Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 import re
+import random
 
 # ---- Load and parse questions from knowledge.txt ----
 def load_questions(file_path):
@@ -8,7 +9,6 @@ def load_questions(file_path):
         data = f.read()
 
     question_blocks = re.split(r'Question:\s*', data)[1:]
-
     questions = []
     for block in question_blocks:
         parts = block.split('Possible Answers:')
@@ -20,94 +20,63 @@ 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 ----
 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',
-    'stack', 'queue', 'recursion', 'reverse', 'bfs', 'dfs', 'time complexity', 'binary search tree',
-    'web application', 'chat system', 'load balancing', 'caching', 'normalization', 'acid', 'indexing',
-    'sql injection', 'https', 'xss', 'hash', 'vulnerabilities'])],
-    
+        'function', 'linked list', 'url', 'rest', 'graphql', 'garbage', 'cap theorem', 'sql', 'hash table',
+        'stack', 'queue', 'recursion', 'reverse', 'bfs', 'dfs', 'time complexity', 'binary search tree',
+        'web application', 'chat system', 'load balancing', 'caching', 'normalization', 'acid', 'indexing',
+        '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", "deadlines", "teamwork", "leadership", "mistake", "conflict", "decision"])],
     '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"])] 
+        "testing", "financial", "automation", "analysis", "regression", "business", "stakeholder"])] 
 }
 
-
-# ---- Hugging Face Client ----
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-# ---- Interview type selection ----
+# ---- Logic functions ----
 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
 
-# ---- Save background ----
 def save_background(info, user_profile):
     user_profile["field"] = info
     return "Awesome! Type 'start' below to begin your interview.", user_profile
 
-# ---- Main respond logic ----
 def respond(message, chat_history, user_profile):
+    message_lower = 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':
+    if message_lower == 'start':
         interview_type = user_profile['interview_type']
         selected_questions = questions_by_type.get(interview_type, [])
+        random.shuffle(selected_questions)
+        selected_questions = selected_questions[:10]
+
         user_profile['questions'] = selected_questions
         user_profile['current_q'] = 0
         user_profile['user_answers'] = []
-        if not selected_questions:
-            bot_msg = "No questions available for this interview type."
-        else:
-            bot_msg = f"First question: {selected_questions[0]['question']}"
+        user_profile['interview_in_progress'] = True
+
+        intro = f"Welcome to your {interview_type} interview for a {user_profile['field']} position. I will ask you up to 10 questions. Type 'stop' anytime to end."
+        first_q = f"First question: {selected_questions[0]['question']}"
+        chat_history.append((message, intro))
+        chat_history.append(("", first_q))
+        return chat_history
+
+    if message_lower == 'stop' and user_profile.get("interview_in_progress"):
+        user_profile['interview_in_progress'] = False
+        bot_msg = "Interview stopped. Type 'feedback' if you'd like me to analyze your answers. Thanks for interviewing with Intervu!"
         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:
+    if user_profile.get("interview_in_progress"):
         q_index = user_profile['current_q']
         user_profile['user_answers'].append(message)
 
@@ -117,22 +86,18 @@ def respond(message, chat_history, user_profile):
         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."
-
+            user_profile['interview_in_progress'] = False
+            bot_msg = "Interview complete! Type 'feedback' if you'd like me to analyze your answers. Thanks for interviewing with Intervu!"
         chat_history.append((message, bot_msg))
         return chat_history
-    
 
-    # Handle feedback request
-    if message.strip().lower() == 'feedback':
+    if message_lower == 'feedback':
         feedback = generate_feedback(user_profile)
         chat_history.append((message, feedback))
         return chat_history
 
-    # Default fallback
-    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."}
-    ]
+    # fallback small talk
+    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})
         messages.append({"role": "assistant", "content": a})
@@ -143,25 +108,23 @@ def respond(message, chat_history, user_profile):
     chat_history.append((message, bot_msg))
     return chat_history
 
-# ---- Simple feedback function (keyword based for now) ----
 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! You covered key points."
+            fb = f"Question {i+1}: ✅ Good job!"
         else:
-            fb = f"Question {i+1}: ❌ You missed some key points: {correct_answers[0]}"
+            fb = f"Question {i+1}: ❌ Missed some key points: {correct_answers[0]}"
         feedback.append(fb)
     return "\n".join(feedback)
 
-# ---- Gradio Interface ----
+# ---- Gradio UI ----
 with gr.Blocks() as demo:
-    user_profile = gr.State({"interview_type": "", "field": ""})
+    user_profile = gr.State({"interview_type": "", "field": "", "interview_in_progress": False})
     chat_history = gr.State([])
 
     gr.Markdown("# 🎤 Welcome to Intervu")