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https://github.com/furyhawk/agent_alpha.git
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furyhawk
bb4b614711
- Added `vectorstore.py` for managing vector storage operations using Milvus. - Introduced `rag_document.py` for handling RAG document lifecycle, including ingestion and status updates. - Created `rag_status.py` for streaming RAG ingestion status via Redis pub/sub. - Developed `rag_sync.py` for managing synchronization operations and logs. - Implemented `sync_source.py` for managing sync source configurations and triggering syncs. - Established a lightweight task dispatcher in `dispatcher.py` for background task execution. - Registered task functions for RAG ingestion and sync operations in `rag_tasks.py`. - Configured task dispatcher settings in `arq_settings.py`. - Added necessary database models and schemas for RAG document and sync operations.
27 lines
738 B
Python
27 lines
738 B
Python
"""Task dispatcher configuration.
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In the current implementation, tasks run in-process via
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:class:`backend.worker.dispatcher.TaskDispatcher`. For production
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deployments with multiple replicas, replace with a Redis-backed
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queue (ARQ, Taskiq, or Celery).
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To switch to ARQ in the future::
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pip install arq
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arq backend.worker.arq_settings.WorkerSettings
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"""
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from __future__ import annotations
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from backend.core.config import settings
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from backend.worker.tasks.rag_tasks import TASK_REGISTRY
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# List of registered task functions for ARQ/Taskiq configuration
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FUNCTIONS = list(TASK_REGISTRY.values())
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# Redis connection info (for future ARQ/Taskiq worker setup)
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REDIS_URL = settings.valkey_url
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__all__ = ["FUNCTIONS", "REDIS_URL"]
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