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# Cron Jobs
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# Use cron jobs
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Sometimes you don't want to run your graph based on user interaction, but rather you would like to schedule your graph to run on a schedule - for example if you wish for your graph to compose and send out a weekly email of to-dos for your team. LangGraph Platform allows you to do this without having to write your own script by using the `Crons` client. To schedule a graph job, you need to pass a [cron expression](https://crontab.cronhub.io/) to inform the client when you want to run the graph. `Cron` jobs are run in the background and do not interfere with normal invocations of the graph.
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# Using Webhooks
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# Use webhooks
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When working with LangGraph Platform, you may want to use webhooks to receive updates after an API call completes. Webhooks are useful for triggering actions in your service once a run has finished processing. To implement this, you need to expose an endpoint that can accept `POST` requests and pass this endpoint as a `webhook` parameter in your API request.
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Currently, the SDK does not provide built-in support for defining webhook endpoints, but you can specify them manually using API requests.
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## Supported Endpoints
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## Supported endpoints
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The following API endpoints accept a `webhook` parameter:
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In this guide, we’ll show how to trigger a webhook after streaming a run.
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## Setting Up Your Assistant and Thread
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## Set up your assistant and thread
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Before making API calls, set up your assistant and thread.
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--data '{}'
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```
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### Example Response
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Example response:
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```json
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{
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"thread_id": "9dde5490-2b67-47c8-aa14-4bfec88af217",
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}
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```
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## Using a Webhook with a Graph Run
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## Use a webhook with a graph run
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To use a webhook, specify the `webhook` parameter in your API request. When the run completes, LangGraph Platform sends a `POST` request to the specified webhook URL.
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}'
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```
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## Webhook Payload
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## Webhook payload
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LangGraph Platform sends webhook notifications in the format of a [Run](../../cloud/concepts/runs.md). See the [API Reference](https://langchain-ai.github.io/langgraph/cloud/reference/api/api_ref.html#model/run) for details. The request payload includes run input, configuration, and other metadata in the `kwargs` field.
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## Securing Webhooks
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## Secure webhooks
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To ensure only authorized requests hit your webhook endpoint, consider adding a security token as a query parameter:
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Your server should extract and validate this token before processing requests.
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## Testing Webhooks
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## Test webhooks
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You can test your webhook using online services like:
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- **[Webhook.site](https://webhook.site/)** – View, debug, and log incoming webhook requests in real time.
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These tools help you verify that LangGraph Platform is correctly triggering and sending webhooks to your service.
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---
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By following these steps, you can integrate webhooks into your LangGraph Platform workflow, automating actions based on completed runs.
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