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doc/source/templates/03_serving_stable_diffusion/README.md

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+# Serving a Stable Diffusion Model with Ray Serve
+
+| Template Specification | Description |
+| ---------------------- | ----------- |
+| Summary | This app provides users a one click production option for serving a pre-trained Stable Diffusion model from Hugging Face.  It leverages [Ray Serve](https://docs.ray.io/en/latest/serve/index.html) to deploy locally and the built-in IDE integration on an Anyscale Workspace so you can iterate and add additional logic to the app. You can then use a simple CLI to deploy to production with [Anyscale Services](https://docs.anyscale.com/productionize/services/get-started?utm_source=ray_docs&utm_medium=docs&utm_campaign=stable_diffusion). |
+| Time to Run | Around 2 minutes to setup the models and generate your first image(s). Less than 10 seconds for every subsequent round of image generation (depending on the image size). |
+| Minimum Compute Requirements | At least 1 GPU node with 1 NVIDIA A10 GPU. |
+| Cluster Environment | This template uses a docker image built on top of the latest Anyscale-provided Ray 2.9 image using Python 3.9: [`anyscale/ray:latest-py39-cu118`](https://docs.anyscale.com/reference/base-images/overview?utm_source=ray_docs&utm_medium=docs&utm_campaign=stable_diffusion). See the appendix below for more details. |
+
+## Get Started
+
+**When the workspace is up and running, start coding by clicking on the Jupyter or VS Code icon above. Open the `start.ipynb` file and follow the instructions there.**
+
+By the end, we'll have an application that generates images using stable diffusion for a given prompt!
+
+The application will look something like this:
+
+```text
+Enter a prompt (or 'q' to quit):   twin peaks sf in basquiat painting style
+
+Generating image(s)...
+
+Generated 4 image(s) in 8.75 seconds to the directory: 58b298d9
+```
+
+![Example output](https://github-production-user-asset-6210df.s3.amazonaws.com/3887863/239090189-dc1f1b7b-2fa0-4886-ae12-ca5d35b8ebc9.png)
+
+## Deploying on Anyscale Service
+
+This template also includes an example for deploying stable diffusion in production with a FastAPI server. In order to run it locally on your workspace run:
+
+```bash
+serve run app:entrypoint
+```
+
+Query the serve application:
+
+```bash
+python query.py
+```
+
+To deploy to a production endpoint on Anyscale run:
+
+```bash
+anyscale service rollout -f service.yaml --name {ENTER_NAME_FOR_SERVICE}
+```
+
+You can find the link to the service in the logs of the `anyscale service rollout` command. Something like:
+
+```
+(anyscale +2.9s) View the service in the UI at https://console.anyscale.com/services/service_gxr3cfmqn2gethuuiusv2zif.
+```
+
+You can call the service programmatically (see the instruction from top right corner's Query button) or using the web interface.
+
+![api-doc-image](https://user-images.githubusercontent.com/21118851/204909023-9e3fac37-40c0-44e3-bfe0-4db502e30c2e.png)
+
+1. Wait for the service to be in a "Running" state.
+2. In the "Deployments" section, find the "APIIngress" row, click the "View" under "API Docs".
+3. You should now see a OpenAPI rendered documentation page.
+4. Click the `/imagine` endpoint, then "Try it out" to enable calling it via the interactive API browser.
+5. Fill in your prompt and click execute.
+
+## Appendix
+
+### Advanced: Build off of this template's cluster environment
+
+#### Option 1: Build a new cluster environment on Anyscale
+
+Find a `cluster_env.yaml` file in the working directory of the template. Feel free to modify this YAML to include more requirements, then follow [this guide](https://docs.anyscale.com/configure/dependency-management/cluster-environments#creating-a-cluster-environment?utm_source=ray_docs&utm_medium=docs&utm_campaign=stable_diffusion) to create a new cluster environment with the `anyscale` CLI .
+
+Finally, update your workspace's cluster environment to this new one after it's done building.
+
+#### Option 2: Build a new docker image with your own infrastructure
+
+Use the following `docker pull` command if you want to manually build a new Docker image based off of this one.
+
+```bash
+docker pull us-docker.pkg.dev/anyscale-workspace-templates/workspace-templates/serve-stable-diffusion-model-ray-serve:latest
+```