Update app.py

app.py

@@ -16,9 +16,7 @@ def load_questions(file_path):
     for block in question_blocks:
         parts = block.split('Possible Answers:')
         question_text = parts[0].strip()
-        answers_text = parts[1].strip()
-        possible_answers = [ans.strip() for ans in re.split(r'\d+\.\s+', answers_text) if ans.strip()]
-        questions.append({'question': question_text, 'answers': possible_answers})
+        questions.append({'question': question_text})
     return questions
 
 all_questions = load_questions('knowledge.txt')
@@ -33,7 +31,7 @@ questions_by_type = {
     'Competency-Based Interview': [q for q in all_questions if any(keyword in q['question'].lower() for keyword in [
         "debugging", "learning", "deadlines", "teamwork", "leadership", "mistake", "conflict", "decision"])],
     'Case': [q for q in all_questions if any(keyword in q['question'].lower() for keyword in [
-        "testing", "financial", "automation", "analysis", "regression", "business", "stakeholder"])] 
+        "testing", "financial", "automation", "analysis", "regression", "business", "stakeholder"])]
 }
 
 # models
@@ -52,7 +50,7 @@ def transcribe_audio(file_path):
     except Exception as e:
         return f"❌ ERROR: {str(e)}"
 
-# setting up the users profile (step 1)
+# step 1
 def set_type(choice, user_profile):
     user_profile["interview_type"] = choice
     return "Great! What’s your background and what field/role are you aiming for?", user_profile
@@ -62,7 +60,7 @@ def save_background(info, user_profile):
     user_profile["field"] = info
     return "Awesome! Type 'start' below to begin your interview.", user_profile
 
-# step 3
+# updated step 3
 def respond(message, chat_history, user_profile):
     message_lower = message.strip().lower()
 
@@ -71,7 +69,6 @@ def respond(message, chat_history, user_profile):
         chat_history.append((message, bot_msg))
         return chat_history
 
-    # interview process
     if message_lower == 'start':
         interview_type = user_profile['interview_type']
         selected_questions = questions_by_type.get(interview_type, [])
@@ -115,7 +112,7 @@ def respond(message, chat_history, user_profile):
         chat_history.append((message, feedback))
         return chat_history
 
-    # starting the chatbot
+    # chatbot fallback
     messages = [{"role": "system", "content": f"You are a professional interviewer conducting a {user_profile['interview_type']} interview for a candidate in {user_profile['field']}."}]
     for q, a in chat_history:
         messages.append({"role": "user", "content": q})
@@ -127,21 +124,27 @@ def respond(message, chat_history, user_profile):
     chat_history.append((message, bot_msg))
     return chat_history
 
+# updated feedback using model
 def generate_feedback(user_profile):
-    feedback = []
     questions = user_profile.get('questions', [])
     answers = user_profile.get('user_answers', [])
-    for i, user_ans in enumerate(answers):
-        correct_answers = questions[i]['answers']
-        match = any(ans.lower() in user_ans.lower() for ans in correct_answers)
-        if match:
-            fb = f"Question {i+1}: ✅ Good job!"
-        else:
-            fb = f"Question {i+1}: ❌ Missed some key points: {correct_answers[0]}"
-        feedback.append(fb)
+    feedback = []
+
+    for i, (question, user_answer) in enumerate(zip(questions, answers)):
+        prompt = (
+            f"You are an expert interviewer. Please evaluate the following response:\n\n"
+            f"Question: {question['question']}\n"
+            f"Candidate's Answer: {user_answer}\n\n"
+            f"Give a brief, constructive evaluation. Say whether it's a strong, okay, or weak answer and what could be improved."
+        )
+
+        response = client.text_generation(prompt, max_new_tokens=200)
+        evaluation = response.strip()
+        feedback.append(f"Question {i+1}:\n{evaluation}\n")
+
     return "\n".join(feedback)
 
-# handle audio input
+# handle audio
 def handle_audio(audio_file, chat_history, user_profile):
     transcribed = transcribe_audio(audio_file)
     if transcribed.startswith("❌"):
@@ -149,7 +152,7 @@ def handle_audio(audio_file, chat_history, user_profile):
         return chat_history
     return respond(transcribed, chat_history, user_profile)
 
-# creating the visual elements
+# UI
 with gr.Blocks() as demo:
     user_profile = gr.State({"interview_type": "", "field": "", "interview_in_progress": False})
     chat_history = gr.State([])
@@ -187,10 +190,8 @@ with gr.Blocks() as demo:
         send_btn = gr.Button("Send Text")
         audio_btn = gr.Button("Send Audio")
 
-
     send_btn.click(respond, inputs=[msg, chat_history, user_profile], outputs=[chatbot], queue=False)
     send_btn.click(lambda: "", None, msg, queue=False)
     audio_btn.click(handle_audio, inputs=[audio_input, chat_history, user_profile], outputs=[chatbot], queue=False)
 
-
-demo.launch()
+demo.launch()