Fix blank Space by calling demo.launch()

app.py

@@ -11,25 +11,19 @@ def respond(
     top_p,
     hf_token: gr.OAuthToken,
 ):
-    """
-    Uses the Hugging Face InferenceClient with a token (OAuth) to access the model.
-    This works with any text-to-text model like BART, T5, Pegasus, etc.
-    """
     client = InferenceClient(
         token=hf_token.token,
         model="Bocklitz-Lab/lit2vec-tldr-bart-model"
     )
 
-    # Construct input text (optionally prepend system message)
     full_input = f"{system_message.strip()}\n\n{message.strip()}"
 
-    # Generate full response in one call
     response = client.text_generation(
         full_input,
         max_new_tokens=max_tokens,
         temperature=temperature,
         top_p=top_p,
-        stream=False  # Set to True for token streaming
+        stream=False
     )
 
     yield response
@@ -38,20 +32,21 @@ def respond(
 chatbot = gr.ChatInterface(
     respond,
     chatbot=gr.Chatbot(),
-    textbox=gr.Textbox(placeholder="Enter text to summarize...", container=False, scale=7),
+    textbox=gr.Textbox(placeholder="Paste abstract of a chemistry paper...", container=False, scale=7),
     additional_inputs=[
-        gr.Textbox(value="Summarize the following scientific text.", label="System message"),
+        gr.Textbox(value="Summarize this chemistry paper abstract:", label="System message"),
         gr.Slider(minimum=16, maximum=1024, value=256, step=8, 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"),
     ],
 )
 
-with gr.Blocks() as demo:
+demo = gr.Blocks()
+
+with demo:
     with gr.Sidebar():
         gr.LoginButton()
     chatbot.render()
 
-
-if __name__ == "__main__":
-    demo.launch()
+# 👇 This MUST be called at the module level for Hugging Face Spaces to work
+demo.launch()