform in platforms:
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adapted = await self.adapt_with_ai(content, platform)
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results[platform] = adapted.content
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return results
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# Instancia global
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platform_adapter = PlatformAdapter()
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