app.py

# Cell 1B: Inference Client

import gradio as gr
from huggingface_hub import InferenceClient
import logging

# Setup logging
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')

# Initialize Inference Client
client = InferenceClient(model="Addaci/mT5-small-experiment-13-checkpoint-2790")

def correct_htr(raw_htr_text):
    try:
        logging.info("Processing HTR correction with InferenceClient...")
        # Sending the input to the hosted model
        result = client.text_generation(f"correct this text: {raw_htr_text}")
        logging.debug(f"Generated output for HTR correction: {result}")
        return result['generated_text']  # Extracting the generated text from the response
    except Exception as e:
        logging.error(f"Error in HTR correction: {e}", exc_info=True)
        return str(e)

def summarize_text(legal_text):
    try:
        logging.info("Processing summarization with InferenceClient...")
        # Sending the input to the hosted model
        result = client.text_generation(f"summarize the following legal text: {legal_text}")
        logging.debug(f"Generated summary: {result}")
        return result['generated_text']  # Extracting the generated text from the response
    except Exception as e:
        logging.error(f"Error in summarization: {e}", exc_info=True)
        return str(e)

def answer_question(legal_text, question):
    try:
        logging.info("Processing question-answering with InferenceClient...")
        # Sending the input to the hosted model
        formatted_input = f"Answer the following question based on the provided context:\n\nQuestion: {question}\n\nContext: {legal_text}"
        result = client.text_generation(formatted_input)
        logging.debug(f"Generated answer: {result}")
        return result['generated_text']  # Extracting the generated text from the response
    except Exception as e:
        logging.error(f"Error in question-answering: {e}", exc_info=True)
        return str(e)

# Create the Gradio Blocks interface
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.")

    with gr.Row():
        gr.HTML('''
            <div style="display: flex; gap: 10px;">
                <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>
                </div>
                <div style="border: 2px solid black; padding: 10px; display: inline-block;">
                    <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>
            </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()