update app.py

app.py

@@ -1,12 +1,55 @@
 import gradio as gr
+import numpy as np
+import random
+from huggingface_hub import InferenceClient
+import os
 
-def infer(prompt):
-    return f"Hello from: {prompt}"
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 1024
+
+client = InferenceClient(
+    provider="hf-inference",
+    api_key=os.environ["HF_API_TOKEN"]
+)
+
+def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+
+    image = client.text_to_image(
+        prompt=prompt,
+        model="stabilityai/sdxl-turbo",
+        negative_prompt=negative_prompt,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_inference_steps,
+        width=width,
+        height=height,
+        seed=seed,
+    )
+    return image, seed
 
 demo = gr.Interface(
     fn=infer,
-    inputs=gr.Textbox(label="Enter something"),
-    outputs=gr.Textbox(label="Output")
+    inputs=[
+        gr.Textbox(label="Prompt"),
+        gr.Textbox(label="Negative Prompt", value=""),
+        gr.Slider(0, MAX_SEED, label="Seed", value=0),
+        gr.Checkbox(label="Randomize Seed", value=True),
+        gr.Slider(256, MAX_IMAGE_SIZE, label="Width", step=32, value=768),
+        gr.Slider(256, MAX_IMAGE_SIZE, label="Height", step=32, value=768),
+        gr.Slider(0, 10, label="Guidance Scale", step=0.1, value=0.0),
+        gr.Slider(1, 50, label="Steps", step=1, value=2)
+    ],
+    outputs=[
+        gr.Image(label="Generated Image"),
+        gr.Number(label="Seed Used")
+    ],
+    examples=[
+        ["A futuristic cityscape at sunset", "", 0, True, 768, 768, 0.0, 2],
+        ["A cat in a space suit", "", 0, True, 768, 768, 0.0, 2],
+    ],
+    title="SDXL Turbo Text-to-Image",
+    allow_flagging="never"
 )
 
-demo.launch(show_api=False)
+demo.launch(show_api=False)