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import os | |
import gradio as gr | |
from transformers import MT5Tokenizer, MT5ForConditionalGeneration | |
# Load your fine-tuned mT5 model | |
model_name = "Addaci/mT5-small-experiment-13-checkpoint-2790" | |
tokenizer = MT5Tokenizer.from_pretrained(model_name) | |
model = MT5ForConditionalGeneration.from_pretrained(model_name) | |
def correct_htr(raw_htr_text): | |
try: | |
inputs = tokenizer(raw_htr_text, return_tensors="pt", max_length=512, truncation=True) | |
outputs = model.generate(**inputs, max_length=128, num_beams=4, early_stopping=True) | |
corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
return corrected_text | |
except Exception as e: | |
return str(e) | |
def summarize_text(legal_text): | |
try: | |
inputs = tokenizer("summarize: " + legal_text, return_tensors="pt", max_length=512, truncation=True) | |
outputs = model.generate(**inputs, max_length=150, num_beams=4, early_stopping=True) | |
summary = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
return summary | |
except Exception as e: | |
return str(e) | |
def answer_question(legal_text, question): | |
try: | |
formatted_input = f"question: {question} context: {legal_text}" | |
inputs = tokenizer(formatted_input, return_tensors="pt", max_length=512, truncation=True) | |
outputs = model.generate(**inputs, max_length=150, num_beams=4, early_stopping=True) | |
answer = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
return answer | |
except Exception as e: | |
return str(e) | |
# Create the Gradio Blocks interface with boxed clickable buttons and bold text | |
with gr.Blocks() as demo: | |
gr.Markdown("# mT5 Legal Assistant") | |
gr.Markdown("Use this tool to correct raw HTR, summarize legal texts, or answer questions about legal cases.") | |
# Adding external link buttons with a box around them and bold text | |
with gr.Row(): | |
gr.HTML('''<div style="border: 2px solid black; padding: 10px; display: inline-block;"> | |
<a href="http://www.marinelives.org/wiki/Tools:_Admiralty_court_legal_glossary" target="_blank"> | |
<button style="font-weight:bold;">Admiralty Court Legal Glossary</button> | |
</a> | |
<a href="https://raw.githubusercontent.com/Addaci/HCA/refs/heads/main/HCA_13_70_Full_Volume_Processed_Text_EDITED_Ver.1.2_18062024.txt" target="_blank"> | |
<button style="font-weight:bold;">HCA 13/70 Ground Truth (1654-55)</button> | |
</a> | |
</div>''') | |
with gr.Tab("Correct HTR"): | |
gr.Markdown("### Correct Raw HTR Text") | |
raw_htr_input = gr.Textbox(lines=5, placeholder="Enter raw HTR text here...") | |
corrected_output = gr.Textbox(lines=5, placeholder="Corrected HTR text") | |
correct_button = gr.Button("Correct HTR") | |
clear_button = gr.Button("Clear") | |
correct_button.click(correct_htr, inputs=raw_htr_input, outputs=corrected_output) | |
clear_button.click(lambda: ("", ""), outputs=[raw_htr_input, corrected_output]) | |
with gr.Tab("Summarize Legal Text"): | |
gr.Markdown("### Summarize Legal Text") | |
legal_text_input = gr.Textbox(lines=10, placeholder="Enter legal text to summarize...") | |
summary_output = gr.Textbox(lines=5, placeholder="Summary of legal text") | |
summarize_button = gr.Button("Summarize Text") | |
clear_button = gr.Button("Clear") | |
summarize_button.click(summarize_text, inputs=legal_text_input, outputs=summary_output) | |
clear_button.click(lambda: ("", ""), outputs=[legal_text_input, summary_output]) | |
with gr.Tab("Answer Legal Question"): | |
gr.Markdown("### Answer a Question Based on Legal Text") | |
legal_text_input_q = gr.Textbox(lines=10, placeholder="Enter legal text...") | |
question_input = gr.Textbox(lines=2, placeholder="Enter your question...") | |
answer_output = gr.Textbox(lines=5, placeholder="Answer to your question") | |
answer_button = gr.Button("Get Answer") | |
clear_button = gr.Button("Clear") | |
answer_button.click(answer_question, inputs=[legal_text_input_q, question_input], outputs=answer_output) | |
clear_button.click(lambda: ("", "", ""), outputs=[legal_text_input_q, question_input, answer_output]) | |
# Launch the Gradio interface | |
demo.launch() | |