Update app.py

app.py

@@ -94,42 +94,39 @@ def generate_summary(card_text: str, card_type: str) -> str:
     """Cached wrapper for generate_summary with TTL."""
     return _generate_summary_gpu(card_text, card_type)
 
-def summarize(hub_id: str = "", card_type: str = "model") -> Tuple[str, str]:
-    """Interface function for Gradio. Returns both text and JSON formats."""
+def summarize(hub_id: str = "", card_type: str = None) -> str:
+    """Interface function for Gradio. Returns JSON format."""
     try:
         if hub_id:
-            # Fetch and validate card type
+            # Fetch and infer card type
             inferred_type, card_text = get_card_info(hub_id)
+            # Only validate if card_type was explicitly provided
             if card_type and card_type != inferred_type:
                 error_msg = f"Error: Provided card_type '{card_type}' doesn't match inferred type '{inferred_type}'"
-                return error_msg, f'{{"error": "{error_msg}"}}'
+                return f'{{"error": "{error_msg}"}}'
             card_type = inferred_type
         else:
             error_msg = "Error: Hub ID must be provided"
-            return error_msg, f'{{"error": "{error_msg}"}}'
+            return f'{{"error": "{error_msg}"}}'
 
         # Use the cached wrapper
         summary = generate_summary(card_text, card_type)
-        json_output = f'{{"summary": "{summary}", "type": "{card_type}", "hub_id": "{hub_id}"}}'
-        return summary, json_output
+        return f'{{"summary": "{summary}", "type": "{card_type}", "hub_id": "{hub_id}"}}'
 
     except Exception as e:
         error_msg = str(e)
-        return f"Error: {error_msg}", f'{{"error": "{error_msg}"}}'
+        return f'{{"error": "{error_msg}"}}'
 
 def create_interface():
     interface = gr.Interface(
         fn=summarize,
         inputs=[
             gr.Textbox(label="Hub ID", placeholder="e.g., huggingface/llama-7b"),
-            gr.Radio(choices=["model", "dataset"], label="Card Type", value="model"),
-        ],
-        outputs=[
-            gr.Textbox(label="Summary"),
-            gr.JSON(label="JSON Output")
+            gr.Radio(choices=["model", "dataset", None], label="Card Type (optional)", value=None),
         ],
+        outputs=gr.JSON(label="Output"),
         title="Hugging Face Hub TLDR Generator",
-        description="Generate concise summaries of model and dataset cards from the Hugging Face Hub.",
+        description="Generate concise summaries of model and dataset cards from the Hugging Face Hub. Leave card type empty for automatic detection.",
     )
     return interface