73d8aa8c7a
Master deck parsing with 20+ layouts requires ~44 LLM calls. At 60s per call with gemini-3.1-pro = 44-60 minutes total. Previous 30 min timeout caused failures at layout 19/22. Co-Authored-By: Claude Sonnet 4.5 (1M context) <noreply@anthropic.com>
36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
"""ARQ worker entry point.
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Run with: python -m arq workers.main.WorkerSettings
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"""
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import os
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from arq.connections import RedisSettings
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from arq.cron import cron
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# Import all SQL models so SQLAlchemy can resolve FK references
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from models.sql.user import UserModel # noqa: F401
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from models.sql.client import ClientModel # noqa: F401
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from models.sql.team import TeamModel # noqa: F401
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from models.sql.presentation import PresentationModel # noqa: F401
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from workers.master_deck_worker import parse_master_deck_task
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from workers.presentation_worker import generate_presentation_task
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from workers.retention_worker import retention_cleanup_task, retention_purge_task
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def _get_redis_settings() -> RedisSettings:
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url = os.environ.get("REDIS_URL", "redis://localhost:6379/0")
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return RedisSettings.from_dsn(url)
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class WorkerSettings:
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redis_settings = _get_redis_settings()
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functions = [generate_presentation_task, parse_master_deck_task]
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cron_jobs = [
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cron(retention_cleanup_task, hour=2, minute=0), # Daily at 2:00 AM
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cron(retention_purge_task, weekday=0, hour=3, minute=0), # Weekly Monday 3:00 AM
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]
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max_jobs = 5
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job_timeout = 5400 # 90 minutes (master deck with 20+ layouts = ~44 LLM calls)
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max_tries = 3
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health_check_interval = 30
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