Update app.py

app.py

@@ -56,7 +56,7 @@ def historical_generation(prompt, max_new_tokens=600):
     # Create highlighted text output
     highlighted_text = []
     for token in tokens:
-        clean_token = token.replace("Ġ", "")  # Remove "Ġ"
+        clean_token = token.replace("Ġ", "")
         token_type = tokenizer.convert_ids_to_tokens([tokenizer.convert_tokens_to_ids(token)])[0]
         highlighted_text.append((clean_token, token_type))
 
@@ -79,47 +79,47 @@ def text_analysis(text):
 
     return pos_tokens, pos_count, html
 
-# Full interface combining text generation and analysis
+# Function to generate dependency parse for generated text on button click
+def generate_dependency_parse(generated_text):
+    tokens_generated, pos_count_generated, html_generated = text_analysis(generated_text)
+    return html_generated
+
+# Full interface combining text generation and analysis, split across steps
 def full_interface(prompt, max_new_tokens):
     generated_highlight, generated_text = historical_generation(prompt, max_new_tokens)
 
-    # Dependency parse of both input and generated text
+    # Dependency parse of input text
     tokens_input, pos_count_input, html_input = text_analysis(prompt)
-    tokens_generated, pos_count_generated, html_generated = text_analysis(generated_text)
 
-    return generated_highlight, pos_count_input, html_input, html_generated
-
-# Create Gradio interface
-iface = gr.Interface(
-    fn=full_interface,
-    inputs=[
-        gr.Textbox(
-            label="Prompt",
-            placeholder="Enter a prompt for historical text generation...",
-            lines=3
-        ),
-        gr.Slider(
-            label="Max New Tokens",
-            minimum=50,
-            maximum=1000,
-            step=50,
-            value=600
-        )
-    ],
-    outputs=[
-        gr.HighlightedText(
-            label="Generated Historical Text",
-            combine_adjacent=True,
-            show_legend=True
-        ),
-        gr.JSON(label="Tokenizer Info (Input Text)"),
-        gr.HTML(label="Dependency Parse Visualization (Input Text)"),
-        gr.HTML(label="Dependency Parse Visualization (Generated Text)")
-    ],
-    title="Historical Text Generation with OCRonos-Vintage",
-    description="Generate historical-style text using OCRonos-Vintage and analyze the tokenizer output, including dependency parsing.",
-    theme=gr.themes.Base()
-)
-
-if __name__ == "__main__":
-    iface.launch()
+    # The "Send" button should now appear after these outputs are generated
+    return generated_highlight, pos_count_input, html_input, gr.update(visible=True), generated_text
+
+# Gradio interface components
+with gr.Blocks() as iface:
+    prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt for historical text generation...", lines=3)
+    max_new_tokens = gr.Slider(label="Max New Tokens", minimum=50, maximum=1000, step=50, value=600)
+
+    # Output components
+    highlighted_text = gr.HighlightedText(label="Generated Historical Text", combine_adjacent=True, show_legend=True)
+    tokenizer_info = gr.JSON(label="Tokenizer Info (Input Text)")
+    dependency_parse_input = gr.HTML(label="Dependency Parse Visualization (Input Text)")
+    
+    # Hidden button and final output for dependency parse visualization
+    send_button = gr.Button(value="Generate Dependency Parse for Generated Text", visible=False)
+    dependency_parse_generated = gr.HTML(label="Dependency Parse Visualization (Generated Text)")
+
+    # Button behavior for generating final parse visualization
+    send_button.click(
+        generate_dependency_parse, 
+        inputs=[dependency_parse_generated], 
+        outputs=[dependency_parse_generated]
+    )
+
+    # Main interface logic
+    prompt.submit(
+        full_interface, 
+        inputs=[prompt, max_new_tokens], 
+        outputs=[highlighted_text, tokenizer_info, dependency_parse_input, send_button, dependency_parse_generated]
+    )
+
+iface.launch()