back to last promising version with treebuild crashlog, feel like sysyphus - trying to sort log formatting with Claude now urg

app.py

@@ -483,11 +483,20 @@ def trim_tree(trim_cutoff, tree_data):
     return trimmed_tree_image
 
 def gradio_interface():
+    class GradioHandler(logging.Handler):
+        def __init__(self, textbox):
+            super().__init__()
+            self.textbox = textbox
+
+        def emit(self, record):
+            log_entry = self.format(record)
+            self.textbox.update(value=self.textbox.value + log_entry + "\n")
+
     def update_visibility(mode):
         if mode == "definition tree generation":
-            return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+            return gr.update(visible=True), gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
         else:
-            return gr.update(visible=True), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+            return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=False)
 
     def update_neuronpedia(selected_sae, feature_number):
         layer_number = int(selected_sae.split()[-1])
@@ -626,9 +635,16 @@ def gradio_interface():
                 trim_slider = gr.Slider(minimum=0.00001, maximum=0.1, value=0.00001, label="Trim cutoff for cumulative probability", visible=False)
                 trim_btn = gr.Button("Trim Tree", visible=False)
 
+                log_output = gr.Textbox(label="Log Output", lines=20, visible=False)
+
         tree_data_state = gr.State()
         neuronpedia_html = gr.HTML(label="Neuronpedia")
 
+        # Set up the custom logger
+        gradio_handler = GradioHandler(log_output)
+        gradio_handler.setFormatter(logging.Formatter('%(message)s'))
+        custom_logger.addHandler(gradio_handler)
+
         inputs = [selected_sae, feature_number, weight_type, use_token_centroid, scaling_factor, use_pca, pca_weight, num_exp, denom_exp, mode]
 
         generate_btn.click(
@@ -647,17 +663,15 @@ def gradio_interface():
 
         trim_btn.click(trim_tree, inputs=[trim_slider, tree_data_state], outputs=[output_image])
 
-        mode.change(update_visibility, inputs=[mode], outputs=[output_stream, output_image, trim_slider, trim_btn, generate_top_500_btn])
+        mode.change(
+            update_visibility,
+            inputs=[mode],
+            outputs=[output_stream, output_image, trim_slider, trim_btn, generate_top_500_btn, log_output]
+        )
 
         selected_sae.change(update_neuronpedia, inputs=[selected_sae, feature_number], outputs=[neuronpedia_html])
         feature_number.change(update_neuronpedia, inputs=[selected_sae, feature_number], outputs=[neuronpedia_html])
 
-        output_stream.change(
-            lambda text: (gr.update(visible=True), gr.update(visible=True)) if "100 tokens" in text else (gr.update(visible=False), gr.update(visible=False)),
-            inputs=[output_stream],
-            outputs=[generate_top_500_btn, output_500_text]
-        )
-
     return demo