Make SIF fail fast and add low-cost remote LLM fallback

backend/services/intelligence/txtai_service.py

@@ -54,6 +54,7 @@ class TxtaiIntelligenceService:
         self.cache_manager = semantic_cache_manager if enable_caching else None
         self._backend = "faiss"  # Default backend
         self._disable_ann_queries = False  # Set when FAISS nprobe incompatibility is detected
+        self.fail_fast = str(os.getenv("SIF_FAIL_FAST", "true")).lower() in {"1", "true", "yes", "on"}
         
         # Mark as initialized for singleton pattern
         self._singleton_initialized = True
@@ -226,6 +227,7 @@ class TxtaiIntelligenceService:
         Args:
             items: List of (id, text, metadata) tuples.
         """
+<<<<<<< HEAD
         # Check if already initialized
         if not self._initialized and not self._initialization_in_progress:
             # Trigger initialization in background (non-blocking)
@@ -241,6 +243,14 @@ class TxtaiIntelligenceService:
         
         if not self.embeddings:
             logger.error(f"Cannot index content - embeddings not available for user {self.user_id}")
+=======
+        self._ensure_initialized()
+        if not self._initialized or not self.embeddings:
+            message = f"Cannot index content - service not initialized for user {self.user_id}"
+            logger.error(message)
+            if self.fail_fast:
+                raise RuntimeError(message)
+>>>>>>> 8b0547c (Make SIF fail fast and add low-cost remote LLM fallback)
             return
 
         try:
@@ -287,7 +297,10 @@ class TxtaiIntelligenceService:
         """Perform semantic search with intelligent caching."""
         self._ensure_initialized()
         if not self._initialized or not self.embeddings:
-            logger.error(f"Cannot perform search - service not initialized for user {self.user_id}")
+            message = f"Cannot perform search - service not initialized for user {self.user_id}"
+            logger.error(message)
+            if self.fail_fast:
+                raise RuntimeError(message)
             return []
 
         try:
@@ -321,6 +334,8 @@ class TxtaiIntelligenceService:
             return results
         except Exception as e:
             logger.error(f"Search failed for user {self.user_id}: {e}")
+            if self.fail_fast:
+                raise
             logger.error(f"Query: '{query}'")
             logger.error(f"Full traceback: {traceback.format_exc()}")
             return []