Update app.py

app.py

@@ -1,4 +1,5 @@
 import streamlit as st
+from streamlit.state import session_state
 import pickle
 import pandas as pd
 import torch
@@ -58,6 +59,14 @@ 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)
 
+# Add this function to initialize the session state
+def init_state():
+    if 'user_input' not in session_state:
+        session_state.user_input = ''
+    if 'chat_history' not in session_state:
+        session_state.chat_history = []
+
+
 def show_predicted_caption(image):
     matches = predict_caption(
         image, model, text_embeddings, testing_df["caption"]
@@ -99,6 +108,9 @@ def download_link(content, filename, link_text):
     href = f'<a href="data:application/octet-stream;base64,{b64}" download="{filename}">{link_text}</a>'
     return href
 
+# Initialize the session state
+init_state()
+
 st.title("RadiXGPT: An Evolution of machine doctors towards Radiology")
 
 # Collect user's personal information
@@ -134,26 +146,28 @@ 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)
 
-            # Add the chatbot functionality
+            # Modify the 1-to-1 consultation section
             st.header("1-to-1 Consultation")
             st.write("Ask any questions you have about the radiology report:")
-
-            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":
+            
+            session_state.user_input = st.text_input("Enter your question:", value=session_state.user_input)
+            
+            if session_state.user_input:
+                session_state.chat_history.append({"user": session_state.user_input})
+            
+                if session_state.user_input.lower() == "thank you":
                     st.write("Bot: You're welcome! If you have any more questions, feel free to ask.")
+                    session_state.user_input = ''
+                    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: {user_input}"
-                    for history_item in chat_history:
+                    prompt = f"Answer to the user's question based on the generated radiology report: {session_state.user_input}"
+                    for history_item in session_state.chat_history:
                         prompt += f"\nUser: {history_item['user']}"
                         if 'bot' in history_item:
                             prompt += f"\nBot: {history_item['bot']}"
-
+            
                     answer = chatbot_response(prompt)
-                    chat_history[-1]["bot"] = answer
+                    session_state.chat_history[-1]["bot"] = answer
                     st.write(f"Bot: {answer}")
+                    session_state.user_input = ''