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questionnaire_app.py

@@ -2,12 +2,19 @@ import streamlit as st
 import os
 import signal
 from pathlib import Path
-from questionnaire_rag import PollQuestionnaireRAG
 
 # Load environment variables from .env file as fallback
 from dotenv import load_dotenv
 load_dotenv()
 
+# Import RAG system with error handling
+try:
+    from questionnaire_rag import PollQuestionnaireRAG
+except ImportError as e:
+    st.error(f"Failed to import RAG system: {e}")
+    st.error("Please ensure all dependencies are installed.")
+    st.stop()
+
 def get_config_value(key: str, default: str = None) -> str: # type: ignore
     """
     Get configuration value with multiple fallback options:

questionnaire_rag.py

@@ -17,12 +17,6 @@ try:
     load_dotenv()
 except ImportError:
     pass
-openai_api_key = os.getenv("OPENAI_API_KEY")
-if openai_api_key is None:
-    raise ValueError("OPENAI_API_KEY environment variable not set")
-pinecone_api_key = os.getenv("PINECONE_API_KEY")
-if pinecone_api_key is None:
-    raise ValueError("PINECONE_API_KEY environment variable not set")
 
 class PollQuestionnaireRAG:
     """Query pre-built vector store for poll questionnaires"""
@@ -31,8 +25,14 @@ class PollQuestionnaireRAG:
         self.openai_api_key = openai_api_key
         self.persist_directory = persist_directory
         self.verbose = verbose
-        self.embeddings = OpenAIEmbeddings(model=os.getenv("EMBEDDING_MODEL", "text-embedding-3-small"))
+        
+        # Get Pinecone API key from environment (set by the app)
+        pinecone_api_key = os.getenv("PINECONE_API_KEY")
+        if pinecone_api_key is None:
+            raise ValueError("PINECONE_API_KEY environment variable not set")
         self.pinecone_api_key = pinecone_api_key
+        
+        self.embeddings = OpenAIEmbeddings(model=os.getenv("EMBEDDING_MODEL", "text-embedding-3-small"))
 
         chat_model = os.getenv("OPENAI_MODEL", "gpt-4o")
         self.llm = ChatOpenAI(model=chat_model, temperature=0)