remove legacy imports

src/pipeline.py

@@ -118,8 +118,23 @@ class PipelineManager:
         try:
             # Load config if not provided
             if not self.config:
-                from auditqa.config.loader import load_config
-                self.config = load_config()
+                try:
+                    from src.config.loader import load_config
+                    self.config = load_config()
+                except ImportError:
+                    # Try alternate import path
+                    from src.config.loader import load_config
+                    self.config = load_config()
+            
+            # Validate config structure
+            if not isinstance(self.config, dict):
+                raise ValueError(f"Config must be a dict, got {type(self.config)}")
+            
+            # Ensure retriever config exists
+            if 'retriever' not in self.config:
+                self.config['retriever'] = {}
+            if 'model' not in self.config['retriever']:
+                raise ValueError("Config must have 'retriever.model' specified")
             
             # Auto-infer embedding model from collection name if not "docling"
             collection_name = self.config.get('qdrant', {}).get('collection_name', 'docling')
@@ -138,7 +153,16 @@ class PipelineManager:
                     if 'vectorstore' in self.config:
                         self.config['vectorstore']['embedding_model'] = inferred_model
 
-            self.vectorstore_manager = VectorStoreManager(self.config)
+            # Initialize vectorstore manager - this might fail if model loading fails
+            try:
+                self.vectorstore_manager = VectorStoreManager(self.config)
+                print("✅ VectorStoreManager initialized successfully")
+            except Exception as vs_error:
+                print(f"❌ Error initializing VectorStoreManager: {vs_error}")
+                import traceback
+                traceback.print_exc()
+                self.vectorstore_manager = None
+                raise  # Re-raise to be caught by outer try-except
 
             self.llm_manager = LLMRegistry()
             
@@ -151,7 +175,7 @@ class PipelineManager:
             except Exception as e:
                 try:
                     # Try direct instantiation with config
-                    from auditqa.llm.adapters import get_llm_client
+                    from src.llm.adapters import get_llm_client
                     self.llm_client = get_llm_client("openai", self.config)
                     print("✅ LLM CLIENT: Initialized using direct get_llm_client function with config")
                 except Exception as e2:
@@ -176,19 +200,28 @@ class PipelineManager:
                         self.llm_client = None
             
             # Load system prompt
-            from auditqa.llm.templates import DEFAULT_AUDIT_SYSTEM_PROMPT
+            from src.llm.templates import DEFAULT_AUDIT_SYSTEM_PROMPT
             self.system_prompt = DEFAULT_AUDIT_SYSTEM_PROMPT
             
             # Initialize report service
             try:
-                from auditqa.reporting.service import ReportService
+                try:
+                    from src.reporting.service import ReportService
+                except ImportError:
+                    from src.reporting.service import ReportService
                 self.report_service = ReportService()
             except Exception as e:
                 print(f"Warning: Could not initialize report service: {e}")
                 self.report_service = None
             
         except Exception as e:
-            print(f"Warning: Error initializing components: {e}")
+            print(f"❌ Error initializing components: {e}")
+            import traceback
+            traceback.print_exc()
+            # Don't set vectorstore_manager to None if it was already set
+            if not hasattr(self, 'vectorstore_manager') or self.vectorstore_manager is None:
+                self.vectorstore_manager = None
+            raise  # Re-raise to allow caller to handle
     
     def test_retrieval(
         self,
@@ -293,6 +326,21 @@ class PipelineManager:
         Returns:
             True if successful, False otherwise
         """
+        # Check if vectorstore_manager is initialized
+        if self.vectorstore_manager is None:
+            print("❌ Vector store manager is not initialized")
+            print("🔄 Attempting to initialize vector store manager...")
+            try:
+                self._initialize_components()
+                if self.vectorstore_manager is None:
+                    print("❌ Failed to initialize vector store manager")
+                    return False
+            except Exception as init_error:
+                print(f"❌ Error initializing vector store manager: {init_error}")
+                import traceback
+                traceback.print_exc()
+                return False
+        
         try:
             vectorstore = self.vectorstore_manager.connect_to_existing(force_recreate=force_recreate)
             if vectorstore:
@@ -304,6 +352,8 @@ class PipelineManager:
         except Exception as e:
             print(f"❌ Error connecting to vector store: {e}")
             log_error(e, {"component": "vectorstore_connection"})
+            import traceback
+            traceback.print_exc()
             
             # If it's a dimension mismatch error, try with force_recreate
             if "dimensions" in str(e).lower() and not force_recreate:
@@ -492,7 +542,7 @@ Answer:"""
                 print(f"🤖 AUTO-INFERRING FILTERS: No explicit filters provided, analyzing query...")
                 try:
                     # Import get_available_metadata here to avoid circular imports
-                    from auditqa.retrieval.filter import get_available_metadata, infer_filters_from_query
+                    from src.retrieval.filter import get_available_metadata, infer_filters_from_query
                     
                     # Get available metadata
                     available_metadata = get_available_metadata(self.vectorstore_manager.get_vectorstore())