Update app.py

app.py

@@ -20,8 +20,7 @@ def load_questions(file_path):
 
 all_questions = load_questions('knowledge.txt')
 
-# ---- Simple way to assign questions to interview types ----
-# You can replace this later with better tagging
+# ---- Tagging interview questions ----
 questions_by_type = {
     'Technical': [q for q in all_questions if any(keyword in q['question'].lower() for keyword in [
     'function', 'linked list', 'url', 'rest', 'graphql', 'garbage', 'cap theorem', 'sql', 'hash table',
@@ -30,30 +29,16 @@ questions_by_type = {
     'sql injection', 'https', 'xss', 'hash', 'vulnerabilities'])],
     
     'Competency-Based Interview': [q for q in all_questions if any(keyword in q['question'].lower() for keyword in [
-    "Debugging",
-    "Learning Fast",
-    "Deadlines",
-    "Teamwork",
-    "Leadership",
-    "Mistake Recovery",
-    "Conflict Management",
-    "Decision Making"])],
+    "Debugging","Learning Fast","Deadlines","Teamwork","Leadership","Mistake Recovery","Conflict Management","Decision Making"])],
     
     'Case': [q for q in all_questions if any(keyword in q['question'].lower() for keyword in [
-    "A/B Testing",
-    "Financial Modeling",
-    "Automation",
-    "Data Analysis",
-    "Regression",
-    "Business Opportunity",
-    "Stakeholder Alignment"])] 
+    "A/B Testing","Financial Modeling","Automation","Data Analysis","Regression","Business Opportunity","Stakeholder Alignment"])] 
 }
 
-
 # ---- Hugging Face Client ----
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-# ---- Interview type selection ----
+# ---- Set interview type ----
 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
@@ -65,13 +50,15 @@ def save_background(info, user_profile):
 
 # ---- Main respond logic ----
 def respond(message, chat_history, user_profile):
+    message = message.strip().lower()
+
     if not user_profile.get("interview_type") or not user_profile.get("field"):
         bot_msg = "Please finish steps 1 and 2 before starting the interview."
         chat_history.append((message, bot_msg))
         return chat_history
 
-    # Start interview logic
-    if message.strip().lower() == 'start':
+    # Start interview
+    if message == 'start':
         interview_type = user_profile['interview_type']
         selected_questions = questions_by_type.get(interview_type, [])
         user_profile['questions'] = selected_questions
@@ -84,75 +71,59 @@ def respond(message, chat_history, user_profile):
         chat_history.append((message, bot_msg))
         return chat_history
 
-    # If interview is ongoing
-    # if user_profile.get("questions"):
-    #     q_index = user_profile['current_q']
-    #     user_profile['user_answers'].append(message)
-
-    #     q_index += 1
-    #     user_profile['current_q'] = q_index
-
-    #     if q_index < len(user_profile['questions']):
-    #         bot_msg = f"Next question: {user_profile['questions'][q_index]['question']}"
-    #     else:
-    #         bot_msg = "Interview complete! Type 'feedback' if you'd like me to analyze your answers."
-    #     chat_history.append((message, bot_msg))
-    #     return chat_history
-    if user_profile.get("questions"):
-
-        # --- NEW STOP LOGIC ---
-        if message.strip().lower() == 'stop':
-            bot_msg = "Thank you for chatting with Intervu! The interview has been stopped. Type 'feedback' if you'd like me to analyze your answers."
-            chat_history.append((message, bot_msg))
-            user_profile['questions'] = []  # clear questions list to stop
-            return chat_history
-
-        # Existing interview logic continues here:
-        q_index = user_profile['current_q']
-        user_profile['user_answers'].append(message)
-
-        q_index += 1
-        user_profile['current_q'] = q_index
-
-        if q_index < len(user_profile['questions']):
-            bot_msg = f"Next question: {user_profile['questions'][q_index]['question']}"
-        else:
-            bot_msg = "Interview complete! Type 'feedback' if you'd like me to analyze your answers."
-
+    # Stop interview early
+    if message == 'stop':
+        user_profile['questions'] = []
+        bot_msg = "Interview stopped. Type 'start' to begin again or 'feedback' to get feedback."
         chat_history.append((message, bot_msg))
         return chat_history
-    
 
-    # Handle feedback request
-    if message.strip().lower() == 'feedback':
+    # Handle feedback
+    if message == 'feedback':
+        if not user_profile.get("questions"):
+            chat_history.append((message, "No completed interview found. Please complete the interview first."))
+            return chat_history
         feedback = generate_feedback(user_profile)
         chat_history.append((message, feedback))
         return chat_history
 
-    # Default fallback
+    # Handle interview questions
+    if user_profile.get("questions"):
+        q_index = user_profile['current_q']
+        if q_index < len(user_profile['questions']):
+            user_profile['user_answers'].append(message)
+            user_profile['current_q'] += 1
+
+            if user_profile['current_q'] < len(user_profile['questions']):
+                next_question = user_profile['questions'][user_profile['current_q']]['question']
+                chat_history.append((message, f"Next question: {next_question}"))
+            else:
+                chat_history.append((message, "Interview complete! Type 'feedback' if you'd like an analysis."))
+            return chat_history
+
+    # General fallback chat using LLM if no interview ongoing
     messages = [
         {"role": "system", "content": f"You are a professional interviewer conducting a {user_profile['interview_type']} interview for a candidate in the {user_profile['field']} field."}
     ]
-    # for q, a in chat_history:
-    #     messages.append({"role": "user", "content": q})
-    #     messages.append({"role": "assistant", "content": a})
-    # messages.append({"role": "user", "content": message})
+    for q, a in chat_history:
+        messages.append({"role": "user", "content": q})
+        messages.append({"role": "assistant", "content": a})
+    messages.append({"role": "user", "content": message})
 
     response = client.chat_completion(messages, max_tokens=150, stream=False)
     bot_msg = response.choices[0].message.content
     chat_history.append((message, bot_msg))
     return chat_history
 
-# ---- Simple feedback function (keyword based for now) ----
+# ---- Feedback generator ----
 def generate_feedback(user_profile):
     feedback = []
     questions = user_profile.get('questions', [])
     answers = user_profile.get('user_answers', [])
 
-    num_questions = min(len(questions), len(answers))  # avoid index error
-
+    num_questions = min(len(questions), len(answers))
     if num_questions == 0:
-        return "No completed interview found. Please complete the interview first."
+        return "No completed interview found."
 
     for i in range(num_questions):
         user_ans = answers[i]
@@ -163,10 +134,9 @@ def generate_feedback(user_profile):
         else:
             fb = f"Question {i+1}: ❌ You missed some key points: {correct_answers[0]}"
         feedback.append(fb)
-
     return "\n".join(feedback)
 
-# ---- Gradio Interface ----
+# ---- Gradio interface ----
 with gr.Blocks() as demo:
     user_profile = gr.State({"interview_type": "", "field": ""})
     chat_history = gr.State([])
@@ -175,10 +145,9 @@ with gr.Blocks() as demo:
 
     gr.Markdown("### Step 1: Choose Interview Type")
     with gr.Row():
-        with gr.Column():
-            btn1 = gr.Button("Technical")
-            btn2 = gr.Button("Competency-Based Interview")
-            btn3 = gr.Button("Case")
+        btn1 = gr.Button("Technical")
+        btn2 = gr.Button("Competency-Based Interview")
+        btn3 = gr.Button("Case")
         type_output = gr.Textbox(label="Bot response", interactive=False)
 
     btn1.click(set_type, inputs=[gr.Textbox(value="Technical", visible=False), user_profile], outputs=[type_output, user_profile])
@@ -201,4 +170,3 @@ with gr.Blocks() as demo:
     send_btn.click(lambda: "", None, msg, queue=False)
 
 demo.launch()
-