Update app.py

app.py

@@ -1,64 +1,44 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+# ====== 1) TEXT LINES (Scenario 1, Turn 1) ======
+OPPONENT_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?"
+}
+
+# ====== 2) AUDIO LINKS (REPLACE with your raw GitHub URLs) ======
+AUDIO_URLS = {
+    "Friendly": "https://raw.githubusercontent.com/sandmonette-jp/boosty-beta-prototype/main/Scenario%201%20Value%20My%20B%20-%20Friendly%20-%20Turn%201.mp3",
+    "Tough": "https://rawgithubusercontent.com/sandmonette-jp/boosty-beta-prototype/main/Scenario%201%20Value%20My%20B%20-%20Tough%20-%20Turn%201.mp3",
+}
+
+def play_turn(tone):
+    """
+    Returns: (opponent_text, audio_url)
+    """
+    text = OPPONENT_LINES[tone]
+    audio_url = AUDIO_URLS[tone]
+    return text, audio_url
+
+with gr.Blocks(title="Boosty — Beta Prototype") as demo:
+    gr.Markdown(
+        "# Boosty — Scenario 1: Valuing Your Career Break\n"
+        "Select a tone, then click **Play Turn 1**. Reply in the textbox if you want.\n"
+        "_(Tip: You’ll hear the voice after clicking the button.)_"
+    )
+
+    with gr.Row():
+        tone = gr.Radio(["Friendly", "Tough"], value="Friendly", label="Opponent Tone")
+        play_btn = gr.Button("▶️ Play Turn 1")
+
+    opponent_text = gr.Markdown(label="Opponent")
+    opponent_audio = gr.Audio(label="Opponent Voice", autoplay=True, interactive=False)
+    user_reply = gr.Textbox(label="Your reply (optional)", placeholder="Type your response here...")
+
+    # (Optional) quick reflection widgets:
+    with gr.Accordion("Post-session quick check (optional)", open=False):
+        conf = gr.Slider(1, 5, value=3, step=1, label="How confident did you feel?")
+        refl = gr.Textbox(label="What would you do differently next time?")
+
+    play_btn.click(fn=play_turn, inputs=[tone], outputs=[opponent_text, opponent_audio])
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
     demo.launch()