feat: generación automática de preguntas diarias
- Script generate_daily_questions.py: genera 5 preguntas por categoría/dificultad - Usa Claude API para generar preguntas en español - Cron job configurado para medianoche (0 0 * * *) - 14 categorías × 5 dificultades × 5 preguntas = 350 preguntas/día - Evita duplicados verificando preguntas existentes fix: rotación de jugadores en robo fallido/pasado Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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256
backend/scripts/generate_daily_questions.py
Executable file
256
backend/scripts/generate_daily_questions.py
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#!/usr/bin/env python3
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"""
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Script para generar preguntas diarias automáticamente usando Claude API.
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Ejecutar con cron a medianoche para generar preguntas del día siguiente.
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"""
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import asyncio
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import sys
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import os
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from datetime import date, timedelta
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from typing import List, Dict
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import json
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# Add backend to path
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sys.path.insert(0, '/root/Trivy/backend')
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import anthropic
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from sqlalchemy import select
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from app.models.base import get_async_session
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from app.models.category import Category
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from app.models.question import Question
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# Configuration
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QUESTIONS_PER_DIFFICULTY = 5 # 5 preguntas por cada dificultad
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DIFFICULTIES = [1, 2, 3, 4, 5]
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POINTS_MAP = {1: 100, 2: 200, 3: 300, 4: 400, 5: 500}
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TIME_MAP = {1: 30, 2: 30, 3: 25, 4: 20, 5: 15}
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# Get API key from environment
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ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
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def get_difficulty_description(difficulty: int) -> str:
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"""Get description for difficulty level."""
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descriptions = {
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1: "muy fácil, conocimiento básico que casi todos saben",
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2: "fácil, conocimiento común para fans casuales",
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3: "moderada, requiere conocimiento intermedio del tema",
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4: "difícil, requiere conocimiento profundo del tema",
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5: "muy difícil, solo expertos o super fans sabrían la respuesta"
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}
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return descriptions.get(difficulty, "moderada")
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async def generate_questions_for_category(
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client: anthropic.Anthropic,
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category: Dict,
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difficulty: int,
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target_date: date,
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existing_questions: List[str]
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) -> List[Dict]:
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"""Generate questions for a specific category and difficulty using Claude."""
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difficulty_desc = get_difficulty_description(difficulty)
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points = POINTS_MAP[difficulty]
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time_seconds = TIME_MAP[difficulty]
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# Build prompt
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prompt = f"""Genera exactamente {QUESTIONS_PER_DIFFICULTY} preguntas de trivia sobre "{category['name']}" con dificultad {difficulty} ({difficulty_desc}).
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REGLAS IMPORTANTES:
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1. Las preguntas deben ser en español
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2. Las respuestas deben ser cortas (1-4 palabras idealmente)
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3. Incluye respuestas alternativas válidas cuando aplique
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4. NO repitas estas preguntas existentes: {json.dumps(existing_questions[:20], ensure_ascii=False) if existing_questions else "ninguna"}
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5. Cada pregunta debe tener un dato curioso relacionado
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6. Las preguntas deben ser verificables y tener una respuesta objetiva correcta
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Responde SOLO con un JSON array válido con esta estructura exacta:
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[
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{{
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"question_text": "¿Pregunta aquí?",
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"correct_answer": "Respuesta correcta",
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"alt_answers": ["alternativa1", "alternativa2"],
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"fun_fact": "Dato curioso relacionado con la pregunta"
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}}
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]
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Genera exactamente {QUESTIONS_PER_DIFFICULTY} preguntas diferentes y variadas sobre {category['name']}."""
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try:
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response = client.messages.create(
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model="claude-sonnet-4-20250514",
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max_tokens=2000,
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messages=[{"role": "user", "content": prompt}]
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)
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# Extract JSON from response
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response_text = response.content[0].text.strip()
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# Try to find JSON array in response
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start_idx = response_text.find('[')
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end_idx = response_text.rfind(']') + 1
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if start_idx == -1 or end_idx == 0:
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print(f" ERROR: No se encontró JSON válido para {category['name']} dificultad {difficulty}")
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return []
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json_str = response_text[start_idx:end_idx]
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questions_data = json.loads(json_str)
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# Format questions for database
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formatted_questions = []
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for q in questions_data:
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formatted_questions.append({
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"category_id": category['id'],
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"question_text": q["question_text"],
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"correct_answer": q["correct_answer"],
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"alt_answers": q.get("alt_answers", []),
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"difficulty": difficulty,
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"points": points,
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"time_seconds": time_seconds,
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"date_active": target_date,
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"status": "approved",
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"fun_fact": q.get("fun_fact", "")
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})
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return formatted_questions
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except json.JSONDecodeError as e:
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print(f" ERROR JSON para {category['name']} dificultad {difficulty}: {e}")
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return []
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except Exception as e:
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print(f" ERROR generando para {category['name']} dificultad {difficulty}: {e}")
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return []
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async def get_existing_questions(db, category_id: int) -> List[str]:
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"""Get existing question texts to avoid duplicates."""
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result = await db.execute(
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select(Question.question_text).where(Question.category_id == category_id)
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)
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return [row[0] for row in result.fetchall()]
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async def generate_daily_questions(target_date: date = None):
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"""Main function to generate all daily questions."""
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if not ANTHROPIC_API_KEY:
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print("ERROR: ANTHROPIC_API_KEY no está configurada")
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sys.exit(1)
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if target_date is None:
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# Generate for tomorrow by default
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target_date = date.today() + timedelta(days=1)
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print(f"=== Generando preguntas para {target_date} ===")
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client = anthropic.Anthropic(api_key=ANTHROPIC_API_KEY)
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AsyncSessionLocal = get_async_session()
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async with AsyncSessionLocal() as db:
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# Get all categories
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result = await db.execute(select(Category))
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categories = result.scalars().all()
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if not categories:
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print("ERROR: No hay categorías en la base de datos")
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return
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print(f"Categorías encontradas: {len(categories)}")
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total_generated = 0
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for category in categories:
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cat_dict = {"id": category.id, "name": category.name}
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print(f"\n📁 Categoría: {category.name}")
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# Get existing questions to avoid duplicates
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existing = await get_existing_questions(db, category.id)
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for difficulty in DIFFICULTIES:
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print(f" Dificultad {difficulty}...", end=" ", flush=True)
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questions = await generate_questions_for_category(
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client, cat_dict, difficulty, target_date, existing
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)
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if questions:
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# Insert into database
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for q_data in questions:
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question = Question(**q_data)
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db.add(question)
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existing.append(q_data["question_text"])
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print(f"✓ {len(questions)} preguntas")
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total_generated += len(questions)
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else:
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print("✗ Error")
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# Small delay to avoid rate limiting
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await asyncio.sleep(1)
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await db.commit()
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print(f"\n=== COMPLETADO ===")
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print(f"Total de preguntas generadas: {total_generated}")
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print(f"Fecha activa: {target_date}")
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async def check_existing_questions(target_date: date = None):
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"""Check if questions already exist for target date."""
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if target_date is None:
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target_date = date.today() + timedelta(days=1)
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AsyncSessionLocal = get_async_session()
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async with AsyncSessionLocal() as db:
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result = await db.execute(
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select(Question).where(Question.date_active == target_date)
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)
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existing = result.scalars().all()
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return len(existing)
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(description="Generar preguntas diarias para Trivy")
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parser.add_argument(
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"--date",
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type=str,
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help="Fecha objetivo (YYYY-MM-DD). Default: mañana"
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)
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parser.add_argument(
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"--force",
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action="store_true",
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help="Generar aunque ya existan preguntas para esa fecha"
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)
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parser.add_argument(
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"--check",
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action="store_true",
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help="Solo verificar si existen preguntas"
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)
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args = parser.parse_args()
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target_date = None
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if args.date:
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target_date = date.fromisoformat(args.date)
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if args.check:
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count = asyncio.run(check_existing_questions(target_date))
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check_date = target_date or (date.today() + timedelta(days=1))
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print(f"Preguntas para {check_date}: {count}")
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sys.exit(0)
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# Check if questions already exist
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if not args.force:
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count = asyncio.run(check_existing_questions(target_date))
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if count > 0:
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check_date = target_date or (date.today() + timedelta(days=1))
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print(f"Ya existen {count} preguntas para {check_date}")
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print("Usa --force para regenerar")
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sys.exit(0)
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asyncio.run(generate_daily_questions(target_date))
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