Consultoría AS
11b0ba46fa
Major improvements to AI content generation: ## New Components (app/services/ai/) - PromptLibrary: YAML-based prompt templates with inheritance - ContextEngine: Anti-repetition and best performers tracking - ContentGeneratorV2: Enhanced generation with dynamic parameters - PlatformAdapter: Platform-specific content adaptation - ContentValidator: AI-powered quality scoring (0-100) ## Prompt Library (app/prompts/) - 3 personalities: default, educational, promotional - 5 templates: tip_tech, product_post, service_post, thread, response - 4 platform configs: x, threads, instagram, facebook - Few-shot examples by category: ia, productividad, seguridad ## Database Changes - New table: content_memory (tracks generated content) - New columns in posts: quality_score, score_breakdown, generation_attempts ## New API Endpoints (/api/v2/generate/) - POST /generate - Generation with quality check - POST /generate/batch - Batch generation - POST /quality/evaluate - Evaluate content quality - GET /templates, /personalities, /platforms - List configs ## Celery Tasks - update_engagement_scores (every 6h) - cleanup_old_memory (monthly) - refresh_best_posts_yaml (weekly) ## Tests - Comprehensive tests for all AI engine components Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
91 lines
2.4 KiB
Python
91 lines
2.4 KiB
Python
"""
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Alembic environment configuration.
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"""
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from logging.config import fileConfig
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from sqlalchemy import engine_from_config
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from sqlalchemy import pool
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from alembic import context
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# Import models and config
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from app.core.config import settings
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from app.core.database import Base
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# Import all models for autogenerate support
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from app.models import (
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User, Product, Service, TipTemplate,
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Post, ContentCalendar, ImageTemplate, Interaction,
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PostMetrics, AnalyticsReport, Lead, OdooSyncLog,
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ABTest, ABTestVariant, RecycledPost, ThreadSeries, ThreadPost,
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ContentMemory
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)
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# this is the Alembic Config object
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config = context.config
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# Override sqlalchemy.url with our settings
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config.set_main_option("sqlalchemy.url", settings.DATABASE_URL)
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# Interpret the config file for Python logging.
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if config.config_file_name is not None:
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fileConfig(config.config_file_name)
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# add your model's MetaData object here for 'autogenerate' support
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target_metadata = Base.metadata
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def run_migrations_offline() -> None:
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"""Run migrations in 'offline' mode.
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This configures the context with just a URL
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and not an Engine, though an Engine is acceptable
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here as well. By skipping the Engine creation
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we don't even need a DBAPI to be available.
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Calls to context.execute() here emit the given string to the
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script output.
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"""
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url = config.get_main_option("sqlalchemy.url")
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context.configure(
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url=url,
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target_metadata=target_metadata,
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literal_binds=True,
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dialect_opts={"paramstyle": "named"},
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)
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with context.begin_transaction():
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context.run_migrations()
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def run_migrations_online() -> None:
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"""Run migrations in 'online' mode.
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In this scenario we need to create an Engine
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and associate a connection with the context.
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"""
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connectable = engine_from_config(
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config.get_section(config.config_ini_section, {}),
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prefix="sqlalchemy.",
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poolclass=pool.NullPool,
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)
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with connectable.connect() as connection:
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context.configure(
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connection=connection,
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target_metadata=target_metadata
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)
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with context.begin_transaction():
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context.run_migrations()
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if context.is_offline_mode():
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run_migrations_offline()
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else:
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run_migrations_online()
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