Update app.py

app.py

@@ -8,7 +8,7 @@ import warnings
 import gradio as gr
 
 # Suppress specific warnings
-warnings.filterwarnings("ignore", message=".*Using the model-agnostic default `max_length`.*")
+warnings.filterwarnings("ignore", message=".*Using the model-agnostic default max_length.*")
 
 # Load environment variables from .env file
 load_dotenv(find_dotenv())
@@ -44,9 +44,17 @@ def generate_caption(image):
         
         # Make the POST request to the endpoint
         response = requests.post(endpoint_url, headers=headers, json=payload)
+        response_data = response.json()
         
         if response.status_code == 200:
-            return response.json().get("generated_text", "No caption generated.")
+            # Handle response as a list or dictionary
+            if isinstance(response_data, list):
+                # Assuming the first item contains the generated text
+                return response_data[0].get("generated_text", "No caption generated.")
+            elif isinstance(response_data, dict):
+                return response_data.get("generated_text", "No caption generated.")
+            else:
+                return f"Unexpected response format: {response_data}"
         else:
             # Log the error response for debugging
             return (
@@ -83,12 +91,13 @@ demo = gr.Interface(
     title="Image Captioning App",
     description=(
         "Upload an image or use one of the predefined samples to generate a caption. "
-        "This app uses a Hugging Face Inference Endpoint for the `Salesforce/blip-image-captioning-base` model."
+        "This app uses a Hugging Face Inference Endpoint for the Salesforce/blip-image-captioning-base model."
     ),
 )
 
 if __name__ == "__main__":
     # Launch the Gradio demo
-    demo.launch()
+    demo.launch()  
+