Update app.py

app.py

@@ -11,61 +11,72 @@ def respond(
     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")
+    # Initialize client (model kept internal)
+    client = InferenceClient(
+        token=hf_token.token,
+        model="openai/gpt-oss-20b"
+    )
 
-    messages = [{"role": "system", "content": system_message}]
+    # 🔥 Strong hidden finance instruction
+    system_prompt = (
+        "You are a professional financial advisor. "
+        "Answer all questions related to finance, investments, risk, valuation, and markets. "
+        "Provide clear explanations, use proper financial terminology, "
+        "and include step-by-step calculations when required."
+    )
 
+    messages = [{"role": "system", "content": system_prompt}]
+
+    # Add chat history
     messages.extend(history)
 
+    # Add user message
     messages.append({"role": "user", "content": message})
 
     response = ""
 
-    for message in client.chat_completion(
+    # Streaming response
+    for msg 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
+        if msg.choices and msg.choices[0].delta.content:
+            token = msg.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
-"""
+# ==============================
+# UI
+# ==============================
+
 chatbot = 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)",
+        gr.Textbox(
+            value="Ask any finance-related question.",
+            label="Instructions"
         ),
+        gr.Slider(1, 2048, value=512, step=1, label="Response Length"),
+        gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Creativity"),
+        gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Response Diversity"),
     ],
 )
 
 with gr.Blocks() as demo:
+    gr.Markdown("# 💰 Finance Chatbot")
+    gr.Markdown("Ask questions about investments, risk, valuation, and financial concepts.")
+
     with gr.Sidebar():
         gr.LoginButton()
+
     chatbot.render()
 
 
 if __name__ == "__main__":
     demo.launch()
-
-this is the app.py already given as a template in gradio so give your code accordingly