Bring back yes/no bold text

src/app.py

@@ -51,8 +51,8 @@ def on_submit(criteria, context, user_message, assistant_message, state):
     logger.debug(f"Starting evaluation for subcatelog {state['selected_sub_catalog']} and criteria name {state['selected_criteria_name']}")
     result_label = generate_text(prompt)['assessment'] # Yes or No
 
-    # html_str = f"<p>{get_result_description(state['selected_sub_catalog'], state['selected_criteria_name'])} <strong>{result_label}</strong></p>"
-    html_str = f"{get_result_description(state['selected_sub_catalog'], state['selected_criteria_name'])} {result_label}"
+    html_str = f"<p>{get_result_description(state['selected_sub_catalog'], state['selected_criteria_name'])} <strong>{result_label}</strong></p>"
+    # html_str = f"{get_result_description(state['selected_sub_catalog'], state['selected_criteria_name'])} {result_label}"
     return gr.update(value=html_str)
 
 def on_show_prompt_click(criteria, context, user_message, assistant_message, state):
@@ -159,15 +159,20 @@ with gr.Blocks(
                 icon=os.path.join(os.path.dirname(os.path.abspath(__file__)), 'send-white.png'),
                 elem_classes='submit-button')
             
-            result_text = gr.Textbox(
+            # result_text = gr.HTML(label='Result', elem_classes=['result-text', 'read-only', 'input-box'], visible=False, value='')
+            result_text = gr.HTML(
                 label='Result',
-                elem_classes=['result-text', 'read-only', 'input-box'],
+                elem_classes=['result-root'],
+                show_label=True,
                 visible=False,
                 value='')
 
             with Modal(visible=False, elem_classes='modal') as modal:
                 prompt = gr.Markdown('')
 
+    
+    ### events
+
     show_propt_button.click(
         on_show_prompt_click,
         inputs=[criteria, context, user_message, assistant_message, state],

src/model.py

@@ -60,23 +60,22 @@ def generate_text(prompt):
         logger.debug('Returning mocked model result.')
         sleep(1)
         return {'assessment': 'Yes', 'certainty': 0.97}
-    else:
-        start = time()
-        
-        tokenized_chat = tokenizer.apply_chat_template([prompt], tokenize=False, add_generation_prompt=True)
+    start = time()
+    
+    tokenized_chat = tokenizer.apply_chat_template([prompt], tokenize=False, add_generation_prompt=True)
 
-        with torch.no_grad():
-            output = model.generate(tokenized_chat, sampling_params, use_tqdm=False)
+    with torch.no_grad():
+        output = model.generate(tokenized_chat, sampling_params, use_tqdm=False)
 
-        # predicted_label = output[0].outputs[0].text.strip()
+    # predicted_label = output[0].outputs[0].text.strip()
 
-        label, prob_of_risk = parse_output(output[0])
+    label, prob_of_risk = parse_output(output[0])
 
-        logger.debug(f'Model generated label: \n{label}')
-        logger.debug(f'Model prob_of_risk: \n{prob_of_risk}')
-        
-        end = time()
-        total = end - start
-        logger.debug(f'The evaluation took {total} secs')
+    logger.debug(f'Model generated label: \n{label}')
+    logger.debug(f'Model prob_of_risk: \n{prob_of_risk}')
+    
+    end = time()
+    total = end - start
+    logger.debug(f'The evaluation took {total} secs')
 
-        return {'assessment': label, 'certainty': prob_of_risk}
+    return {'assessment': label, 'certainty': prob_of_risk}

src/styles.css

@@ -73,40 +73,43 @@
 }
 
 .read-only label textarea,input {
-    /* cursor: not-allowed; */
+    cursor: text;
     /* border: none;
     box-shadow: none; */
     resize: none;
     border: none;
+    background-color: var(--block-background-fill);
     /* -webkit-text-fill-color: rgba(82, 82, 82, 1) !important; */
     /* color: rgba(82, 82, 82, 1) !important; */
   
     /* background-color: var(--background-fill-secondary); */
 }
 
-.result-text p {
-    box-shadow: none;
+.result-root {
+    background-color: var(--block-background-fill) !important;
+    padding: var(--block-padding) !important;
 }
 
-.result-container {
-    background-color: var(--block-background-fill);
-    gap: var(--block-padding);
-    padding: var(--block-padding);
-    flex-grow: 0 !important;
+.result-root span label span {
+    display: none;
 }
 
-.result-title span{
-    display: inline-block;
+.result-root span label {
+    border: solid var(--block-title-border-width) var(--block-title-border-color) !important;
+    border-radius: var(--block-title-radius) !important;
+    background: var(--block-title-background-fill) !important;
+    padding: var(--block-title-padding) !important;
+    color: var(--block-title-text-color) !important;
+    font-weight: var(--block-title-text-weight) !important;
+    font-size: var(--block-title-text-size) !important;
+    line-height: var(--line-sm) !important;
     position: relative;
-    z-index: var(--layer-4);
-    border: solid var(--block-title-border-width) var(--block-title-border-color);
-    border-radius: var(--block-title-radius);
-    background: var(--block-title-background-fill);
-    padding: var(--block-title-padding);
-    color: var(--block-title-text-color);
-    font-weight: var(--block-title-text-weight);
-    font-size: var(--block-title-text-size);
-    line-height: var(--line-sm);
+    top: 0 !important; 
+    left: 0 !important;
+}
+
+.result-root .pending .prose {
+    min-height: 44px;
 }
 
 .modal .modal-container .modal-block{