Update app.py

app.py

@@ -5,36 +5,33 @@ import requests
 API_URL = "https://api-inference.huggingface.co/models/nasa-impact/nasa-smd-ibm-v0.1"
 headers = {"Authorization": "Bearer HF_TOKEN"}
 
-def query_huggingface(payload):
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.json()
-
-# Function to generate response
-def generate_response(user_message):
+def query_huggingface():
     payload = {
-        "inputs": user_message
+        "inputs": "The answer to the universe is <mask>."
     }
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
 
-    response = query_huggingface(payload)
+def get_model_output():
+    response = query_huggingface()
+    # Extract the output from the response
     output = response.get('generated_text', 'No response')  # Adjust according to the model's response format
-
     return output
 
 # Gradio interface
-def gradio_interface(user_message, history):
-    response = generate_response(user_message)
-    history.append((user_message, response))
-    return history, history
+def gradio_interface():
+    return get_model_output()
 
 # Define Gradio blocks
-with gr.Blocks() as demo:
-    user_message = gr.Textbox(label="Your Message")
-    chatbot = gr.Chatbot(label="Chat History")
-    state = gr.State([])
-    submit_button = gr.Button("Submit")
-
-    submit_button.click(gradio_interface, inputs=[user_message, state], outputs=[chatbot, state])
+demo = gr.Interface(
+    fn=gradio_interface,
+    inputs=[],
+    outputs="text",
+    title="Hugging Face Model Output",
+    description="Feed a hard-coded input to the model and get the output."
+)
 
 # Launch the interface
 demo.launch()
 
+