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Debugging app.py as rewritten by ChatGPT-4o (#1)
Browse files- Debugging app.py as rewritten by ChatGPT-4o (f4088d4b41e5f10242fbefde4397e4b71c28dfce)
app.py
CHANGED
@@ -10,10 +10,6 @@ model_id = "google/flan-t5-small"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
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# Define the sliders outside the gr.Row() block
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max_new_tokens = gr.Slider(minimum=10, maximum=512, value=360, step=1, label="Max New Tokens") # Adjusted for smaller model
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temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature")
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def correct_htr(raw_htr_text, max_new_tokens, temperature):
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try:
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if not raw_htr_text:
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@@ -98,6 +94,11 @@ with gr.Blocks() as demo:
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</div>
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''')
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with gr.Tab("Correct HTR"):
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gr.Markdown("### Correct Raw HTR Text")
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raw_htr_input = gr.Textbox(lines=5, placeholder="Enter raw HTR text here...")
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@@ -105,7 +106,7 @@ with gr.Blocks() as demo:
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correct_button = gr.Button("Correct HTR")
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clear_button = gr.Button("Clear")
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correct_button.click(correct_htr, inputs=[raw_htr_input,
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clear_button.click(clear_fields, outputs=[raw_htr_input, corrected_output])
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with gr.Tab("Summarize Legal Text"):
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@@ -115,7 +116,7 @@ with gr.Blocks() as demo:
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summarize_button = gr.Button("Summarize Text")
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clear_button = gr.Button("Clear")
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summarize_button.click(summarize_text, inputs=[legal_text_input,
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clear_button.click(clear_fields, outputs=[legal_text_input, summary_output])
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with gr.Tab("Answer Legal Question"):
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@@ -126,18 +127,12 @@ with gr.Blocks() as demo:
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answer_button = gr.Button("Get Answer")
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clear_button = gr.Button("Clear")
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answer_button.click(answer_question, inputs=[legal_text_input_q, question_input,
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clear_button.click(clear_fields, outputs=[legal_text_input_q, question_input, answer_output])
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# The sliders are already defined, so just include them in the layout
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with gr.Row():
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# No need to redefine max_new_tokens and temperature here
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pass
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# Model warm-up (optional, but useful for performance)
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model.generate(**tokenizer("Warm-up", return_tensors="pt"), max_length=10)
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# Launch the Gradio interface
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if __name__ == "__main__":
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demo.launch()
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
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def correct_htr(raw_htr_text, max_new_tokens, temperature):
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try:
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if not raw_htr_text:
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</div>
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''')
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# Sliders for max_new_tokens and temperature
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with gr.Row():
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max_new_tokens_slider = gr.Slider(minimum=10, maximum=512, value=128, step=1, label="Max New Tokens")
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temperature_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature")
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with gr.Tab("Correct HTR"):
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gr.Markdown("### Correct Raw HTR Text")
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raw_htr_input = gr.Textbox(lines=5, placeholder="Enter raw HTR text here...")
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correct_button = gr.Button("Correct HTR")
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clear_button = gr.Button("Clear")
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correct_button.click(correct_htr, inputs=[raw_htr_input, max_new_tokens_slider, temperature_slider], outputs=corrected_output)
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clear_button.click(clear_fields, outputs=[raw_htr_input, corrected_output])
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with gr.Tab("Summarize Legal Text"):
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summarize_button = gr.Button("Summarize Text")
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clear_button = gr.Button("Clear")
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summarize_button.click(summarize_text, inputs=[legal_text_input, max_new_tokens_slider, temperature_slider], outputs=summary_output)
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clear_button.click(clear_fields, outputs=[legal_text_input, summary_output])
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with gr.Tab("Answer Legal Question"):
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answer_button = gr.Button("Get Answer")
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clear_button = gr.Button("Clear")
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answer_button.click(answer_question, inputs=[legal_text_input_q, question_input, max_new_tokens_slider, temperature_slider], outputs=answer_output)
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clear_button.click(clear_fields, outputs=[legal_text_input_q, question_input, answer_output])
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# Model warm-up (optional, but useful for performance)
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model.generate(**tokenizer("Warm-up", return_tensors="pt"), max_length=10)
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# Launch the Gradio interface
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if __name__ == "__main__":
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demo.launch()
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