add extra import handling

multi_agent_chatbot.py

@@ -8,8 +8,6 @@ This system implements a 3-agent architecture:
 
 Each agent has specialized prompts and responsibilities.
 """
-
-import os
 import json
 import time
 import logging
@@ -19,7 +17,6 @@ from dataclasses import dataclass
 from typing import Dict, List, Any, Optional, TypedDict
 
 
-import re
 from langchain_core.tools import tool
 from langgraph.graph import StateGraph, END
 from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
@@ -110,15 +107,31 @@ class MultiAgentRAGChatbot:
         
         # Initialize pipeline manager early to load models
         logger.info("🔄 Initializing pipeline manager and loading models...")
-        self.pipeline_manager = PipelineManager(self.config)
-        logger.info("✅ Pipeline manager initialized and models loaded")
+        try:
+            self.pipeline_manager = PipelineManager(self.config)
+            logger.info("✅ Pipeline manager initialized and models loaded")
+        except Exception as e:
+            logger.error(f"❌ Failed to initialize pipeline manager: {e}")
+            import traceback
+            traceback.print_exc()
+            raise RuntimeError(f"Pipeline manager initialization failed: {e}")
         
         # Connect to vector store
         logger.info("🔄 Connecting to vector store...")
-        if not self.pipeline_manager.connect_vectorstore():
-            logger.error("❌ Failed to connect to vector store")
-            raise RuntimeError("Vector store connection failed")
-        logger.info("✅ Vector store connected successfully")
+        try:
+            if not self.pipeline_manager.connect_vectorstore():
+                logger.error("❌ Failed to connect to vector store")
+                logger.error("💡 Check that QDRANT_API_KEY environment variable is set")
+                logger.error("💡 Check that Qdrant URL and collection name are correct in config")
+                raise RuntimeError("Vector store connection failed")
+            logger.info("✅ Vector store connected successfully")
+        except RuntimeError:
+            raise  # Re-raise RuntimeError as-is
+        except Exception as e:
+            logger.error(f"❌ Error during vector store connection: {e}")
+            import traceback
+            traceback.print_exc()
+            raise RuntimeError(f"Vector store connection failed: {e}")
         
         # Load dynamic data
         self._load_dynamic_data()