Update app.py

app.py

@@ -6,6 +6,7 @@ from streamlit_extras.add_vertical_space import add_vertical_space
 from streamlit_mic_recorder import speech_to_text
 from model_pipeline import ModelPipeLine
 from q_learning_chatbot import QLearningChatbot
+from retriever import create_vectorstore
 
 from gtts import gTTS
 from io import BytesIO
@@ -101,6 +102,17 @@ def get_text():
 def generate_response(prompt):
     response = mdl.call_conversational_rag(prompt,final_chain)
     return response['answer']
+        
+    
+def get_response(self, user_query):
+        db=self.create_vectorstore(documents)
+        docs = db.similarity_search(user_query)
+        most_similar_question = docs[0].page_content.split("\n")[0]  # Extract the first question
+        if user_query==most_similar_question:
+          most_similar_question=docs[1].page_content.split("\n")[0]
+
+        print(most_similar_question)
+        return most_similar_question   
     
 ## Applying the user input box        
 with input_container:
@@ -131,7 +143,7 @@ with input_container:
                 # Retrieve question
                 if user_sentiment in ["Negative", "Moderately Negative", "Neutral"]:
                     question = retriever.get_response(
-                        user_message, predicted_mental_category
+                        user_message
                     )
                     st.session_state.asked_questions.append(question)
                     show_question = True
@@ -195,7 +207,7 @@ with input_container:
                 # Retrieve question
                 if user_sentiment in ["Negative", "Moderately Negative", "Neutral"]:
                     question = retriever.get_response(
-                        user_message, predicted_mental_category
+                        user_message
                     )
                     st.session_state.asked_questions.append(question)
                     show_question = True