Debugging app.py and making interface changes (repositioning sliders and changing their colour)

app.py

@@ -18,7 +18,7 @@ def correct_htr(raw_htr_text, max_new_tokens, temperature):
         logging.info("Processing HTR correction with Flan-T5 Small...")
         prompt = f"Correct this text: {raw_htr_text}"
         inputs = tokenizer(prompt, return_tensors="pt")
-        max_length = min(max_new_tokens, len(inputs['input_ids'][0]) + max_new_tokens)  # Cap max_length
+        max_length = min(max_new_tokens, len(inputs['input_ids'][0]) + max_new_tokens)
         outputs = model.generate(**inputs, max_length=max_length, temperature=temperature)
         corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
         logging.debug(f"Generated output for HTR correction: {corrected_text}")
@@ -38,7 +38,7 @@ def summarize_text(legal_text, max_new_tokens, temperature):
         logging.info("Processing summarization with Flan-T5 Small...")
         prompt = f"Summarize the following legal text: {legal_text}"
         inputs = tokenizer(prompt, return_tensors="pt")
-        max_length = min(max_new_tokens, len(inputs['input_ids'][0]) + max_new_tokens)  # Cap max_length
+        max_length = min(max_new_tokens, len(inputs['input_ids'][0]) + max_new_tokens)
         outputs = model.generate(**inputs, max_length=max_length, temperature=temperature)
         summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
         logging.debug(f"Generated summary: {summary}")
@@ -58,7 +58,7 @@ def answer_question(legal_text, question, max_new_tokens, temperature):
         logging.info("Processing question-answering with Flan-T5 Small...")
         prompt = f"Answer the following question based on the provided context:\n\nQuestion: {question}\n\nContext: {legal_text}"
         inputs = tokenizer(prompt, return_tensors="pt")
-        max_length = min(max_new_tokens, len(inputs['input_ids'][0]) + max_new_tokens)  # Cap max_length
+        max_length = min(max_new_tokens, len(inputs['input_ids'][0]) + max_new_tokens)
         outputs = model.generate(**inputs, max_length=max_length, temperature=temperature)
         answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
         logging.debug(f"Generated answer: {answer}")
@@ -74,7 +74,7 @@ def clear_fields():
     return "", "", ""
 
 # Create the Gradio Blocks interface
-with gr.Blocks() as demo:
+with gr.Blocks(css=".block .input-slider { color: blue !important }") as demo:
     gr.Markdown("# Flan-T5 Small Legal Assistant")
     gr.Markdown("Use this tool to correct raw HTR, summarize legal texts, or answer questions about legal cases (powered by Flan-T5 Small).")
 
@@ -94,20 +94,21 @@ with gr.Blocks() as demo:
             </div>
         ''')
 
-    # Sliders for max_new_tokens and temperature
-    with gr.Row():
-        max_new_tokens_slider = gr.Slider(minimum=10, maximum=512, value=128, step=1, label="Max New Tokens")
-        temperature_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature")
-
     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_max_new_tokens = gr.Slider(minimum=10, maximum=512, value=128, step=1, label="Max New Tokens")
+        correct_temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature")
 
-        correct_button.click(correct_htr, inputs=[raw_htr_input, max_new_tokens_slider, temperature_slider], outputs=corrected_output)
+        correct_button.click(correct_htr, inputs=[raw_htr_input, correct_max_new_tokens, correct_temperature], outputs=corrected_output)
         clear_button.click(clear_fields, outputs=[raw_htr_input, corrected_output])
+        
+        gr.Markdown("### Set Parameters")
+        correct_max_new_tokens.render()
+        correct_temperature.render()
 
     with gr.Tab("Summarize Legal Text"):
         gr.Markdown("### Summarize Legal Text")
@@ -115,9 +116,15 @@ with gr.Blocks() as demo:
         summary_output = gr.Textbox(lines=5, placeholder="Summary of legal text")
         summarize_button = gr.Button("Summarize Text")
         clear_button = gr.Button("Clear")
+        summarize_max_new_tokens = gr.Slider(minimum=10, maximum=1024, value=256, step=1, label="Max New Tokens")
+        summarize_temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.5, step=0.1, label="Temperature")
 
-        summarize_button.click(summarize_text, inputs=[legal_text_input, max_new_tokens_slider, temperature_slider], outputs=summary_output)
+        summarize_button.click(summarize_text, inputs=[legal_text_input, summarize_max_new_tokens, summarize_temperature], outputs=summary_output)
         clear_button.click(clear_fields, outputs=[legal_text_input, summary_output])
+        
+        gr.Markdown("### Set Parameters")
+        summarize_max_new_tokens.render()
+        summarize_temperature.render()
 
     with gr.Tab("Answer Legal Question"):
         gr.Markdown("### Answer a Question Based on Legal Text")
@@ -126,9 +133,15 @@ with gr.Blocks() as demo:
         answer_output = gr.Textbox(lines=5, placeholder="Answer to your question")
         answer_button = gr.Button("Get Answer")
         clear_button = gr.Button("Clear")
+        answer_max_new_tokens = gr.Slider(minimum=10, maximum=512, value=150, step=1, label="Max New Tokens")
+        answer_temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.1, label="Temperature")
 
-        answer_button.click(answer_question, inputs=[legal_text_input_q, question_input, max_new_tokens_slider, temperature_slider], outputs=answer_output)
+        answer_button.click(answer_question, inputs=[legal_text_input_q, question_input, answer_max_new_tokens, answer_temperature], outputs=answer_output)
         clear_button.click(clear_fields, outputs=[legal_text_input_q, question_input, answer_output])
+        
+        gr.Markdown("### Set Parameters")
+        answer_max_new_tokens.render()
+        answer_temperature.render()
 
 # Model warm-up (optional, but useful for performance)
 model.generate(**tokenizer("Warm-up", return_tensors="pt"), max_length=10)