Update

app.py

@@ -1,11 +1,8 @@
 from __future__ import annotations
 
-import os
-
 import gradio as gr
 import torch
 from gradio_client import Client
-from gradio_client.client import Job
 
 DESCRIPTION = "# Comparing image captioning models"
 ORIGINAL_SPACE_INFO = """\
@@ -26,31 +23,28 @@ torch.hub.download_url_to_file(
 )
 
 
-def generate_caption_git(image_path: str, return_job: bool = False) -> str | Job:
+def generate_caption_git(image_path: str) -> str:
     try:
         client = Client("hysts/image-captioning-with-git")
-        fn = client.submit if return_job else client.predict
-        return fn(image_path, api_name="/caption")
+        return client.predict(image_path, api_name="/caption")
     except Exception:
         gr.Warning("The GIT-large Space is currently unavailable. Please try again later.")
         return ""
 
 
-def generate_caption_blip(image_path: str, return_job: bool = False) -> str | Job:
+def generate_caption_blip(image_path: str) -> str:
     try:
         client = Client("hysts/image-captioning-with-blip")
-        fn = client.submit if return_job else client.predict
-        return fn(image_path, "A picture of", api_name="/caption")
+        return client.predict(image_path, "A picture of", api_name="/caption")
     except Exception:
         gr.Warning("The BLIP-large Space is currently unavailable. Please try again later.")
         return ""
 
 
-def generate_caption_blip2_opt(image_path: str, return_job: bool = False) -> str | Job:
+def generate_caption_blip2_opt(image_path: str) -> str:
     try:
         client = Client("merve/BLIP2-with-transformers")
-        fn = client.submit if return_job else client.predict
-        return fn(
+        return client.predict(
             image_path,
             "Beam search",
             1,  # temperature
@@ -63,11 +57,10 @@ def generate_caption_blip2_opt(image_path: str, return_job: bool = False) -> str
         return ""
 
 
-def generate_caption_blip2_t5xxl(image_path: str, return_job: bool = False) -> str | Job:
+def generate_caption_blip2_t5xxl(image_path: str) -> str:
     try:
         client = Client("hysts/BLIP2")
-        fn = client.submit if return_job else client.predict
-        return fn(
+        return client.predict(
             image_path,
             "Beam search",
             1,  # temperature
@@ -84,11 +77,10 @@ def generate_caption_blip2_t5xxl(image_path: str, return_job: bool = False) -> s
         return ""
 
 
-def generate_caption_instructblip(image_path: str, return_job: bool = False) -> str | Job:
+def generate_caption_instructblip(image_path: str) -> str:
     try:
         client = Client("hysts/InstructBLIP")
-        fn = client.submit if return_job else client.predict
-        return fn(
+        return client.predict(
             image_path,
             "Describe the image.",
             "Beam search",
@@ -106,28 +98,15 @@ def generate_caption_instructblip(image_path: str, return_job: bool = False) ->
         return ""
 
 
-def generate_caption_fuyu(image_path: str, return_job: bool = False) -> str | Job:
+def generate_caption_fuyu(image_path: str) -> str:
     try:
         client = Client("adept/fuyu-8b-demo")
-        fn = client.submit if return_job else client.predict
-        return fn(image_path, "Generate a coco style caption.\n", fn_index=3)
+        return client.predict(image_path, "Generate a coco style caption.\n", fn_index=3)
     except Exception:
         gr.Warning("The Fuyu-8B Space is currently unavailable. Please try again later.")
         return ""
 
 
-def generate_captions(image_path: str) -> tuple[str, str, str, str, str, str]:
-    jobs = [
-        generate_caption_git(image_path, return_job=True),
-        generate_caption_blip(image_path, return_job=True),
-        generate_caption_blip2_opt(image_path, return_job=True),
-        generate_caption_blip2_t5xxl(image_path, return_job=True),
-        generate_caption_instructblip(image_path, return_job=True),
-        generate_caption_fuyu(image_path, return_job=True),
-    ]
-    return tuple(job.result() if job else "" for job in jobs)
-
-
 with gr.Blocks(css="style.css") as demo:
     gr.Markdown(DESCRIPTION)
     with gr.Row():
@@ -142,14 +121,6 @@ with gr.Blocks(css="style.css") as demo:
             out_instructblip = gr.Textbox(label="InstructBLIP")
             out_fuyu = gr.Textbox(label="Fuyu-8B")
 
-    outputs = [
-        out_git,
-        out_blip,
-        out_blip2_opt,
-        out_blip2_t5xxl,
-        out_instructblip,
-        out_fuyu,
-    ]
     gr.Examples(
         examples=[
             "cats.jpg",
@@ -157,20 +128,26 @@ with gr.Blocks(css="style.css") as demo:
             "astronaut.jpg",
         ],
         inputs=input_image,
-        outputs=outputs,
-        fn=generate_captions,
-        cache_examples=os.getenv("CACHE_EXAMPLES") == "1",
     )
 
     with gr.Accordion(label="The original Spaces can be found here:", open=False):
         gr.Markdown(ORIGINAL_SPACE_INFO)
 
-    run_button.click(
-        fn=generate_captions,
-        inputs=input_image,
-        outputs=outputs,
-        api_name="caption",
-    )
+    fn_out_pairs = [
+        (generate_caption_git, out_git),
+        (generate_caption_blip, out_blip),
+        (generate_caption_blip2_opt, out_blip2_opt),
+        (generate_caption_blip2_t5xxl, out_blip2_t5xxl),
+        (generate_caption_instructblip, out_instructblip),
+        (generate_caption_fuyu, out_fuyu),
+    ]
+    for fn, out in fn_out_pairs:
+        run_button.click(
+            fn=fn,
+            inputs=input_image,
+            outputs=out,
+            api_name=False,
+        )
 
 if __name__ == "__main__":
-    demo.queue(max_size=20).launch()
+    demo.queue(max_size=20, api_open=False).launch(show_api=False)

style.css

@@ -2,4 +2,3 @@ h1 {
   text-align: center;
   display: block;
 }
-