Update app.py

app.py

@@ -50,6 +50,7 @@ st.markdown(
     unsafe_allow_html=True,
 )
 
+
 device = torch.device("cpu")
 
 testing_df = pd.read_csv("testing_df.csv")
@@ -57,12 +58,6 @@ model = CLIPModel().to(device)
 model.load_state_dict(torch.load("weights.pt", map_location=torch.device('cpu')))
 text_embeddings = torch.load('saved_text_embeddings.pt', map_location=device)
 
-# Initialize the session state
-if 'user_input' not in st.session_state:
-    st.session_state.user_input = ''
-if 'chat_history' not in st.session_state:
-    st.session_state.chat_history = []
-
 def show_predicted_caption(image):
     matches = predict_caption(
         image, model, text_embeddings, testing_df["caption"]
@@ -104,7 +99,6 @@ def download_link(content, filename, link_text):
     href = f'<a href="data:application/octet-stream;base64,{b64}" download="{filename}">{link_text}</a>'
     return href
 
-
 st.title("RadiXGPT: An Evolution of machine doctors towards Radiology")
 
 # Collect user's personal information
@@ -140,28 +134,26 @@ if uploaded_file is not None:
                 st.write(radiology_report_with_personal_info)
                 st.markdown(download_link(save_as_docx(radiology_report_with_personal_info, "radiology_report.docx"), "radiology_report.docx", "Download Report as DOCX"), unsafe_allow_html=True)
 
-            # Modify the 1-to-1 consultation section
+            # Add the chatbot functionality
             st.header("1-to-1 Consultation")
             st.write("Ask any questions you have about the radiology report:")
-            
-            st.session_state.user_input = st.text_input("Enter your question:", value=st.session_state.user_input)
-            
-            if st.session_state.user_input:
-                st.session_state.chat_history.append({"user": st.session_state.user_input})
-            
-                if st.session_state.user_input.lower() == "thank you":
+
+            user_input = st.text_input("Enter your question:")
+            chat_history = []
+
+            if user_input:
+                chat_history.append({"user": user_input})
+
+                if user_input.lower() == "thank you":
                     st.write("Bot: You're welcome! If you have any more questions, feel free to ask.")
-                    st.session_state.user_input = ''
-                    st.session_state.chat_history = []
                 else:
                     # Generate the answer to the user's question
-                    prompt = f"Answer to the user's question based on the generated radiology report: {st.session_state.user_input}"
-                    for history_item in st.session_state.chat_history:
+                    prompt = f"Answer to the user's question based on the generated radiology report: {user_input}"
+                    for history_item in chat_history:
                         prompt += f"\nUser: {history_item['user']}"
                         if 'bot' in history_item:
                             prompt += f"\nBot: {history_item['bot']}"
-            
+
                     answer = chatbot_response(prompt)
-                    st.session_state.chat_history[-1]["bot"] = answer
-                    st.write(f"Bot: {answer}")
-                    st.session_state.user_input = ''
+                    chat_history[-1]["bot"] = answer
+                    st.write(f"Bot: {answer}")