Update app.py (added two clickable buttons at top of each tab page)

Add Gradio Interface and Launch
# After your function definitions (correct_htr, summarize_text, answer_question), you need to define your Gradio interface and call demo.launch() to run the app.

Add two clickable buttons
# To add two clickable buttons for accessing external links (the Admiralty Court Legal Glossary and HCA 13/70 Ground Truth) on the left-hand side of each tab window, you can use Gradio's gr.Button() along with gr.HTML() to embed links in the interface.
# Unfortunately, Gradio does not currently support traditional sidebars, but we can still place these buttons or links at the top of the interface (before the main content) for easy access.

app.py

@@ -8,49 +8,66 @@ tokenizer = T5Tokenizer.from_pretrained(model_name)
 model = T5ForConditionalGeneration.from_pretrained(model_name)
 
 def correct_htr(raw_htr_text):
-    # Tokenize the input text
     inputs = tokenizer(raw_htr_text, return_tensors="pt", max_length=512, truncation=True)
-    print("Tokenized Inputs for HTR Correction:", inputs)  # Debugging
-
-    # Generate corrected text with max_length and beam search
     outputs = model.generate(**inputs, max_length=128, num_beams=4, early_stopping=True)
-    print("Generated Output (Tokens) for HTR Correction:", outputs)  # Debugging
-
-    # Decode the output, skipping special tokens
     corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    print("Decoded Output for HTR Correction:", corrected_text)  # Debugging
-
     return corrected_text
 
 def summarize_text(legal_text):
-    # Tokenize the input text with the summarization prompt
     inputs = tokenizer("summarize: " + legal_text, return_tensors="pt", max_length=512, truncation=True)
-    print("Tokenized Inputs for Summarization:", inputs)  # Debugging
-
-    # Generate summary with beam search for better results
     outputs = model.generate(**inputs, max_length=150, num_beams=4, early_stopping=True)
-    print("Generated Summary (Tokens):", outputs)  # Debugging
-
-    # Decode the output, skipping special tokens
     summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    print("Decoded Summary:", summary)  # Debugging
-
     return summary
 
 def answer_question(legal_text, question):
-    # Format input for question-answering
     formatted_input = f"question: {question} context: {legal_text}"
     inputs = tokenizer(formatted_input, return_tensors="pt", max_length=512, truncation=True)
-    print("Tokenized Inputs for Question Answering:", inputs)  # Debugging
-
-    # Generate answer using beam search
     outputs = model.generate(**inputs, max_length=150, num_beams=4, early_stopping=True)
-    print("Generated Answer (Tokens):", outputs)  # Debugging
-
-    # Decode the output, skipping special tokens
     answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    print("Decoded Answer:", answer)  # Debugging
-
     return answer
 
+# 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.")
+
+    # Adding external link buttons at the top
+    with gr.Row():
+        gr.HTML('<a href="http://www.marinelives.org/wiki/Tools:_Admiralty_court_legal_glossary" target="_blank"><button>Admiralty Court Legal Glossary</button></a>')
+        gr.HTML('<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>HCA 13/70 Ground Truth (1654-55)</button></a>')
+
+    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()
+