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d de e de fddZ de fddZ de e ddfddZ de de de fddZ!de de de fd d Z"dS ) zSContains `WebhooksServer` and `webhook_endpoint` to create a webhook server easily. N)wraps)
TYPE_CHECKINGAnyCallableDictOptional ) experimentalis_fastapi_availableis_gradio_available)Request)FastAPIr ) JSONResponseWebhooksServer _global_appSPACE_IDc s e Zd ZdZd fdd Z dded dee ddfd d
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The [`WebhooksServer`] class lets you create an instance of a Gradio app that can receive Huggingface webhooks.
These webhooks can be registered using the [`~WebhooksServer.add_webhook`] decorator. Webhook endpoints are added to
the app as a POST endpoint to the FastAPI router. Once all the webhooks are registered, the `launch` method has to be
called to start the app.
It is recommended to accept [`WebhookPayload`] as the first argument of the webhook function. It is a Pydantic
model that contains all the information about the webhook event. The data will be parsed automatically for you.
Check out the [webhooks guide](../guides/webhooks_server) for a step-by-step tutorial on how to setup your
WebhooksServer and deploy it on a Space.
`WebhooksServer` is experimental. Its API is subject to change in the future.
You must have `gradio` installed to use `WebhooksServer` (`pip install --upgrade gradio`).
Args:
ui (`gradio.Blocks`, optional):
A Gradio UI instance to be used as the Space landing page. If `None`, a UI displaying instructions
about the configured webhooks is created.
webhook_secret (`str`, optional):
A secret key to verify incoming webhook requests. You can set this value to any secret you want as long as
you also configure it in your [webhooks settings panel](https://huggingface.co/settings/webhooks). You
can also set this value as the `WEBHOOK_SECRET` environment variable. If no secret is provided, the
webhook endpoints are opened without any security.
Example:
```python
import gradio as gr
from huggingface_hub import WebhooksServer, WebhookPayload
with gr.Blocks() as ui:
...
app = WebhooksServer(ui=ui, webhook_secret="my_secret_key")
@app.add_webhook("/say_hello")
async def hello(payload: WebhookPayload):
return {"message": "hello"}
app.launch()
```
returnc s( t stdt stdt | S )NzjYou must have `gradio` installed to use `WebhooksServer`. Please run `pip install --upgrade gradio` first.zlYou must have `fastapi` installed to use `WebhooksServer`. Please run `pip install --upgrade fastapi` first.)r ImportErrorr
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S ttj fdd}|S )ax
Decorator to add a webhook to the [`WebhooksServer`] server.
Args:
path (`str`, optional):
The URL path to register the webhook function. If not provided, the function name will be used as the
path. In any case, all webhooks are registered under `/webhooks`.
Raises:
ValueError: If the provided path is already registered as a webhook.
Example:
```python
from huggingface_hub import WebhooksServer, WebhookPayload
app = WebhooksServer()
@app.add_webhook
async def trigger_training(payload: WebhookPayload):
if payload.repo.type == "dataset" and payload.event.action == "update":
# Trigger a training job if a dataset is updated
...
app.launch()
```
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Go to https://huggingface.co/settings/webhooks to setup your webhooks.r )r! _get_default_ui
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nd W d |S 1 sAw Y |S ) zLDefault UI if not provided (lists webhooks and provides basic instructions).r Nu) # This is an app to process 🤗 WebhooksaT Webhooks are a foundation for MLOps-related features. They allow you to listen for new changes on specific repos or to all repos belonging to particular set of users/organizations (not just your repos, but any repo). Check out this [guide](https://huggingface.co/docs/hub/webhooks) to get to know more about webhooks on the Huggingface Hub.z webhook(s) are registered:z
z
c s s. | ]\}}d | dt |j| dV qdS )z- [z]()N)_get_webhook_doc_urlr* )r: webhook_pathr; r r r r> s
z1WebhooksServer._get_default_ui..zGo to https://huggingface.co/settings/webhooks to setup your webhooks.
You app is running locally. Please look at the logs to check the full URL you need to set.z
This app is running on a Space. You can find the corresponding URL in the options menu (top-right) > 'Embed the Space'. The URL looks like 'https://{username}-{repo_name}.hf.space'.)gradioBlocksMarkdownlenr$ rJ rD rA )r& grr r r r r? s0
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+$r( r c s6 t r t S ttjdtdtf fdd }|S )a Decorator to start a [`WebhooksServer`] and register the decorated function as a webhook endpoint.
This is a helper to get started quickly. If you need more flexibility (custom landing page or webhook secret),
you can use [`WebhooksServer`] directly. You can register multiple webhook endpoints (to the same server) by using
this decorator multiple times.
Check out the [webhooks guide](../guides/webhooks_server) for a step-by-step tutorial on how to setup your
server and deploy it on a Space.
`webhook_endpoint` is experimental. Its API is subject to change in the future.
You must have `gradio` installed to use `webhook_endpoint` (`pip install --upgrade gradio`).
Args:
path (`str`, optional):
The URL path to register the webhook function. If not provided, the function name will be used as the path.
In any case, all webhooks are registered under `/webhooks`.
Examples:
The default usage is to register a function as a webhook endpoint. The function name will be used as the path.
The server will be started automatically at exit (i.e. at the end of the script).
```python
from huggingface_hub import webhook_endpoint, WebhookPayload
@webhook_endpoint
async def trigger_training(payload: WebhookPayload):
if payload.repo.type == "dataset" and payload.event.action == "update":
# Trigger a training job if a dataset is updated
...
# Server is automatically started at the end of the script.
```
Advanced usage: register a function as a webhook endpoint and start the server manually. This is useful if you
are running it in a notebook.
```python
from huggingface_hub import webhook_endpoint, WebhookPayload
@webhook_endpoint
async def trigger_training(payload: WebhookPayload):
if payload.repo.type == "dataset" and payload.event.action == "update":
# Trigger a training job if a dataset is updated
...
# Start the server manually
trigger_training.launch()
```
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`app = WebhooksServer(webhook_secret='my_secret', ...)`zpFor more details about webhook secrets, please refer to https://huggingface.co/docs/hub/webhooks#webhook-secret.z$Webhook secret is correctly defined.)rK r7 r r r r% C s r% webhook_namerR c C s d| | dd d S )z@Returns the anchor to a given webhook in the docs (experimental)z/docs#/default/r) rM _post)replace)ri rR r r r rQ R s rQ r- c sd t t dtf fdd }djvr0jt jdt jjtdftj d|_
|S )a Wraps a webhook function to check the webhook secret before calling the function.
This is a hacky way to add the `request` parameter to the function signature. Since FastAPI based itself on route
parameters to inject the values to the function, we need to hack the function signature to retrieve the `Request`
object (and hence the headers). A far cleaner solution would be to use a middleware. However, since
`fastapi==0.90.1`, a middleware cannot be added once the app has started. And since the FastAPI app is started by
Gradio internals (and not by us), we cannot add a middleware.
This method is called only when a secret has been defined by the user. If a request is sent without the
"x-webhook-secret", the function will return a 401 error (unauthorized). If the header is sent but is incorrect,
the function will return a 403 error (forbidden).
Inspired by https://stackoverflow.com/a/33112180.
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