chore: import upstream snapshot with attribution

doc/source/serve/doc_code/stable_diffusion.py

@@ -0,0 +1,88 @@
+# __example_code_start__
+
+from io import BytesIO
+from fastapi import FastAPI
+from fastapi.responses import Response
+import torch
+
+from ray import serve
+from ray.serve.handle import DeploymentHandle
+
+
+app = FastAPI()
+
+
+@serve.deployment(num_replicas=1)
+@serve.ingress(app)
+class APIIngress:
+    def __init__(self, diffusion_model_handle: DeploymentHandle) -> None:
+        self.handle = diffusion_model_handle
+
+    @app.get(
+        "/imagine",
+        responses={200: {"content": {"image/png": {}}}},
+        response_class=Response,
+    )
+    async def generate(self, prompt: str, img_size: int = 512):
+        assert len(prompt), "prompt parameter cannot be empty"
+
+        image = await self.handle.generate.remote(prompt, img_size=img_size)
+        file_stream = BytesIO()
+        image.save(file_stream, "PNG")
+        return Response(content=file_stream.getvalue(), media_type="image/png")
+
+
+@serve.deployment(
+    ray_actor_options={"num_gpus": 1},
+    autoscaling_config={"min_replicas": 0, "max_replicas": 2},
+)
+class StableDiffusionXL:
+    def __init__(self):
+        from diffusers import DiffusionPipeline
+
+        model_id = "stabilityai/stable-diffusion-xl-base-1.0"
+
+        self.pipe = DiffusionPipeline.from_pretrained(
+            model_id, torch_dtype=torch.float16, variant="fp16", use_safetensors=True
+        )
+        self.pipe = self.pipe.to("cuda")
+
+    def generate(self, prompt: str, img_size: int = 512):
+        assert len(prompt), "prompt parameter cannot be empty"
+
+        with torch.autocast("cuda"):
+            image = self.pipe(prompt, height=img_size, width=img_size).images[0]
+            return image
+
+
+entrypoint = APIIngress.bind(StableDiffusionXL.bind())
+
+# __example_code_end__
+
+
+if __name__ == "__main__":
+    import ray
+    import os
+    import requests
+
+    ray.init(
+        runtime_env={
+            "pip": [
+                "diffusers==0.33.1",
+                "transformers==4.51.3",
+            ]
+        }
+    )
+
+    handle = serve.run(entrypoint)
+    handle.generate.remote("hi").result()
+
+    prompt = "a cute cat is dancing on the grass."
+    prompt_query = "%20".join(prompt.split(" "))
+    resp = requests.get(f"http://127.0.0.1:8000/imagine?prompt={prompt_query}")
+
+    with open("output.png", "wb") as f:
+        f.write(resp.content)
+
+    assert os.path.exists("output.png")
+    os.remove("output.png")