Update app.py

app.py

@@ -1,17 +1,15 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-import re
-import random
 import whisper
 from pydub import AudioSegment
-# models
+
+# Load models
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 whisper_model = whisper.load_model("base")
 
-# whisper audio-to-text function
+# Whisper transcription function
 def transcribe_audio(file_path):
     try:
-        print(f"📂 Processing audio: {file_path}")
         audio = AudioSegment.from_file(file_path)
         converted_path = "converted.wav"
         audio.export(converted_path, format="wav")
@@ -19,24 +17,25 @@ def transcribe_audio(file_path):
         return result["text"]
     except Exception as e:
         return f"❌ ERROR: {str(e)}"
-# setting up the users profile (step 1)
+
+# Step 1: 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
 
-# step 2
+# Step 2: Save background
 def save_background(info, user_profile):
     user_profile["field"] = info
     return "Awesome! Type 'start' below to begin your interview.", user_profile
 
-# generate question using LLM
+# Generate interview question
 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
+# 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", []))):
@@ -48,13 +47,14 @@ def generate_feedback_llm(user_profile):
         feedback.append(f"Question {i+1}: {response.choices[0].message.content.strip()}")
     return "\n\n".join(feedback)
 
-# step 3: interview loop
+# Chat 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))
+        chat_history.append({"role": "user", "content": message})
+        chat_history.append({"role": "assistant", "content": bot_msg})
         return chat_history
 
     if message_lower == 'start':
@@ -66,19 +66,22 @@ def respond(message, chat_history, user_profile):
         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}"))
+        chat_history.append({"role": "user", "content": message})
+        chat_history.append({"role": "assistant", "content": intro})
+        chat_history.append({"role": "assistant", "content": 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))
+        chat_history.append({"role": "user", "content": message})
+        chat_history.append({"role": "assistant", "content": bot_msg})
         return chat_history
 
     if message_lower == 'feedback':
         feedback = generate_feedback_llm(user_profile)
-        chat_history.append((message, feedback))
+        chat_history.append({"role": "user", "content": message})
+        chat_history.append({"role": "assistant", "content": feedback})
         return chat_history
 
     if user_profile.get("interview_in_progress"):
@@ -93,7 +96,8 @@ def respond(message, chat_history, user_profile):
             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))
+        chat_history.append({"role": "user", "content": message})
+        chat_history.append({"role": "assistant", "content": bot_msg})
         return chat_history
 
     # fallback LLM response
@@ -103,132 +107,57 @@ def respond(message, chat_history, user_profile):
     ]
     response = client.chat_completion(messages, max_tokens=150, stream=False)
     bot_msg = response.choices[0].message.content.strip()
-    chat_history.append((message, bot_msg))
+    chat_history.append({"role": "user", "content": message})
+    chat_history.append({"role": "assistant", "content": 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("❌"):
-        chat_history.append(("Audio input", transcribed))
+        chat_history.append({"role": "assistant", "content": transcribed})
         return chat_history
     return respond(transcribed, chat_history, user_profile)
-# The new Intervu 2.0 UI with your design!
-with gr.Blocks(css="""
-    body { background-color: #161b24; font-family: 'Nato', sans-serif !important; }
-    h1 { text-align: center; color: #2c3e50; }
-    img { display: block; margin: auto; width: 100px; border-radius: 20px; }
-    button { 
-    font-size: 16px; 
-    padding: 10px 20px; 
-    border-radius: 10px; 
-    border: 2px solid rgba(124, 248, 255, 0.4); 
-    background-color: rgba(124, 248, 255, 0.4); 
-    color: #fafdff; 
-    transition: all 0.2s ease;
-}
-    button:hover {
-    background-color: #49888f;
-    border-color: #7cf8ff;
-    transform: scale(1.05);
-}
-
-    .gr-chatbot { background-color: white; border-radius: 15px; padding: 20px; }
-""") as demo:
-
-
-
-   
-    gr.Markdown("""
-<div style='width: 100%; text-align: center;'>
-  <img src="https://cdn-uploads.huggingface.co/production/uploads/6841b10b397a67a7c7a39b89/MTR_dMHte-RCIbyujLW83.png" style="width: 100%; height: auto; object-fit: contain;">
-</div>
-""")
-
-
-
-
-    
+
+# Gradio UI
+with gr.Blocks(css="""body { background-color: #161b24; font-family: 'Nato', sans-serif !important; }""") as demo:
+    gr.Markdown("# 🎤 Welcome to Intervu")
+
     user_profile = gr.State({"interview_type": "", "field": "", "interview_in_progress": False})
     chat_history = gr.State([])
 
-    #Header
-    gr.Markdown("""<div style='
-    font-family: 'Lato', sans-serif;
-    text-align: center;
-    padding: 30px;
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
-    margin-bottom: 20px;
-'>
-    <h1 style='font-size: 89.5px; color: #fafdff;'>Welcome to <b><span style='color: #7cf8ff;'>Intervu</span></b></h1>
-    <p style='font-size: 22.1px; color: #fafdff; margin-top: 30px; text-align: center; margin-bottom: 30px;'>Before you begin, complete Step 1 to select your interview type and Step 2 to enter your background. Practice is available through text, speech, or webcam.</p>
-</div>
-""")
-
-
-    # Step 1 - Choose Interview Type
-    # gr.Markdown("### Step 1: Choose Interview Type")
-    # with gr.Row():
-    #     btn1 = gr.Button("Technical")
-    #     btn2 = gr.Button("Competency-Based Interview")
-    #     btn3 = gr.Button("Case")
-    # type_output = gr.Textbox(label="Bot response", interactive=False)
+    # Step 1
     with gr.Row():
-    
-        # LEFT SIDE: Transparent box with interview type buttons
-        with gr.Column(scale=2):
-            gr.Markdown("""
-                <div style="
-                    background: rgba(255, 255, 255, 0.1); 
-                    padding: 20px; 
-                    border-radius: 15px; 
-                    backdrop-filter: blur(5px); 
-                    box-shadow: 0 4px 10px rgba(0,0,0,0.2);
-                ">
-                    <h3>Step 1: Choose Interview Type</h3>
-                    <p>Select the type of interview you want to practice.</p>
-                </div>
-            """)
-            
+        with gr.Column():
             btn1 = gr.Button("Technical")
             btn2 = gr.Button("Competency-Based Interview")
             btn3 = gr.Button("Case")
-    
-        # RIGHT SIDE: Bot response display (type_output)
-        with gr.Column(scale=2):
-            type_output = gr.Textbox(label="Bot Response", interactive=False)
-
-
+        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])
     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")
+    # Step 2
     background = gr.Textbox(label="Your background and field/goal")
     background_btn = gr.Button("Submit")
     background_output = gr.Textbox(label="Bot response", interactive=False)
     background_btn.click(save_background, inputs=[background, user_profile], outputs=[background_output, user_profile])
 
-    # Step 3 - Chatbot Mode Selection
-    # Step 3 - Chatbot Mode Selection
-# Step 3 - Chatbot Mode Selection
-    gr.Markdown("### Step 3: Choose Chat Mode")
-    
+    # Step 3 - Tabs
+    gr.Markdown("### Choose Chat Mode")
     with gr.Tabs():
         with gr.Tab("Text Mode"):
-            chatbot_text = gr.Chatbot(label="Interview Chat (Text Mode)")
+            chatbot_text = gr.Chatbot(label="Interview Chat (Text Mode)", type="messages")
             msg = gr.Textbox(label="Type 'start' to begin")
             send_btn = gr.Button("Send")
             send_btn.click(respond, inputs=[msg, chat_history, user_profile], outputs=[chatbot_text], queue=False)
             send_btn.click(lambda: "", None, msg, queue=False)
-    
+
         with gr.Tab("Audio Mode"):
-            chatbot_audio = gr.Chatbot(label="Interview Chat (Audio Mode)")
-            audio_input = gr.Audio(source="microphone", type="filepath", label="Record Your Answer")
+            chatbot_audio = gr.Chatbot(label="Interview Chat (Audio Mode)", type="messages")
+            audio_input = gr.Audio(type="filepath", label="Record Your Answer")
             audio_btn = gr.Button("Send Audio")
             audio_btn.click(handle_audio, inputs=[audio_input, chat_history, user_profile], outputs=[chatbot_audio], queue=False)
 
-
 demo.launch()