chore: import upstream snapshot with attribution

2026-07-13 13:17:40 +08:00
commit f1825c8ceb
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+---
+orphan: true
+---
+
+(serve-stable-diffusion-tutorial)=
+
+# Serve a Stable Diffusion Model
+
+<a href="https://https://console.anyscale.com/register/ha?render_flow=ray&utm_source=ray_docs&utm_medium=docs&utm_campaign=ray-serve-stable-diffusion-quickstart&redirectTo=/v2/template-preview/serve-stable-diffusion-v2">
+    <img src="../../_static/img/run-on-anyscale.svg" alt="Run on Anyscale">
+</a>
+<br></br>
+This example runs a Stable Diffusion application with Ray Serve.
+
+To run this example, install the following:
+
+```bash
+pip install "ray[serve]" requests torch diffusers==0.35.2 transformers
+```
+
+This example uses the [stabilityai/stable-diffusion-xl-base-1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) model and [FastAPI](https://fastapi.tiangolo.com/) to build the example. Save the following code to a file named stable_diffusion.py. 
+
+The Serve code is as follows:
+```{literalinclude} ../doc_code/stable_diffusion.py
+:language: python
+:start-after: __example_code_start__
+:end-before: __example_code_end__
+```
+
+Use `serve run stable_diffusion:entrypoint` to start the Serve application.
+
+:::{note}
+The autoscaling config sets `min_replicas` to 0, which means the deployment starts with no `ObjectDetection` replicas. These replicas spawn only when a request arrives. When no requests arrive after a certain period of time, Serve downscales `ObjectDetection` back to 0 replica to save GPU resources.
+:::
+
+You should see these messages in the output:
+```text
+(ServeController pid=362, ip=10.0.44.233) INFO 2023-03-08 16:44:57,579 controller 362 http_state.py:129 - Starting HTTP proxy with name 'SERVE_CONTROLLER_ACTOR:SERVE_PROXY_ACTOR-7396d5a9efdb59ee01b7befba448433f6c6fc734cfa5421d415da1b3' on node '7396d5a9efdb59ee01b7befba448433f6c6fc734cfa5421d415da1b3' listening on '127.0.0.1:8000'
+(ServeController pid=362, ip=10.0.44.233) INFO 2023-03-08 16:44:57,588 controller 362 http_state.py:129 - Starting HTTP proxy with name 'SERVE_CONTROLLER_ACTOR:SERVE_PROXY_ACTOR-a30ea53938547e0bf88ce8672e578f0067be26a7e26d23465c46300b' on node 'a30ea53938547e0bf88ce8672e578f0067be26a7e26d23465c46300b' listening on '127.0.0.1:8000'
+(ProxyActor pid=439, ip=10.0.44.233) INFO:     Started server process [439]
+(ProxyActor pid=5779) INFO:     Started server process [5779]
+(ServeController pid=362, ip=10.0.44.233) INFO 2023-03-08 16:44:59,362 controller 362 deployment_state.py:1333 - Adding 1 replica to deployment 'APIIngress'.
+2023-03-08 16:45:01,316 SUCC <string>:93 -- Deployed Serve app successfully.
+```
+
+Use the following code to send requests:
+```python
+import requests
+
+prompt = "a cute cat is dancing on the grass."
+input = "%20".join(prompt.split(" "))
+resp = requests.get(f"http://127.0.0.1:8000/imagine?prompt={input}")
+with open("output.png", 'wb') as f:
+    f.write(resp.content)
+```
+The app saves the `output.png` file locally. The following is an example of an output image. ![image](https://raw.githubusercontent.com/ray-project/images/master/docs/serve/stable_diffusion_output.png)