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app.py

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+import io
+import os
+import warnings
+
+from IPython.display import display
+from PIL import Image
+from stability_sdk import client
+import stability_sdk.interfaces.gooseai.generation.generation_pb2 as generation
+
+import gradio as gr
+stability_api = client.StabilityInference(
+    key=os.environ["Secret"], 
+    verbose=True,
+)
+
+
+def infer(prompt):
+  # the object returned is a python generator
+  answers = stability_api.generate(
+      prompt=prompt
+  )
+  
+  # iterating over the generator produces the api response
+  for resp in answers:
+      for artifact in resp.artifacts:
+          if artifact.finish_reason == generation.FILTER:
+              warnings.warn(
+                  "Your request activated the API's safety filters and could not be processed."
+                  "Please modify the prompt and try again.")
+          if artifact.type == generation.ARTIFACT_IMAGE:
+              img = Image.open(io.BytesIO(artifact.binary))
+              return img
+
+
+block = gr.Blocks(css=".container { max-width: 600px; margin: auto; }")
+
+num_samples = 1
+
+
+
+with block as demo:
+    gr.Markdown("<h1><center>Stable Diffusion</center></h1>")
+    gr.Markdown(
+        "Get an image for any prompt you provide!"
+    )
+    with gr.Group():
+        with gr.Box():
+            with gr.Row().style(mobile_collapse=False, equal_height=True):
+
+                text = gr.Textbox(
+                    label="Enter your prompt", show_label=False, max_lines=1
+                ).style(
+                    border=(True, False, True, True),
+                    rounded=(True, False, False, True),
+                    container=False,
+                )
+                btn = gr.Button("Run").style(
+                    margin=False,
+                    rounded=(False, True, True, False),
+                )
+        
+               
+        gallery = gr.Image()
+        text.submit(infer, inputs=[text], outputs=gallery)
+        btn.click(infer, inputs=[text], outputs=gallery)
+
+   
+    
+
+
+demo.launch()