Update app.py

app.py

@@ -6,7 +6,6 @@ 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 model_pipeline.ModelPipeLine import rag_retriever
 
 from gtts import gTTS
 from io import BytesIO
@@ -18,6 +17,9 @@ st.sidebar.image(image_path, use_column_width=True)
 st.title('PeacePal 🌱')
 
 mdl = ModelPipeLine()
+# Now you can access the retriever attribute of the ModelPipeLine instance
+retriever = mdl.retriever
+
 final_chain = mdl.create_final_chain()
 
 # Define states and actions
@@ -128,7 +130,7 @@ with input_container:
     
                 # Retrieve question
                 if user_sentiment in ["Negative", "Moderately Negative", "Neutral"]:
-                    question = rag_retriever.get_response(
+                    question = retriever.get_response(
                         user_message, predicted_mental_category
                     )
                     st.session_state.asked_questions.append(question)
@@ -192,7 +194,7 @@ with input_container:
     
                 # Retrieve question
                 if user_sentiment in ["Negative", "Moderately Negative", "Neutral"]:
-                    question = rag_retriever.get_response(
+                    question = retriever.get_response(
                         user_message, predicted_mental_category
                     )
                     st.session_state.asked_questions.append(question)