Add back all dataset

app.py

@@ -40,7 +40,6 @@ dataset = load_dataset(
     ],
 )
 
-dataset = dataset.select(range(1000))
 # Convert the train split to a pandas DataFrame
 train_df = dataset.to_pandas()
 del dataset
@@ -119,21 +118,6 @@ layout = html.Div(
 )
 
 
-@app.callback(
-    Output("material-dropdown", "options"),
-    Output("material-dropdown", "value"),
-    Input("materials-input", "submitButtonClicks"),
-    Input("materials-input", "value"),
-)
-def on_submit_materials_input(n_clicks, query):
-    if n_clicks is None or not query:
-        return [], None
-    options = search_materials(query)
-    if not options:
-        return [], None
-    return options, options[0]["value"]
-
-
 # Function to search for materials
 def search_materials(query):
     element_list = [el.strip() for el in query.split(",")]
@@ -154,19 +138,20 @@ def search_materials(query):
     return options
 
 
-# # Callback to update the material dropdown based on search
-# @app.callback(
-#     [Output("material-dropdown", "options"), Output("material-dropdown", "value")],
-#     Input("search-button", "n_clicks"),
-#     State("query-input", "value"),
-# )
-# def update_material_dropdown(n_clicks, query):
-#     if n_clicks is None or not query:
-#         return [], None
-#     options = search_materials(query)
-#     if not options:
-#         return [], None
-#     return options, options[0]["value"]
+# Callback to update the material dropdown based on search
+@app.callback(
+    Output("material-dropdown", "options"),
+    Output("material-dropdown", "value"),
+    Input("materials-input", "submitButtonClicks"),
+    Input("materials-input", "value"),
+)
+def on_submit_materials_input(n_clicks, query):
+    if n_clicks is None or not query:
+        return [], None
+    options = search_materials(query)
+    if not options:
+        return [], None
+    return options, options[0]["value"]
 
 
 # Callback to display the selected material