Update app.py

app.py

@@ -94,74 +94,43 @@ 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", content: str = "") -> str:
-    """Interface function for Gradio."""
+def summarize(hub_id: str = "", card_type: str = "model") -> Tuple[str, str]:
+    """Interface function for Gradio. Returns both text and JSON formats."""
     try:
         if hub_id:
             # Fetch and validate card type
             inferred_type, card_text = get_card_info(hub_id)
             if card_type and card_type != inferred_type:
-                return f"Error: Provided card_type '{card_type}' doesn't match inferred 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}"}}'
             card_type = inferred_type
-        elif content:
-            if not card_type:
-                return "Error: card_type must be provided when using direct content"
-            card_text = content
         else:
-            return "Error: Either hub_id or content must be provided"
+            error_msg = "Error: Hub ID must be provided"
+            return error_msg, f'{{"error": "{error_msg}"}}'
 
         # Use the cached wrapper
         summary = generate_summary(card_text, card_type)
-        return summary
+        json_output = f'{{"summary": "{summary}", "type": "{card_type}", "hub_id": "{hub_id}"}}'
+        return summary, json_output
 
     except Exception as e:
-        return f"Error: {str(e)}"
+        error_msg = str(e)
+        return f"Error: {error_msg}", f'{{"error": "{error_msg}"}}'
 
-# Create the Gradio interface
 def create_interface():
-    with gr.Blocks(title="Hub TLDR") as interface:
-        gr.Markdown("# Hugging Face Hub TLDR Generator")
-        gr.Markdown("Generate concise summaries of model and dataset cards from the Hugging Face Hub.")
-        
-        with gr.Tab("Summarize by Hub ID"):
-            hub_id_input = gr.Textbox(
-                label="Hub ID",
-                placeholder="e.g., huggingface/llama-7b"
-            )
-            hub_id_type = gr.Radio(
-                choices=["model", "dataset"],
-                label="Card Type (optional)",
-                value="model"
-            )
-            hub_id_button = gr.Button("Generate Summary")
-            hub_id_output = gr.Textbox(label="Summary")
-            
-            hub_id_button.click(
-                fn=summarize,
-                inputs=[hub_id_input, hub_id_type],
-                outputs=hub_id_output
-            )
-
-        with gr.Tab("Summarize Custom Content"):
-            content_input = gr.Textbox(
-                label="Content",
-                placeholder="Paste your model or dataset card content here...",
-                lines=10
-            )
-            content_type = gr.Radio(
-                choices=["model", "dataset"],
-                label="Card Type",
-                value="model"
-            )
-            content_button = gr.Button("Generate Summary")
-            content_output = gr.Textbox(label="Summary")
-            
-            content_button.click(
-                fn=lambda content, card_type: summarize(content=content, card_type=card_type),
-                inputs=[content_input, content_type],
-                outputs=content_output
-            )
-
+    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")
+        ],
+        title="Hugging Face Hub TLDR Generator",
+        description="Generate concise summaries of model and dataset cards from the Hugging Face Hub.",
+    )
     return interface
 
 if __name__ == "__main__":