f2b5dce63a
**Phase 1 — Agent Usage Sync to AgentHub Collector**
- Add agent_usage service: per-agent stats (messages, tokens, conversations, unique users, first/last used)
- Collector sync now includes usage data in payload; sync_agent accepts optional db session
- Celery beat task runs every 6h to sync all active agents with fresh usage stats
**Phase 2 — LibreCodeInterpreter Integration**
- Add code-interpreter, redis, minio services to docker-compose.prod.yml
- CodeInterpreterTool (BaseTool): sandboxed execution via /exec, 13 languages, Python session persistence via conversation_id
- ToolContext extended with conversation_id and agent_slug
- enable_code_interpreter boolean on Agent model (migration 027), tool seeded in tool_definitions (migration 026)
- Code interpreter auto-injected into agent tools when enabled
- Frontend: CodeExecutionResult component with terminal-style stdout/stderr/files rendering
**Phase 3 — Agent API Endpoints**
- GET /api/v1/agents/{slug}/analytics — per-agent usage stats + daily time series
- POST /api/v1/agents/{slug}/execute — synchronous programmatic agent execution (non-SSE)
- Sub-routes registered before /{slug} to avoid FastAPI route conflict
**Phase 4 — Fix Department & Region RAG Scoping**
- Department filter now OR-includes global (null department) docs, matching region filter behaviour
- retriever.search_documents/retrieve_and_prepare/query accept department_ids/region_codes lists
- MatchAny used for multi-value Qdrant filters; chat.py passes full arrays from knowledge_scope
- Admin PATCH /users/{id} now validates region_code against the regions table
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
80 lines
2.2 KiB
Python
80 lines
2.2 KiB
Python
"""
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Celery Application Configuration
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Broker: Redis
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Result backend: Redis
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Usage (inside container):
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celery -A celery_app worker --loglevel=info --queues=sharepoint,default
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celery -A celery_app beat --loglevel=info
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celery -A celery_app flower --port=5555
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"""
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from celery import Celery
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from celery.schedules import crontab
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from app.config import settings
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celery_app = Celery(
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"nexus",
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broker=settings.CELERY_BROKER_URL,
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backend=settings.CELERY_RESULT_BACKEND,
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include=[
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"app.tasks.sharepoint_sync",
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"app.tasks.knowledge_processing",
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"app.tasks.agent_sync",
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],
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)
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celery_app.conf.update(
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# Serialization
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task_serializer="json",
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result_serializer="json",
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accept_content=["json"],
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# Timezone
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timezone="UTC",
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enable_utc=True,
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# Task time limits
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task_time_limit=1800, # hard kill after 30 min
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task_soft_time_limit=1500, # SoftTimeLimitExceeded after 25 min
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# Concurrency (can be overridden by CLI --concurrency)
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worker_concurrency=settings.WORKERS_COUNT,
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# Task routing
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task_routes={
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"app.tasks.sharepoint_sync.*": {"queue": "sharepoint"},
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"app.tasks.knowledge_processing.*": {"queue": "default"},
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"app.tasks.agent_sync.*": {"queue": "default"},
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},
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# Result retention: keep results for 24 hours
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result_expires=86400,
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# Reliability
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task_acks_late=True,
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task_reject_on_worker_lost=True,
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worker_prefetch_multiplier=1,
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# Beat schedule
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beat_schedule={
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"renew-expiring-webhooks": {
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"task": "app.tasks.sharepoint_sync.renew_expiring_webhooks",
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"schedule": crontab(hour=3, minute=0),
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},
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"sync-sharepoint-sources": {
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"task": "app.tasks.sharepoint_sync.sync_all_active_sources",
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"schedule": crontab(minute=0), # hourly
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},
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"sync-agent-collector-usage": {
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"task": "app.tasks.agent_sync.sync_agents_usage",
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"schedule": crontab(minute=0, hour="*/6"), # every 6 hours
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},
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},
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)
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@celery_app.task(name="celery_healthcheck", bind=True)
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def celery_healthcheck(self):
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"""Simple task used to verify worker is alive."""
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return {"status": "ok", "worker": self.request.hostname}
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