Various enhancements to the Gradio Ray Serve tutorial #50276
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* adds missing pip requirements * improves the overall narrative flow of the tutorial * clarifies that there are 2 separate examples within the same page * clarifies the difference between the two methods Signed-off-by: Ricardo Decal <rdecal@anyscale.com>
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jcotant1
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angelinalg
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Feb 18, 2025
| ## Quickstart: Deploy your Gradio app with Ray Serve | ||
| ## Example 1: Scaling up your Gradio app with `GradioServer` | ||
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| The first example summarizes text using the [T5 Small](https://huggingface.co/t5-small) model and uses [Hugging Face's Pipelines](https://huggingface.co/docs/transformers/main_classes/pipelines) to access that model. It demonstrates one easy way to deploy Gradio apps onto Ray Serve: using the simple `GradioServer` wrapper. Later, in example 2, we will show how to use `GradioIngress` for more customized use-cases. |
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Suggested change
| The first example summarizes text using the [T5 Small](https://huggingface.co/t5-small) model and uses [Hugging Face's Pipelines](https://huggingface.co/docs/transformers/main_classes/pipelines) to access that model. It demonstrates one easy way to deploy Gradio apps onto Ray Serve: using the simple `GradioServer` wrapper. Later, in example 2, we will show how to use `GradioIngress` for more customized use-cases. | |
| The first example summarizes text using the [T5 Small](https://huggingface.co/t5-small) model and uses [Hugging Face's Pipelines](https://huggingface.co/docs/transformers/main_classes/pipelines) to access that model. It demonstrates one easy way to deploy Gradio apps onto Ray Serve: using the simple `GradioServer` wrapper. Example 2 shows how to use `GradioIngress` for more customized use-cases. |
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Avoid first person and future tense when possible.
| ```{literalinclude} ../doc_code/gradio-integration.py | ||
| :start-after: __doc_gradio_app_begin__ | ||
| :end-before: __doc_gradio_app_end__ | ||
| ``` | ||
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| ### Deploying Gradio Server | ||
| In order to deploy your Gradio app onto Ray Serve, you need to wrap your Gradio app in a Serve [deployment](serve-key-concepts-deployment). `GradioServer` acts as that wrapper. It serves your Gradio app remotely on Ray Serve so that it can process and respond to HTTP requests. | ||
| In order to deploy your Gradio app onto Ray Serve, you need to wrap your Gradio app in a Serve [deployment](serve-key-concepts-deployment). `GradioServer` acts as that wrapper. It serves your Gradio app remotely on Ray Serve so that it can process and respond to HTTP requests. |
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| In order to deploy your Gradio app onto Ray Serve, you need to wrap your Gradio app in a Serve [deployment](serve-key-concepts-deployment). `GradioServer` acts as that wrapper. It serves your Gradio app remotely on Ray Serve so that it can process and respond to HTTP requests. | |
| To deploy your Gradio app onto Ray Serve, you need to wrap the Gradio app in a Serve [deployment](serve-key-concepts-deployment). `GradioServer` acts as that wrapper. It serves your Gradio app remotely on Ray Serve so that it can process and respond to HTTP requests. |
| @@ -59,7 +63,7 @@ Using either the Gradio app `io`, which the builder function constructed, or you | |||
| :end-before: __doc_app_end__ | |||
| ``` | |||
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| Finally, deploy your Gradio Server. Run the following in your terminal: | |||
| Finally, deploy your Gradio Server. Run the following in your terminal (assuming that you saved the file as `demo.py`): | |||
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Suggested change
| Finally, deploy your Gradio Server. Run the following in your terminal (assuming that you saved the file as `demo.py`): | |
| Finally, deploy your Gradio Server. Run the following in your terminal, assuming that you saved the file as `demo.py`: |
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Avoid excessive use of parentheses.
| Suppose you want to run the following program. | ||
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| 1. Take two text generation models, [`gpt2`](https://huggingface.co/gpt2) and [`distilgpt2`](https://huggingface.co/distilgpt2). | ||
| 2. Run the two models on the same input text, so that the generated text has a minimum length of 20 and maximum length of 100. | ||
| 3. Display the outputs of both models using Gradio. | ||
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| Let's compare an unparallelized approach using vanilla Gradio to a parallelized approach using Ray Serve. |
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| Let's compare an unparallelized approach using vanilla Gradio to a parallelized approach using Ray Serve. | |
| The following is a comparison of an unparallelized approach using vanilla Gradio to a parallelized approach using Ray Serve. |
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Why are these changes needed?
Related issue number
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Checks
git commit -s) in this PR.scripts/format.shto lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.