Update app.py

app.py

@@ -1,133 +1,57 @@
-# import gradio as gr
-# from huggingface_hub import InferenceClient
-
-# client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") #change LLM
-
-# def respond(message, history):
-#     messages = [{"role": "system", "content": "You are a professional Interviewer and you are asking questions based on interview choices"}]
-#     if history:
-#         messages.extend(history)
-#     messages.append({"role": "user", "content": message})
-    
-#     response = ""
-#     for message in client.chat_completion(
-#         messages,
-#         max_tokens=100,
-#         stream=True,
-        
-#     ):
-#         token = message.choices[0].delta.content
-#         response += token
-#         yield response
-
-# chatbot = gr.ChatInterface(respond, type="messages")
-# chatbot.launch() 
 import gradio as gr
+from huggingface_hub import InferenceClient
 
-# In-memory user profile
-user_profile = {
-    "interview_type": "",
-    "field": "",
-    "mode": "",
-    "responses": []
-}
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") #change LLM
 
-# Question bank
-questions = {
-    "technical": {
-        "software": [
-            "Can you explain a recent project where you solved a technical challenge?",
-            "How would you optimize a slow-running algorithm?"
-        ],
-        "general": [
-            "Explain Big O Notation.",
-            "What’s a common bug and how do you fix it?"
-        ]
-    },
-    "behavioral": {
-        "general": [
-            "Tell me about a time you had to overcome a challenge.",
-            "How do you handle feedback?"
-        ]
-    },
-    "college": {
-        "general": [
-            "Why do you want to attend this school?",
-            "What extracurricular activity means the most to you and why?"
-        ]
-    }
+user_profile = {
+    "interview_type": None,
+    "field": None,
+    "mode": "text",
+    "stage": "select_type",  # stages: select_type → get_background → interview → done
 }
 
-# Phase 1: Choose interview type
-def set_type(choice):
-    user_profile["interview_type"] = choice.lower()
-    return "Great! What’s your background and what field/role are you aiming for?"
-
-# Phase 2: Save background
-def save_background(info):
-    user_profile["field"] = info
-    return "Would you like to continue with Text, Audio, or Webcam interview?"
-
-# Phase 3: Set mode
-def set_mode(choice):
-    user_profile["mode"] = choice.lower()
-    return f"Starting {choice} interview... Type 'done' anytime to finish."
-
-# Phase 4: Ask question
-def start_interview(user_input):
-    if user_input.lower() == "done":
-        return "Interview finished! We'll provide feedback shortly."
-
-    user_profile["responses"].append(user_input)
-
-    itype = user_profile["interview_type"]
-    field = user_profile["field"].lower()
-
-    field_key = "software" if "software" in field else "general"
-    question_list = questions.get(itype, {}).get(field_key, [])
-
-    if len(user_profile["responses"]) < len(question_list):
-        return question_list[len(user_profile["responses"])]
-    else:
-        return "Thank you! You've completed all questions. Type 'done' to finish."
-
-# UI construction
-with gr.Blocks() as demo:
-    gr.Markdown("# 🎤 Welcome to Intervu")
-
-    with gr.Row():
-        gr.Markdown("## Step 1: Choose Interview Type")
-        type_out = gr.Textbox(label="Bot Response")
-
-    with gr.Row():
-        btn1 = gr.Button("Behavioral")
-        btn2 = gr.Button("Technical")
-        btn3 = gr.Button("College / Scholarship")
-
-    btn1.click(set_type, inputs=[], outputs=type_out, _js="() => 'Behavioral'")
-    btn2.click(set_type, inputs=[], outputs=type_out, _js="() => 'Technical'")
-    btn3.click(set_type, inputs=[], outputs=type_out, _js="() => 'College'")
-
-    gr.Markdown("## Step 2: Enter Background")
-    background = gr.Textbox(label="Your background + field/goal")
-    background_btn = gr.Button("Submit Background")
-    mode_out = gr.Textbox(label="Bot Response")
-
-    background_btn.click(save_background, inputs=background, outputs=mode_out)
-
-    gr.Markdown("## Step 3: Choose Mode")
-    btn_text = gr.Button("Text")
-    btn_audio = gr.Button("Audio (WIP)")
-    btn_webcam = gr.Button("Webcam (WIP)")
-    mode_feedback = gr.Textbox(label="Bot Response")
-
-    btn_text.click(set_mode, inputs=[], outputs=mode_feedback, _js="() => 'Text'")
-    btn_audio.click(set_mode, inputs=[], outputs=mode_feedback, _js="() => 'Audio'")
-    btn_webcam.click(set_mode, inputs=[], outputs=mode_feedback, _js="() => 'Webcam'")
-
-    gr.Markdown("## Step 4: Text Interview")
-    user_input = gr.Textbox(label="Your Response")
-    bot_reply = gr.Textbox(label="Bot Question")
-    user_input.submit(start_interview, inputs=user_input, outputs=bot_reply)
+def respond(message, history):
+    global user_profile
+
+    # Stage 1: Choose interview type
+    if user_profile["stage"] == "select_type":
+        user_profile["interview_type"] = message.lower()
+        user_profile["stage"] = "get_background"
+        yield f"Great! What’s your background and what field are you aiming for?"
+        return
+
+    # Stage 2: Get background info
+    elif user_profile["stage"] == "get_background":
+        user_profile["field"] = message
+        user_profile["stage"] = "interview"
+        yield f"Thanks! Let’s begin your {user_profile['interview_type']} interview. Type 'start' to begin."
+        return
+
+    # Stage 3: Start asking interview questions
+    elif user_profile["stage"] == "interview":
+        if message.lower() == "start":
+            intro = f"Let’s begin! I’ll ask you questions based on a {user_profile['interview_type']} interview in {user_profile['field']}."
+            return_stream = client.text_generation(
+                f"Ask a good first interview question for a {user_profile['interview_type']} interview in the {user_profile['field']} field.",
+                max_tokens=100,
+                stream=True
+            )
+            for token in return_stream:
+                yield intro + "\n\n" + token
+        elif message.lower() == "done":
+            user_profile["stage"] = "done"
+            yield "Thanks for completing the interview! I’ll now evaluate your performance... (WIP)"
+        else:
+            messages = [{"role": "system", "content": "You are a professional interviewer. Give feedback or ask follow-up questions."}]
+            messages.extend(history)
+            messages.append({"role": "user", "content": message})
+            response = ""
+            for message in client.chat_completion(messages, max_tokens=100, stream=True):
+                token = message.choices[0].delta.content
+                response += token
+                yield response
+
+
+chatbot = gr.ChatInterface(respond, type="messages", title="Intervu - AI Interview Practice")
+chatbot.launch()
 
-demo.launch()