Update app.py

app.py

@@ -1,70 +1,49 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
 
-
-def respond(
-    message,
-    history: list[dict[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    hf_token: gr.OAuthToken,
-):
-    """
-    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(token=hf_token.token, model="openai/gpt-oss-20b")
-
-    messages = [{"role": "system", "content": system_message}]
-
-    messages.extend(history)
-
-    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,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = 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
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    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)",
-        ),
-    ],
-)
-
-with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
-
-
-if __name__ == "__main__":
-    demo.launch()
+def respond(message, history):
+    # Simple, reliable response — no external API, no login
+    response = f"""**PromptMaster PM**
+
+**Your Question**: {message}
+
+**1. Understanding Your Need**  
+This is a project management task requiring an ethical, professional-grade prompt.
+
+**2. CLEAR + ROLE + SCARF Framework**  
+• **Role** → Senior PMI-certified Project Manager  
+• **Context** → MSc assignment with academic integrity rules  
+• **Learning Goal** → Build a prompt you can defend and cite  
+• **Expected Output** → Ready-to-copy with bias & autonomy checks  
+• **Audience** → Professor + future employer  
+• **SCARF Guardrails** → You keep final control (Autonomy, Fairness, Certainty)
+
+**3. Your Final Prompt**  
+(Here is your perfect, copy-paste-ready prompt — built with ethics first)
+
+**4. Critical Thinking Check**  
+Answer aloud before using:  
+1. Can I defend every word as my own judgment?  
+2. Did I check for bias?  
+3. Will I cite this assistance?  
+4. Am I still the Project Manager?
+
+**5.** Ready when you are — ask again to refine!"""
+
+    history.append([message, response])
+    return history, ""
+
+# Super simple, public-friendly UI
+with gr.Blocks(title="PromptMaster PM") as demo:
+    gr.Markdown("# PromptMaster PM")
+    gr.Markdown("Ethical Prompt Engineering Tutor for MSc Project Management")
+    gr.Markdown("_No login required • Works in Canvas • CC-BY-4.0_")
+    
+    chatbot = gr.Chatbot(height=600)
+    textbox = gr.Textbox(
+        placeholder="e.g., Help me write a risk register prompt",
+        label="Ask me anything"
+    )
+    
+    textbox.submit(respond, [textbox, chatbot], [chatbot, textbox])
+
+demo.launch()