Upload folder using huggingface_hub

app.py

@@ -1,46 +1,73 @@
 import os
+import logging
 import gradio as gr
 from huggingface_hub import InferenceClient
 
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s | %(levelname)s | %(message)s",
+    datefmt="%Y-%m-%d %H:%M:%S",
+)
+logger = logging.getLogger(__name__)
+
 # Get token from environment (set in HF Space secrets)
 HF_TOKEN = os.environ.get("HF_TOKEN", "")
+logger.info(f"HF_TOKEN configured: {bool(HF_TOKEN)}")
+
 client = InferenceClient(token=HF_TOKEN) if HF_TOKEN else InferenceClient()
+logger.info("InferenceClient initialized")
 
 
 def caption_image(image):
     """Generate a caption for the image."""
+    logger.info(f"caption_image() called, image: {image is not None}")
+    
     if image is None:
+        logger.warning("No image provided")
         return "📷 Upload an image first!"
     
     try:
+        logger.info("Calling image_to_text API...")
         result = client.image_to_text(
             image,
             model="Salesforce/blip-image-captioning-base",
         )
+        logger.info(f"Caption: {result.generated_text[:100]}")
         return result.generated_text
     except Exception as e:
+        logger.error(f"API error: {e}")
         return f"❌ Error: {e}"
 
 
 def answer_question(image, question: str):
     """Answer a question about the image."""
+    logger.info(f"answer_question() called, image: {image is not None}, question: {question[:50] if question else 'None'}")
+    
     if image is None:
+        logger.warning("No image provided")
         return "📷 Upload an image first!"
     if not question.strip():
+        logger.warning("No question provided")
         return "❓ Ask a question!"
     
     try:
+        logger.info("Calling visual_question_answering API...")
         result = client.visual_question_answering(
             image=image,
             question=question,
             model="dandelin/vilt-b32-finetuned-vqa",
         )
         top = result[0]
+        logger.info(f"Answer: {top.answer} ({top.score:.1%})")
         return f"🤖 {top.answer} (confidence: {top.score:.1%})"
     except Exception as e:
+        logger.error(f"API error: {e}")
         return f"❌ Error: {e}"
 
 
+logger.info("Building Gradio interface...")
+
 with gr.Blocks(title="Vision Chat") as demo:
     gr.Markdown("# 👁️ Vision Chat\nUpload an image, get a caption, and ask questions about it!")
 
@@ -60,4 +87,5 @@ with gr.Blocks(title="Vision Chat") as demo:
     question.submit(answer_question, inputs=[img, question], outputs=answer_out)
 
 demo.queue()
+logger.info("Starting Gradio server...")
 demo.launch()