Update app.py

app.py

@@ -1664,27 +1664,20 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     user_audio_input.change(transcribe, user_audio_input, stt_transcript)
 
     def process_answer(transcript, audio_path, video_path, state, data):
-        if not transcript and not video_path:
+        if not transcript:
             return state, gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update()
+    
         elapsed = round(time.time() - state.get("q_start_time", time.time()), 2)
         state["timings"].append(elapsed)
         state["answers"].append(transcript)
         state["conversation_history"].append({'role': 'Candidate', 'content': transcript})
 
-        # --- 1. Emotion analysis ---
-        # voice_label = analyze_audio_emotion(audio_path)
-        # face_label = analyze_video_emotions(video_path)
-        # state["voice_labels"].append(voice_label)
-        # state["face_labels"].append(face_label)
-
-        #just for testing
+        # --- 1. Emotion analysis (simplified for testing) ---
         voice_label = "neutral"
         face_label = "neutral"
         state["voice_labels"].append(voice_label)
         state["face_labels"].append(face_label)
 
-        
-
         # --- 2. Evaluate previous Q and Answer ---
         last_q = state["questions"][-1]
         q_eval = state["question_evaluations"][-1]  # Already in state
@@ -1701,15 +1694,10 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         else:
             state["difficulty_adjustment"] = None
 
-        # --- 4. Effective confidence ---
-        # eff_conf = interpret_confidence(voice_label, face_label, answer_score)
-        # state["effective_confidences"].append(eff_conf)
-
-        #just for testing:
+        # --- 4. Effective confidence (simplified) ---
         eff_conf = {"effective_confidence": 0.6}
         state["effective_confidences"].append(eff_conf)
 
-
         # --- LOG ---
         state["log"].append({
             "type": "answer",
@@ -1739,9 +1727,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                             f"- *Answer*: {state['answers'][i]}\n"
                             f"- *Q Eval*: {state['question_evaluations'][i]}\n"
                             f"- *A Eval*: {state['answer_evaluations'][i]}\n"
-                            #also this are removed just for testing :(
-                            # f"- *Face Emotion: {state['face_labels'][i]}, **Voice Emotion*: {state['voice_labels'][i]}\n"
-                            # f"- *Effective Confidence*: {state['effective_confidences'][i]['effective_confidence']}\n"
                             f"- *Time*: {state['timings'][i]}s\n")
             summary += f"\n\n⏺ Full log saved as {log_file}."
             return (state, gr.update(visible=True, value=summary), gr.update(value=None), gr.update(value=None), gr.update(value=None), gr.update(value=None), gr.update(visible=True, value=f"Last Detected — Face: {face_label}, Voice: {voice_label}"))
@@ -1773,14 +1758,15 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             return (
                 state, gr.update(visible=False), audio_path, f"*Question {qidx + 1}:* {next_q}",
                 gr.update(value=None), gr.update(value=None),
-                gr.update(visible=True, value=f"Last Detected — Face: {face_label}, Voice: {voice_label}"),
+                gr.update(visible=True, value=eval_md),
             )
+    # Replace your confirm_btn.click with this:
     confirm_btn.click(
         process_answer,
-        [stt_transcript, user_audio_input, interview_state, user_data],
-        [interview_state, interview_summary, question_audio, question_text, user_audio_input]
+        [stt_transcript, user_audio_input, None, interview_state, user_data],  # Added None for video_path
+        [interview_state, interview_summary, question_audio, question_text, user_audio_input, stt_transcript, evaluation_display]
     ).then(
-        lambda: (gr.update(value=None), gr.update(value=None)), None, [user_audio_input]
+        lambda: (gr.update(value=None), gr.update(value=None)), None, [user_audio_input, stt_transcript]
     )
 
 demo.launch(debug=True)