Update app.py

app.py

@@ -1,13 +1,15 @@
+# imports
 import gradio as gr
 from huggingface_hub import InferenceClient
+import random
 import whisper
 from pydub import AudioSegment
 
-# Load models
+# models
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 whisper_model = whisper.load_model("base")
 
-# ---------- Whisper Audio-to-Text Function ----------
+# whisper audio-to-text function
 def transcribe_audio(file_path):
     try:
         print(f"📂 Processing audio: {file_path}")
@@ -19,37 +21,94 @@ def transcribe_audio(file_path):
     except Exception as e:
         return f"❌ ERROR: {str(e)}"
 
-# ---------- Step 1 ----------
+# setting up the users profile (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
 
-# ---------- Step 2 ----------
+# step 2
 def save_background(info, user_profile):
     user_profile["field"] = info
     return "Awesome! Type 'start' below to begin your interview.", user_profile
 
-# ---------- Step 3 ----------
+# generate question using LLM
+def generate_question(user_profile):
+    system_prompt = f"You are a professional interviewer conducting a {user_profile['interview_type']} interview for a candidate in {user_profile['field']}. Generate one thoughtful, clear, and concise interview question."
+    messages = [{"role": "system", "content": system_prompt}]
+    response = client.chat_completion(messages, max_tokens=100, stream=False)
+    return response.choices[0].message.content.strip()
+
+# generate feedback using LLM
+def generate_feedback_llm(user_profile):
+    feedback = []
+    for i, (question, answer) in enumerate(zip(user_profile.get("questions", []), user_profile.get("user_answers", []))):
+        messages = [
+            {"role": "system", "content": f"You are a professional interviewer providing feedback for a candidate's response in a {user_profile['interview_type']} interview for a {user_profile['field']} role."},
+            {"role": "user", "content": f"Question: {question}\nAnswer: {answer}\nPlease give specific, constructive feedback."}
+        ]
+        response = client.chat_completion(messages, max_tokens=150, stream=False)
+        feedback.append(f"Question {i+1}: {response.choices[0].message.content.strip()}")
+    return "\n\n".join(feedback)
+
+# step 3: interview loop
 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
 
+    if message_lower == 'start':
+        user_profile['questions'] = []
+        user_profile['user_answers'] = []
+        user_profile['current_q'] = 0
+        user_profile['interview_in_progress'] = True
+
+        intro = f"Welcome to your {user_profile['interview_type']} interview for a {user_profile['field']} position. I will ask you up to 10 questions. Type 'stop' anytime to end."
+        first_q = generate_question(user_profile)
+        user_profile['questions'].append(first_q)
+        chat_history.append((message, intro))
+        chat_history.append(("", f"First question: {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 message_lower == 'feedback':
+        feedback = generate_feedback_llm(user_profile)
+        chat_history.append((message, feedback))
+        return chat_history
+
+    if user_profile.get("interview_in_progress"):
+        user_profile['user_answers'].append(message)
+        user_profile['current_q'] += 1
+
+        if user_profile['current_q'] < 10:
+            next_q = generate_question(user_profile)
+            user_profile['questions'].append(next_q)
+            bot_msg = f"Next question: {next_q}"
+        else:
+            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
+
+    # fallback LLM response
     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."}
+        {"role": "system", "content": f"You are a professional interviewer conducting a {user_profile['interview_type']} interview for a candidate in {user_profile['field']}."},
+        {"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
+    bot_msg = response.choices[0].message.content.strip()
     chat_history.append((message, bot_msg))
     return chat_history
 
-# ---------- Handle Audio Input ----------
+# handle audio input
 def handle_audio(audio_file, chat_history, user_profile):
     transcribed = transcribe_audio(audio_file)
     if transcribed.startswith("❌"):
@@ -57,28 +116,26 @@ def handle_audio(audio_file, chat_history, user_profile):
         return chat_history
     return respond(transcribed, chat_history, user_profile)
 
-# ---------- Gradio UI ----------
+# 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('<img src="Take1.jpeg" alt="Banner" style="width: 100%; max-width: 600px;">')
-    gr.Markdown("# 🎤 Welcome to Intervu")
+    gr.Markdown("# Welcome to Intervu")
+    gr.Image(value="images.JPEG", show_label=False, width=200)
 
-    # Step 1: Choose Interview Type
     gr.Markdown("### Step 1: Choose Interview Type")
     with gr.Row():
         with gr.Column():
-            btn1 = gr.Button("Behavioral")
-            btn2 = gr.Button("Technical")
-            btn3 = gr.Button("College / Scholarship")
+            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="Behavioral", visible=False), user_profile], outputs=[type_output, user_profile])
-    btn2.click(set_type, inputs=[gr.Textbox(value="Technical", visible=False), user_profile], outputs=[type_output, user_profile])
-    btn3.click(set_type, inputs=[gr.Textbox(value="College", visible=False), user_profile], outputs=[type_output, user_profile])
+    btn1.click(set_type, inputs=[gr.Textbox(value="Technical", visible=False), user_profile], outputs=[type_output, user_profile])
+    btn2.click(set_type, inputs=[gr.Textbox(value="Competency-Based Interview", visible=False), user_profile], outputs=[type_output, user_profile])
+    btn3.click(set_type, inputs=[gr.Textbox(value="Case", visible=False), user_profile], outputs=[type_output, user_profile])
 
-    # Step 2: Enter Background
     gr.Markdown("### Step 2: Enter Your Background")
     background = gr.Textbox(label="Your background and field/goal")
     background_btn = gr.Button("Submit")
@@ -86,13 +143,12 @@ with gr.Blocks() as demo:
 
     background_btn.click(save_background, inputs=[background, user_profile], outputs=[background_output, user_profile])
 
-    # Step 3: Interview Chat
     gr.Markdown("### Step 3: Start Interview")
     chatbot = gr.Chatbot(label="Interview Bot")
 
     with gr.Row():
         msg = gr.Textbox(label="Your message")
-        audio_input = gr.Audio(type="filepath", label="🎙️ Upload or Record your answer")
+        audio_input = gr.Audio(type="filepath", label="🎧 Upload or Record your answer")
 
     with gr.Row():
         send_btn = gr.Button("Send Text")
@@ -100,8 +156,8 @@ with gr.Blocks() as demo:
 
     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)
 
-# ---------- Launch App ----------
-demo.launch()
+
+if __name__ == "__main__":
+    demo.launch()