Update pages/type_text.py

pages/type_text.py

@@ -9,21 +9,6 @@ import time
 import os
 os.getenv("HF_TOKEN") 
 
-
-#hide_streamlit_style = """
-#        <style>
-#        div[data-testid="stHeader"] {
-#        visibility: visible;
-#        position: sticky;
-#        top: 0
-#        }
-#        </style>
-#        """
-#st.markdown(hide_streamlit_style, unsafe_allow_html=True)
-
-#st.title("Map internal descriptions to SBS codes with Sentence Transformer + Reasoning Models")
-#st.subheader("Select specific Chapter for quicker results")
-
 def get_device_map() -> str:
     return 'cuda' if torch.cuda.is_available() else 'cpu'
 device = get_device_map()  # 'cpu'
@@ -47,46 +32,6 @@ def convert_json(df:pd.DataFrame):
     #st.json(json_string, expanded=True)
     return json_string
 
-def scroll_to_bottom():
-    # This script uses Streamlit's message system to ensure proper timing
-    js_code = """
-    <script>
-        // Function to scroll to bottom
-        function scrollToBottom() {
-            // This targets Streamlit's specific structure
-            const mainContainer = window.parent.document.querySelector('.stApp');
-            if (mainContainer) {
-                mainContainer.scrollTo({
-                    top: mainContainer.scrollHeight,
-                    behavior: 'smooth'
-                });
-            }
-        }
-        
-        // Use MutationObserver to detect when content is added
-        const observer = new MutationObserver((mutations) => {
-            scrollToBottom();
-        });
-        
-        // Start observing the document body for changes
-        const streamlitDoc = window.parent.document;
-        observer.observe(streamlitDoc.body, { 
-            childList: true,
-            subtree: true 
-        });
-        
-        // Initial scroll and disconnect after some time
-        scrollToBottom();
-        setTimeout(() => {
-            observer.disconnect();
-            // One final scroll
-            scrollToBottom();
-        }, 1000);
-    </script>
-    """
-    
-    # Use unsafe_allow_html to inject JavaScript
-    st.markdown(js_code, unsafe_allow_html=True)
 
 #df_chapters = pd.read_csv("SBS_V2_0/Chapter_Index_Rows.csv") 
 df_chapters = pd.read_csv("SBS_V2_0/Chapter_Index_Rows_with_total.csv") 
@@ -230,7 +175,7 @@ if INTdesc_input is not None and st.button("Map to SBS codes", key="run_st_model
         dfALL = pd.concat([dfALL, pd.DataFrame([dictA])], ignore_index=True)
  
     st.dataframe(data=dfALL, hide_index=True)
-    scroll_to_bottom()
+    auto_scroll_to_bottom()
 
     display_format = "ask REASONING MODEL: Which, if any, of the following SBS descriptions corresponds best to " + INTdesc_input +"? " 
     #st.write(display_format)
@@ -254,7 +199,7 @@ if INTdesc_input is not None and st.button("Map to SBS codes", key="run_st_model
         max_new_tokens=256,
     )
     st.write(outputs[0]["generated_text"][-1]["content"]) 
-    scroll_to_bottom()
+    auto_scroll_to_bottom()
     
     bs, b1, b2, b3, bLast = st.columns([0.75, 1.5, 1.5, 1.5, 0.75])
     with b1: