Update app.py

app.py

@@ -9,6 +9,8 @@ import spaces
 from cachetools import TTLCache
 from cachetools.func import ttl_cache
 import time
+import os
+os.environ['HF_TRANSFER'] = "1"
 # Set up logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -94,25 +96,19 @@ 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 = None) -> str:
+def summarize(hub_id: str = "") -> str:
     """Interface function for Gradio. Returns JSON format."""
     try:
         if hub_id:
-            # 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 f'{{"error": "{error_msg}"}}'
-            card_type = inferred_type
+            # Fetch and infer card type automatically
+            card_type, card_text = get_card_info(hub_id)
+            # Use the cached wrapper
+            summary = generate_summary(card_text, card_type)
+            return f'{{"summary": "{summary}", "type": "{card_type}", "hub_id": "{hub_id}"}}'
         else:
             error_msg = "Error: Hub ID must be provided"
             return f'{{"error": "{error_msg}"}}'
 
-        # Use the cached wrapper
-        summary = generate_summary(card_text, card_type)
-        return f'{{"summary": "{summary}", "type": "{card_type}", "hub_id": "{hub_id}"}}'
-
     except Exception as e:
         error_msg = str(e)
         return f'{{"error": "{error_msg}"}}'
@@ -120,13 +116,10 @@ def summarize(hub_id: str = "", card_type: str = None) -> str:
 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", None], label="Card Type (optional)", value=None),
-        ],
+        inputs=gr.Textbox(label="Hub ID", placeholder="e.g., huggingface/llama-7b"),
         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. Leave card type empty for automatic detection.",
+        description="Generate concise summaries of model and dataset cards from the Hugging Face Hub.",
     )
     return interface