DocsHow-to GuidesHow to Use the Slack Events API in Kestra

How to Use the Slack Events API in Kestra

Trigger Kestra flows based on Slack events.

The Slack Events API allows you to build apps that respond to events from Slack. For example, you can trigger a custom action anytime a user joins a channel or when someone reacts to a message with a specific emoji.

Create a Slack App

To use the Slack Events API, you'll need to create a Slack app. You can do this from the Slack API website.

First, click on the "Create New App" button:

Choose the option "From scratch":

Then, give your app a name and select the workspace where you want to install it:

Now, you need to enable the "Event Subscriptions" feature:

In the "Subscribe to bot events" section, you can add events you want to listen to.

For example, you can listen to the app_mentions and reaction_added events:

Create a flow with a Webhook trigger

You can now create a Kestra flow that will listen to the events you've subscribed to:

yaml

id: slack_events
namespace: prod

tasks:
  - id: process_slack_event
    type: io.kestra.core.tasks.log.Log
    message: "{{ trigger.body }}"

triggers:
  - id: slack_event
    type: io.kestra.core.models.triggers.types.Webhook
    key: superStrongSecretKey42

Note that the webhook key cannot contain any special characters — only letters and digits. Also, consider it as a secret that you should keep safe. You can use Kestra's Secrets to store it securely.

Now, the only part left is to create a simple app that will listen to Slack events and will forward them to your Kestra flow via the Webhook trigger.

We'll look at how to do this using Python and FastAPI. For deployments, we'll show two options:

Using Modal for easy deployment
Using ngrok to expose our local FastAPI server to the internet. You can replace ngrok for any other deployment method you prefer.

First, sign up for a free account on Modal. Then, go to your Settings:

And create a new API token:

You will see a similar command:

bash

modal token set --token-id ak-zzzzzzzzz --token-secret as-zzzzzzzzz

Now, create the following flow in Kestra and replace the token ID and token secret with the ones you got from Modal. You can use Kestra's Secrets to store those securely. Also, make sure to replace your_kestra_host with your Kestra host URL in the slack.py file.

yaml

id: slack_app
namespace: prod

tasks:
  - id: modal_slack_app
    type: io.kestra.plugin.modal.cli.ModalCLI
    commands:
      - modal deploy slack.py
    env:
      MODAL_TOKEN_ID: "{{ secret('MODAL_TOKEN_ID') }}"
      MODAL_TOKEN_SECRET: "{{ secret('MODAL_TOKEN_SECRET') }}"
    inputFiles:
      slack.py: |
        from fastapi import FastAPI, Request
        from fastapi.responses import JSONResponse
        from modal import Image, Stub, asgi_app

        web_app = FastAPI()
        stub = Stub("slack_app")

        image = Image.debian_slim().pip_install("requests")


        @web_app.post("/slack/events")
        async def slack_events(request: Request):
            import requests

            json_data = await request.json()

            # Slack URL Verification Challenge
            if "challenge" in json_data:
                return JSONResponse(content={"challenge": json_data["challenge"]})

            # TODO adjust the URL below to your Kestra Webhook URL
            url = "http://your_kestra_host:8080/api/v1/executions/webhook/prod/slack_events/superStrongSecretKey42"
            headers = {
                "Content-Type": "application/json",
            }

            response = requests.post(url, headers=headers, json=json_data)
            print(response.text)

            return JSONResponse(
                content={"status": response.status_code, "response": response.text}
            )


        @stub.function(image=image)
        @asgi_app()
        def fastapi_app():
            return web_app

If you don't like adding the Python script inline in the YAML file, you can enable namespaceFiles and add the Python code in the embedded VS Code Editor in a separate file e.g. called slack.py and reference it in the flow as shown below:

yaml

id: slack_app
namespace: prod

tasks:
  - id: modal_slack_app
    type: io.kestra.plugin.modal.cli.ModalCLI
    namespaceFiles:
      enabled: true
    commands:
      - modal deploy slack.py
    env:
      MODAL_TOKEN_ID: "{{ secret('MODAL_TOKEN_ID') }}"
      MODAL_TOKEN_SECRET: "{{ secret('MODAL_TOKEN_SECRET') }}"

Once you execute that flow, you will see the endpoint to your app in the logs:

Go back to Slack and add the URL to the "Request URL" field in the "Event Subscriptions" section. Make sure to add slack/events at the end of the URL, e.g.:

bash

https://anna-geller--slack-app-fastapi-app.modal.run/slack/events

You should see the Verified message. Hit Save Changes and you're all set!

Install the Slack app to a Workspace and test it

First, we need to install the app to the workspace. Go to "Install App" and click on "Install to Workspace":

Now you can test the integration by mentioning your app in a channel. For example, you can write a hello message hello @kestra:

Confirm to invite the app to the channel and congratulate yourself with the "Nicely done!" emoji 🙌:

You should see that both events (app mention and reaction added) have triggered an execution of your Kestra flow:

Now it's up to you to automate your daily operations with Slack and Kestra!

Example automation: AI Chatbot

You can extend the slack_events flow to automate your daily business operations.

To do something more useful than just logging the Slack event, you can create a flow that listens to the app_mention event and responds to that message with a GPT-4 chatbot. First, create an incoming webhook in your Slack app:

Copy the webhook URL:

...and paste it into the url field of the SlackIncomingWebhook task in the flow below:

yaml

id: slack_events
namespace: prod

tasks:
  - id: if_app_mention
    type: io.kestra.core.tasks.flows.If
    condition: "{{ trigger.body.event.type == 'app_mention' }}"
    then:
      - id: gpt
        type: io.kestra.plugin.openai.ChatCompletion
        apiKey: "{{ secret('OPENAI_API_KEY') }}"
        model: gpt-4-0125-preview
        messages:
          - role: system
            content: The user will refer to you as <@{{ trigger.body.authorizations[0].user_id }}>. You get a prompt from a user and provide a concise answer.
        prompt: "{{ trigger.body.event.text ?? null }}"

      - id: slack
        type: io.kestra.plugin.notifications.slack.SlackIncomingWebhook
        url: "{{ secret('SLACK_WEBHOOK_URL') }}"
        payload: |
          {"channel":"{{ trigger.body.event.channel }}","text":"{{ outputs.gpt.choices[0].message.content }}"}
    else:
      - id: other_events
        type: io.kestra.core.tasks.log.Log
        message: "{{ trigger.body }}"

triggers:
  - id: slack_event
    type: io.kestra.core.models.triggers.types.Webhook
    key: superStrongSecretKey42

And here is the result:

Local testing with ngrok

If you don't want to host your app on Modal, you can use ngrok to expose your local server to the internet.

First, install ngrok:

bash

brew install ngrok/ngrok/ngrok

Then, sign up for a free account and then authenticate your terminal, as explained in the Getting Started guide:

bash

ngrok config add-authtoken long_token_string

Create a FastAPI app in a file called main.py:

python

from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
import requests

app = FastAPI()


@app.post("/slack/events")
async def slack_events(request: Request):
    json_data = await request.json()

    # Slack URL Verification Challenge
    if "challenge" in json_data:
        return JSONResponse(content={"challenge": json_data["challenge"]})

    print("Received an event")
    print(json_data)

    # URL of your Kestra flow webhook
    url = "http://your_kestra_host:8080/api/v1/executions/webhook/prod/slack_events/superStrongSecretKey42"
    headers = {
        "Content-Type": "application/json",
    }

    response = requests.post(url, headers=headers, json=json_data)
    print(response.text)

    return JSONResponse(
        content={"status": response.status_code, "response": response.text}
    )

Then, set up your FastAPI server:

bash

pip install fastapi uvicorn requests
uvicorn main:app --reload --port 3000
ngrok http http://localhost:3000

This will expose your local server to the internet. You should see a similar URL:

bash

https://0913-31-18-152-123.ngrok-free.app

Go back to your Slack app and add the URL to the "Request URL" field in the "Event Subscriptions" section. Make sure to add slack/events at the end of the URL, e.g.:

bash

https://0913-31-18-152-123.ngrok-free.app/slack/events

The rest of the process is the same as with Modal. You can now adjust the flow slack_events referenced in the FastAPI code and start automationg various processes based on Slack events.

Other deployment options

You can deploy that Slack app in many other ways including:

an on-prem VM
a serverless approach with AWS Lambda, Google Cloud Functions, or Azure Functions
a containerized approach with AWS Fargate, Google Cloud Run, or Azure Container Instances
a Kubernetes deployment.

And of course, you can use any other programming language and framework to build your Slack app. The only requirement is to forward the Slack events to your Kestra flow via the Webhook trigger.

How To GuidesHow to Use Secrets in Kestra

How To GuidesHow to Use Webhooks in Kestra

​How to ​Use the ​Slack ​Events ​A​P​I in ​Kestra

Create a Slack App

Create a flow with a Webhook trigger

Deploy a Slack app with Modal

Install the Slack app to a Workspace and test it

Example automation: AI Chatbot

Local testing with ngrok

Other deployment options

How to Use the Slack Events API in Kestra