Update app.py

app.py

@@ -56,7 +56,10 @@ def inference(raw_image, model_n, question, strategy):
             answer = model_vq(image_vq, question, train=False, inference='generate') 
         return  'answer: '+answer[0]
     
-inputs = [gr.Image(type='pil'),gr.Radio(choices=['Image Captioning',"Visual Question Answering"], type="value", default="Image Captioning", label="Task"),gr.Textbox(lines=2, label="Question"),gr.Radio(choices=['Beam search','Nucleus sampling'], type="value", default="Nucleus sampling", label="Caption Decoding Strategy")]
+inputs = [gr.Image(type='pil'), 
+          gr.Radio(choices=['Image Captioning',"Visual Question Answering"], type="value", value="Image Captioning", label="Task"),
+          gr.Textbox(lines=2, label="Question"),
+          gr.Radio(choices=['Beam search','Nucleus sampling'], type="value", value="Nucleus sampling", label="Caption Decoding Strategy")]
 outputs = gr.Textbox(label="Output")
 
 title = "BLIP"
@@ -66,12 +69,14 @@ description = "Gradio demo for BLIP: Bootstrapping Language-Image Pre-training f
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2201.12086' target='_blank'>BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation</a> | <a href='https://github.com/salesforce/BLIP' target='_blank'>Github Repo</a></p>"
 
 
-gr.Interface(inference, 
-             inputs, 
-             outputs, 
-             title=title, 
-             description=description, 
-             article=article, 
-             examples=[['starrynight.jpeg',"Image Captioning","None","Nucleus sampling"]],
-             allow_flagging='never',
-             cache_examples=False).queue(concurrency_count=1).launch(show_error=True)
+demo = gr.Interface(inference, 
+                    inputs, 
+                    outputs, 
+                    title=title, 
+                    description=description, 
+                    article=article, 
+                    examples=[['starrynight.jpeg',"Image Captioning","None","Nucleus sampling"]],
+                    allow_flagging='never',
+                    cache_examples="lazy",
+                    delete_cache=(4000, 4000))
+demo.queue(default_concurrency_limit=2).launch(show_error=True)