Create app.py

app.py

@@ -0,0 +1,54 @@
+import os
+import base64
+import requests
+from PIL import Image
+from io import BytesIO
+import gradio as gr
+
+hf_token = os.environ.get('hf_token')
+API_URL = os.environ.get('api_url')
+
+headers = {
+	"Accept" : "application/json",
+	"Authorization": f"Bearer {hf_token}",
+	"Content-Type": "application/json" 
+}
+
+# helper to decode input image
+def decode_base64_image(image_string):
+    base64_image = base64.b64decode(image_string)
+    buffer = BytesIO(base64_image)
+    image = Image.open(buffer)
+    return image
+
+def predict(prompt, temperature, guidance_scale, num_inference_steps, seed):
+    payload = {
+        "inputs": prompt,
+        "temperature": temperature,
+        "guidance_scale": guidance_scale,
+        "num_inference_steps": num_inference_steps,
+        "seed": seed
+        }
+    response = requests.post(API_URL, headers=headers, json=payload)
+    output = response.json()
+    image = decode_base64_image(image_string=output)
+    return image
+
+demo = gr.Interface(
+    predict,
+    inputs=[
+        gr.Textbox(label='Prompt'),
+        gr.Slider(0.1, 5.0, label='Temperature', step=0.1, value=1.0),
+        gr.Slider(0.1, 15.0, label='Guidance Scale', step=0.1, value=7.5),
+        gr.Slider(1, 100, label='Number of inference steps', step=1, value=50),
+        gr.Slider(1, 100, label='Seed', step=1, value=42),
+    ],
+    outputs="image",
+    title="Android toy SD demo",
+    description="Generate images with android toy!! Just specify an android toy somewhere in the prompt or click on the example provided below. The first run could take up to 2 minutes if the model is sleeping, then approximately 10 seconds per one request",
+    examples=[["An android toy near Eiffel Tower", 1.0, 7.5, 50, 42],
+              ["A blue android toy in snow near Eiffel Tower in winter", 1.0, 7.5, 50, 42],
+              ["An android toy flying near Statue of Liberty", 1.0, 7.5, 50, 42]],
+    cache_examples=True
+    )
+demo.launch()