Update app.py

app.py

@@ -1,78 +1,62 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
+# Initialize your model
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Step 1: Set interview type
 def set_type(choice, user_profile):
-    user_profile["interview_type"] = choice.lower()
-    return f"Great! What’s your background and what field/role are you aiming for?", 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: Save background info
 def save_background(info, user_profile):
     user_profile["field"] = info
     return "Awesome! Type 'start' below to begin your interview.", user_profile
 
+# Step 3: Respond to user
 def respond(message, history, user_profile):
-    if not user_profile["interview_type"] or not user_profile["field"]:
+    if not user_profile.get("interview_type") or not user_profile.get("field"):
         return "Please finish steps 1 and 2 before starting the interview."
 
     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 the {user_profile['field']} field."}
     ]
     if history:
         messages.extend(history)
     messages.append({"role": "user", "content": message})
 
-    response = client.chat_completion(
-        messages,
-        max_tokens=150,
-        stream=False
-    )
-
+    response = client.chat_completion(messages, max_tokens=150, stream=False)
     return response.choices[0].message.content
 
-
+# Build UI
 with gr.Blocks() as demo:
     user_profile = gr.State({"interview_type": "", "field": ""})
 
     gr.Markdown("# 🎤 Welcome to Intervu")
-
+    
     # Step 1
     gr.Markdown("### Step 1: Choose Interview Type")
     with gr.Row():
-        behavioral_val = gr.Textbox(value="Behavioral", visible=False)
-        technical_val = gr.Textbox(value="Technical", visible=False)
-        college_val = gr.Textbox(value="College", visible=False)
-
         btn1 = gr.Button("Behavioral")
         btn2 = gr.Button("Technical")
         btn3 = gr.Button("College / Scholarship")
+    type_output = gr.Textbox(label="Bot", interactive=False)
 
-    type_out = gr.Textbox(label="Bot", interactive=False)
-
-    btn1.click(set_type, inputs=[behavioral_val, user_profile], outputs=[type_out, user_profile])
-    btn2.click(set_type, inputs=[technical_val, user_profile], outputs=[type_out, user_profile])
-    btn3.click(set_type, inputs=[college_val, user_profile], outputs=[type_out, user_profile])
+    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])
 
     # Step 2
     gr.Markdown("### Step 2: Enter Your Background")
     background = gr.Textbox(label="Your background and field/goal")
-    background_btn = gr.Button("Submit Background")
-    background_out = gr.Textbox(label="Bot", interactive=False)
+    background_btn = gr.Button("Submit")
+    background_output = gr.Textbox(label="Bot", interactive=False)
 
-    background_btn.click(save_background, inputs=[background, user_profile], outputs=[background_out, user_profile])
+    background_btn.click(save_background, inputs=[background, user_profile], outputs=[background_output, user_profile])
 
     # Step 3
     gr.Markdown("### Step 3: Start Interview")
-    chatbot = gr.ChatInterface(
-        fn=lambda msg, hist: respond(msg, hist, user_profile.value),
-        title="Intervu - AI Interview Practice",
-        chatbot=gr.Chatbot(label="Interview Bot"),
-        input_textbox=gr.Textbox(placeholder="Type your answer here..."),
-        type="messages"
-    )
+    chatbot = gr.ChatInterface(fn=lambda msg, hist: respond(msg, hist, user_profile.value), title="Intervu - AI Interview Practice", type="messages")
 
 demo.launch()
-