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Update app.py
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app.py
CHANGED
@@ -19,7 +19,7 @@ model.to(device)
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# Load spaCy model for dependency parsing
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os.system('python -m spacy download en_core_web_sm')
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nlp = spacy.load("en_core_web_sm")
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# Function for generating text and tokenizing
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def historical_generation(prompt, max_new_tokens=600):
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@@ -56,7 +56,7 @@ def historical_generation(prompt, max_new_tokens=600):
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# Create highlighted text output
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highlighted_text = []
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for token in tokens:
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clean_token = token.replace("Ġ", "")
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token_type = tokenizer.convert_ids_to_tokens([tokenizer.convert_tokens_to_ids(token)])[0]
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highlighted_text.append((clean_token, token_type))
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@@ -92,7 +92,11 @@ def full_interface(prompt, max_new_tokens):
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tokens_input, pos_count_input, html_input = text_analysis(prompt)
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# The "Send" button should now appear after these outputs are generated
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return generated_highlight, pos_count_input, html_input, gr.update(visible=True), generated_text
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# Gradio interface components
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with gr.Blocks() as iface:
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@@ -108,6 +112,9 @@ with gr.Blocks() as iface:
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send_button = gr.Button(value="Generate Dependency Parse for Generated Text", visible=False)
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dependency_parse_generated = gr.HTML(label="Dependency Parse Visualization (Generated Text)")
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# Button behavior for generating final parse visualization
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send_button.click(
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generate_dependency_parse,
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@@ -115,11 +122,19 @@ with gr.Blocks() as iface:
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outputs=[dependency_parse_generated]
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)
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# Main interface logic
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full_interface,
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inputs=[prompt, max_new_tokens],
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outputs=[highlighted_text, tokenizer_info, dependency_parse_input, send_button, dependency_parse_generated]
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)
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iface.launch()
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# Load spaCy model for dependency parsing
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os.system('python -m spacy download en_core_web_sm')
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nlp = spacy.load("en_core_web_sm")
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# Function for generating text and tokenizing
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def historical_generation(prompt, max_new_tokens=600):
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# Create highlighted text output
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highlighted_text = []
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for token in tokens:
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clean_token = token.replace("Ġ", "") # Remove "Ġ"
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token_type = tokenizer.convert_ids_to_tokens([tokenizer.convert_tokens_to_ids(token)])[0]
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highlighted_text.append((clean_token, token_type))
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tokens_input, pos_count_input, html_input = text_analysis(prompt)
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# The "Send" button should now appear after these outputs are generated
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return generated_highlight, pos_count_input, html_input, gr.update(visible=True), generated_text, gr.update(visible=False), gr.update(visible=True)
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# Reset function to restore button states
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def reset_interface():
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return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
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# Gradio interface components
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with gr.Blocks() as iface:
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send_button = gr.Button(value="Generate Dependency Parse for Generated Text", visible=False)
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dependency_parse_generated = gr.HTML(label="Dependency Parse Visualization (Generated Text)")
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# Reset button, hidden initially
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reset_button = gr.Button(value="Start Again", visible=False)
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# Button behavior for generating final parse visualization
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send_button.click(
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generate_dependency_parse,
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outputs=[dependency_parse_generated]
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)
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# Main interface logic: when clicked, "Generate" button hides itself and shows the reset button
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generate_button = gr.Button(value="Generate Text and Initial Outputs")
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generate_button.click(
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full_interface,
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inputs=[prompt, max_new_tokens],
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outputs=[highlighted_text, tokenizer_info, dependency_parse_input, send_button, dependency_parse_generated, generate_button, reset_button]
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)
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# Reset button logic: hide itself and re-show the "Generate" button
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reset_button.click(
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reset_interface,
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inputs=None,
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outputs=[generate_button, send_button, reset_button]
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)
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iface.launch()
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