Refactor user data handling and enhance chat functionality

- Removed deprecated user_info files and paths from configuration.
- Added user soil data integration in chat context to improve response accuracy.
- Updated build_rag_context and chat_rag_stream functions to include sensor_uuid for user-specific data retrieval.
- Enhanced load_sources function to load user data from the database.
- Implemented filtering in search_with_query and QdrantVectorStore to isolate user data based on sensor_uuid.
- Introduced Celery Beat schedule for periodic user data ingestion.

config/settings.py

@@ -107,3 +107,11 @@ CELERY_BROKER_URL = os.environ.get("CELERY_BROKER_URL", "redis://localhost:6379/
 CELERY_RESULT_BACKEND = os.environ.get("CELERY_RESULT_BACKEND", "redis://localhost:6379/0")
 CELERY_ACCEPT_CONTENT = ["json"]
 CELERY_TASK_SERIALIZER = "json"
+
+# Celery Beat — embed دیتای کاربران هر ۶ ساعت
+CELERY_BEAT_SCHEDULE = {
+    "rag-ingest-periodic": {
+        "task": "rag.tasks.rag_ingest_task",
+        "schedule": 6 * 60 * 60,  # ۶ ساعت
+    },
+}