Update app.py

app.py

@@ -1,12 +1,12 @@
 import gradio as gr
-from huggingface_hub import InferenceApi
+from huggingface_hub import InferenceClient
 import requests
 from PIL import Image
 import io
 
-# Initialize the Hugging Face Inference API
+# Initialize the Hugging Face Inference Client
 model_id = "Salesforce/blip-image-captioning-large"
-api = InferenceApi(repo_id=model_id)
+client = InferenceClient(model=model_id)
 
 def caption_image(image):
     # Convert the PIL image to bytes
@@ -15,7 +15,7 @@ def caption_image(image):
     img_bytes = buffered.getvalue()
     
     # Call the Hugging Face inference API
-    response = api(inputs=img_bytes)
+    response = client.image_to_text(inputs=img_bytes)
     
     # Check the response and format it properly
     if isinstance(response, list) and response:
@@ -26,7 +26,7 @@ def caption_image(image):
 # Set up the Gradio interface
 interface = gr.Interface(
     fn=caption_image,
-    inputs=gr.inputs.Image(type="pil"),
+    inputs=gr.Image(type="pil"),
     outputs="text",
     title="Image Captioning",
     description="Generate captions for images using the BLIP model."