Add Request to Queue with fal.ai API on New Events (Instant) from Twilio SendGrid API

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New Events (Instant) from the Twilio SendGrid API

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Add Request to Queue with the fal.ai API

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Getting Started#

This integration creates a workflow with a Twilio SendGrid trigger and fal.ai action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Events (Instant) trigger
1. Connect your Twilio SendGrid account
2. Select one or more Event Types
Configure the Add Request to Queue action
1. Connect your fal.ai account
2. Configure App ID
3. Configure Data
4. Optional- Configure Rerun Enabled
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

New Events (Instant) on Twilio SendGrid

Description:Emit new event when any of the specified SendGrid events is received

Version:0.0.5

Key:sendgrid-events

View on GitHub

Twilio SendGrid Overview#

The Twilio SendGrid API opens up a world of possibilities for email automation, enabling you to send emails efficiently and track their performance. With this API, you can programmatically create and send personalized email campaigns, manage contacts, and parse inbound emails for data extraction. When you harness the power of Pipedream, you can connect SendGrid to hundreds of other apps to automate workflows, such as triggering email notifications based on specific actions, syncing email stats with your analytics, or handling incoming emails to create tasks or tickets.

Trigger Code#

import common from "../common/http-based.mjs";
import deliveryEventTypes from "./delivery-event-types.mjs";
import engagementEventTypes from "./engagement-event-types.mjs";

export default {
  ...common,
  key: "sendgrid-events",
  name: "New Events (Instant)",
  description: "Emit new event when any of the specified SendGrid events is received",
  version: "0.0.5",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    eventTypes: {
      type: "string[]",
      label: "Event Types",
      description: "The type of events to listen to",
      options(context) {
        const { page } = context;
        if (page !== 0) {
          return {
            options: [],
          };
        }

        const options = [
          ...deliveryEventTypes,
          ...engagementEventTypes,
        ];
        return {
          options,
        };
      },
    },
  },
  methods: {
    ...common.methods,
    baseWebhookSettings() {
      // The list of events that a webhook can listen to. This method returns an
      // exhaustive list of all such flags disabled, and each event source can
      // then override the flags that are relevant to the event they handle.
      //
      // See the docs for more information:
      // https://sendgrid.com/docs/api-reference/
      const eventTypesData = [
        ...deliveryEventTypes,
        ...engagementEventTypes,
      ];
      return eventTypesData.reduce((accum, eventTypeData) => ({
        ...accum,
        [eventTypeData.value]: false,
      }), {});
    },
    webhookEventFlags() {
      return this.eventTypes.reduce((accum, eventType) => ({
        ...accum,
        [eventType]: true,
      }), {});
    },
    generateMeta(data) {
      const {
        event: eventType,
        sg_event_id: id,
        timestamp: ts,
      } = data;
      const summary = `New event: ${eventType}`;
      return {
        id,
        summary,
        ts,
      };
    },
  },
};

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Twilio SendGrid	`sendgrid`	`app`	This component uses the Twilio SendGrid app.
N/A	`http`	`$.interface.http`	This component uses `$.interface.http` to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the `run()` method of the component.
Event Types	`eventTypes`	`string[]`	Select a value from the drop down menu.

Trigger Authentication#

Twilio SendGrid uses API keys for authentication. When you connect your Twilio SendGrid account, Pipedream securely stores the keys so you can easily authenticate to Twilio SendGrid APIs in both code and no-code steps.

About Twilio SendGrid#

Send marketing and transactional email through the Twilio SendGrid platform with the Email API, proprietary mail transfer agent, and infrastructure for scalable delivery.

Action#

Add Request to Queue on fal.ai

Description:Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates. [See the documentation](https://fal.ai/docs/model-endpoints/queue#queue-endpoints).

Version:0.0.1

Key:fal_ai-add-request-to-queue

View on GitHub

Action Code#

import app from "../../fal_ai.app.mjs";

export default {
  key: "fal_ai-add-request-to-queue",
  name: "Add Request to Queue",
  description: "Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates. [See the documentation](https://fal.ai/docs/model-endpoints/queue#queue-endpoints).",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    appId: {
      propDefinition: [
        app,
        "appId",
      ],
    },
    data: {
      type: "object",
      label: "Data",
      description: "Additional data to include with the request. [See the documentation](https://fal.ai/models/fal-ai/lora/api#schema-input) for more input fields.",
      default: {
        model_name: "stabilityai/stable-diffusion-xl-base-1.0",
        prompt: "Photo of a european medieval 40 year old queen, silver hair, highly detailed face, detailed eyes, head shot, intricate crown, age spots, wrinkles",
      },
    },
    reRunEnabled: {
      type: "boolean",
      label: "Rerun Enabled",
      description: "Enable the step to rerun to retrieve the request response. [See the documentation](https://pipedream.com/docs/code/nodejs/rerun/#flowrerun).",
      optional: true,
      reloadProps: true,
      default: false,
    },
  },
  additionalProps() {
    if (this.reRunEnabled) {
      return {
        reRunTimeoutInSecs: {
          type: "integer",
          label: "Rerun Timeout",
          description: "The time in seconds to wait before rerunning the step to retrieve the request response. Eg. `30`. [See the documentation](https://pipedream.com/docs/code/nodejs/rerun/#flowrerun).",
          optional: true,
          min: 10,
        },
      };
    }

    return {
      falWebhook: {
        type: "string",
        label: "Webhook URL",
        description: "The URL to receive updates via webhook.",
        optional: true,
      },
    };
  },
  methods: {
    addToQueue({
      appId, ...args
    } = {}) {
      return this.app.post({
        path: `/${appId}`,
        ...args,
      });
    },
  },
  async run({ $ }) {
    const {
      context: {
        run: {
          runs,
          callback_request: callbackRequest,
        },
      },
    } = $;

    const {
      app,
      addToQueue,
      appId,
      data,
      falWebhook,
      reRunEnabled,
      reRunTimeoutInSecs,
    } = this;

    if (!reRunEnabled) {
      const response = await addToQueue({
        $,
        appId,
        params: {
          fal_webhook: falWebhook,
        },
        data,
      });

      $.export("$summary", `Successfully added the request to the queue with ID \`${response.request_id}\`.`);
      return response;
    }

    if (runs === 1) {
      const timeout = 1000 * (reRunTimeoutInSecs || 10);
      const { resume_url: resumeUrl } = $.flow.rerun(timeout, null, 1);

      return addToQueue({
        $,
        appId,
        params: {
          fal_webhook: resumeUrl,
        },
        data,
      });
    }

    const response = await app.getRequestResponse({
      $,
      appId,
      requestId: callbackRequest.body?.request_id,
    });

    $.export("$summary", "Successfully retrieved the request response.");
    return response;
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
fal.ai	`app`	`app`	This component uses the fal.ai app.
App ID	`appId`	`string`	The unique identifier for the app. Eg. `lora`.
Data	`data`	`object`	Additional data to include with the request. See the documentation for more input fields.
Rerun Enabled	`reRunEnabled`	`boolean`	Enable the step to rerun to retrieve the request response. See the documentation.