Update app.py

app.py

@@ -1,6 +1,115 @@
+import gradio as gr
+import openai
+
+# =========================
+# 1) OpenAI API Key
+# =========================
+openai.api_key = "YOUR_OPENAI_API_KEY"
+
+# =========================
+# 2) Recruiter first lines
+# =========================
+FIRST_LINES = {
+    "Friendly": "I see you took a few years off. That’s interesting — tell me more about what you learned during that time.",
+    "Tough": "A gap that long raises questions. Why should we consider you over someone with recent experience?"
+}
+
+# =========================
+# 3) GPT reply for recruiter
+# =========================
+def get_recruiter_reply(user_text, style, history):
+    prompt = f"""
+    You are a recruiter in an interview. Tone = {style} (friendly or tough).
+    Conversation so far:
+    {history}
+    Candidate just said: {user_text}
+    Rules:
+    - Keep replies under 25 words
+    - Ask one probing question at a time
+    - Avoid repeating previous questions
+    Context: mid-career woman re-entering the workforce
+    Return the next recruiter question only.
+    """
+    response = openai.ChatCompletion.create(
+        model="gpt-4o-mini",
+        messages=[{"role":"user", "content":prompt}]
+    )
+    return response.choices[0].message.content.strip()
+
+# =========================
+# 4) GPT feedback after 10 exchanges
+# =========================
+def get_feedback(history):
+    prompt = f"""
+    Based on this 10-turn transcript:
+    {history}
+    Return concise feedback:
+    - Confidence (0-10)
+    - Strengths (2 bullets)
+    - One improvement tip
+    - Example reframe sentence (<=20 words)
+    """
+    response = openai.ChatCompletion.create(
+        model="gpt-4o-mini",
+        messages=[{"role":"user", "content":prompt}]
+    )
+    return response.choices[0].message.content.strip()
+
+# =========================
+# 5) Dummy TTS function (Gradio handles text-to-speech)
+# =========================
 def speak(text):
     """
     No external TTS API needed.
-    Gradio will handle text-to-speech automatically in the Audio block.
+    Gradio will synthesize audio automatically.
     """
     return text
+
+# =========================
+# 6) Conversation handler
+# =========================
+def run_boosty(style, user_voice, history="", turn=1):
+    # Step 1: First recruiter line
+    if turn == 1:
+        first_line = FIRST_LINES[style]
+        history += f"Recruiter ({style}): {first_line}\n"
+        audio = speak(first_line)
+        return "", history, audio, turn + 1, ""
+    
+    # Steps 2-10: transcribe user voice using OpenAI Whisper API
+    with open(user_voice.name, "rb") as f:
+        transcription = openai.Audio.transcriptions.create(file=f, model="whisper-1")["text"]
+    
+    history += f"User: {transcription}\n"
+    
+    # After 10 exchanges → feedback
+    if turn > 10:
+        feedback = get_feedback(history)
+        return "", history, None, turn, feedback
+    
+    # Generate next recruiter line
+    reply = get_recruiter_reply(transcription, style, history)
+    history += f"Recruiter: {reply}\n"
+    audio = speak(reply)
+    
+    return "", history, audio, turn + 1, ""
+
+# =========================
+# 7) Gradio interface
+# =========================
+with gr.Blocks() as demo:
+    style_var = gr.Radio(["Friendly", "Tough"], label="Choose recruiter style")
+    user_voice = gr.Audio(source="microphone", type="file", label="Speak your reply")
+    history = gr.Textbox(label="Transcript", interactive=False)
+    audio_output = gr.Audio(label="Recruiter voice", type="auto", interactive=False)
+    turn_var = gr.State(value=1)
+    feedback_text = gr.Textbox(label="Feedback", interactive=False)
+    
+    submit_btn = gr.Button("Next")
+    submit_btn.click(
+        fn=run_boosty,
+        inputs=[style_var, user_voice, history, turn_var],
+        outputs=[style_var, history, audio_output, turn_var, feedback_text]
+    )
+
+demo.launch()