auth

app.py

@@ -109,6 +109,19 @@ def is_authenticated():
 
 # Function to retrieve answer using the RAG system
 @spaces.GPU(duration=60)
+def test_rag(query):
+    books_retriever = books_db_client_retriever.run(query)
+    
+    # Extract the relevant answer using regex
+    corrected_text_match = re.search(r"Helpful Answer:(.*)", books_retriever, re.DOTALL)
+    
+    if corrected_text_match:
+        corrected_text_books = corrected_text_match.group(1).strip()
+    else:
+        corrected_text_books = "No helpful answer found."
+    
+    return corrected_text_books
+    
 # Gradio app with OAuth integration
 def chat_interface():
     global access_token
@@ -117,19 +130,6 @@ def chat_interface():
     if not is_authenticated():
         auth_url = get_auth_url()
         return gr.Markdown(f"Please [log in]({auth_url}) to use the chatbot.")
-
-    def test_rag(query):
-        books_retriever = books_db_client_retriever.run(query)
-        
-        # Extract the relevant answer using regex
-        corrected_text_match = re.search(r"Helpful Answer:(.*)", books_retriever, re.DOTALL)
-        
-        if corrected_text_match:
-            corrected_text_books = corrected_text_match.group(1).strip()
-        else:
-            corrected_text_books = "No helpful answer found."
-        
-        return corrected_text_books
     
     # Gradio chatbot interface
     def chat(query, history=None):
@@ -137,7 +137,7 @@ def chat_interface():
             history = []
         if query:
             # Chatbot logic here
-            answer = "This is a dummy answer."
+            answer = test_rag(query)
             history.append((query, answer))
         return history, ""  # Clear input after submission