Minor code refactor

src/app.py

@@ -165,7 +165,7 @@ def on_submit(criteria, context, user_message, assistant_message_text, assistant
 
     result = get_guardian_response(messages=messages, criteria_name=criteria_name)
     result_label = result["assessment"]  # Yes or No
-    result_confidence_score = round(result["certainty"] if result["certainty"] > 0.5 else 1 - result["certainty"], 3)
+    result_confidence_score = round(result["certainty"], 3)
 
     html_str = f"<p><strong>{result_label}</strong> <span style='padding-left: 0.25rem; color: gray; font-style: italic'>(Confidence Score: {result_confidence_score})</span></p>"
     # html_str = f"{get_result_description(state['selected_sub_catalog'], state['selected_criteria_name'])} {result_label}"

src/model.py

@@ -202,16 +202,17 @@ def get_guardian_response(messages, criteria_name):
             # logger.debug(f"model output is:\n{output}")
 
             label, prob_of_risk = parse_output(output, input_len)
-            logger.debug(f"Label is: {label}")
-            logger.debug(f"Prob_of_risk is: {prob_of_risk}")
+
     else:
         raise Exception("Environment variable 'INFERENCE_ENGINE' must be one of [WATSONX, MOCK, TORCH]")
 
-    logger.debug(f"Model generated label: {label}")
-    logger.debug(f"Model prob_of_risk: {prob_of_risk}")
+    certainty = prob_of_risk if prob_of_risk > 0.5 else 1 - prob_of_risk
+    
+    logger.debug(f"Label: {label}")
+    logger.debug(f"Probabiliy of risk: {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, "prob_of_risk": prob_of_risk, "certainty": certainty}