Create Social Media Post with TextCortex 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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Create Social Media Post with the TextCortex API

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Getting Started#

This integration creates a workflow with a Twilio SendGrid trigger and TextCortex 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 Create Social Media Post action
1. Connect your TextCortex account
2. Configure Context
3. Optional- Configure Keywords
4. Optional- Configure Max Tokens
5. Select a Mode
6. Optional- Select a Model
7. Optional- Configure N
8. Optional- Select a Source Language
9. Optional- Select a Target Language
10. Optional- Configure Temperature
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:0.0.6

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: "0.0.6",
  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#

Create Social Media Post on TextCortex

Description:Create a social media post. [See the documentation](https://docs.textcortex.com/api/paths/texts-social-media-posts/post)

Version:0.0.1

Key:textcortex-create-social-media-post

View on GitHub

TextCortex Overview#

The TextCortex API enables automated creation of human-like text, making it a powerful tool for a variety of text generation tasks like drafting emails, creating content, or generating product descriptions. With Pipedream, you can integrate TextCortex into serverless workflows to harness AI writing assistance, trigger content creation based on events, or enhance data with generated text. The API's capability enhances automation and can be combined with other apps for more complex tasks.

Action Code#

import app from "../../textcortex.app.mjs";
import constants from "../../common/constants.mjs";

export default {
  key: "textcortex-create-social-media-post",
  name: "Create Social Media Post",
  description: "Create a social media post. [See the documentation](https://docs.textcortex.com/api/paths/texts-social-media-posts/post)",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    context: {
      type: "string",
      label: "Context",
      description: "The context of the social media post.",
    },
    keywords: {
      type: "string[]",
      label: "Keywords",
      description: "Keywords to be included in the post.",
      optional: true,
    },
    maxTokens: {
      propDefinition: [
        app,
        "maxTokens",
      ],
    },
    mode: {
      type: "string",
      label: "Mode",
      description: "The platform, e.g. `twitter` to generate a Tweet. Allowed values: `twitter`, `linkedin`",
      options: Object.values(constants.SOCIAL_MEDIA_MODE),
    },
    model: {
      propDefinition: [
        app,
        "model",
      ],
    },
    n: {
      propDefinition: [
        app,
        "n",
      ],
    },
    sourceLang: {
      propDefinition: [
        app,
        "sourceLang",
      ],
    },
    targetLang: {
      propDefinition: [
        app,
        "targetLang",
      ],
    },
    temperature: {
      propDefinition: [
        app,
        "temperature",
      ],
    },
  },
  methods: {
    createSocialMediaPost(args = {}) {
      return this.app.post({
        path: "/texts/social-media-posts",
        ...args,
      });
    },
  },
  async run({ $: step }) {
    const {
      createSocialMediaPost,
      context,
      keywords,
      maxTokens,
      mode,
      model,
      n,
      sourceLang,
      targetLang,
      temperature,
    } = this;

    const response = await createSocialMediaPost({
      step,
      data: {
        context,
        keywords,
        max_tokens: maxTokens,
        mode,
        model,
        n,
        source_lang: sourceLang,
        target_lang: targetLang,
        temperature,
      },
    });

    step.export("$summary", `Successfully created social media post with status \`${response.status}\``);

    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
TextCortex	`app`	`app`	This component uses the TextCortex app.
Context	`context`	`string`	The context of the social media post.
Keywords	`keywords`	`string[]`	Keywords to be included in the post.
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens to generate.
Mode	`mode`	`string`	Select a value from the drop down menu:`twitterlinkedin`
Model	`model`	`string`	Select a value from the drop down menu:`velox-1aecus-1alta-1sophos-1chat-sophos-1`
N	`n`	`integer`	The number of outputs to generate.
Source Language	`sourceLang`	`string`	Select a value from the drop down menu:`{ "label": "English (Default)", "value": "en" }{ "label": "The API will attempt to detect the language of the text and translate it.", "value": "auto" }{ "label": "Bulgarian", "value": "bg" }{ "label": "Czech", "value": "cs" }{ "label": "Danish", "value": "da" }{ "label": "German", "value": "de" }{ "label": "Greek", "value": "el" }{ "label": "Spanish", "value": "es" }{ "label": "Estonian", "value": "et" }{ "label": "Finnish", "value": "fi" }{ "label": "French", "value": "fr" }{ "label": "Hungarian", "value": "hu" }{ "label": "Indonesian", "value": "id" }{ "label": "Italian", "value": "it" }{ "label": "Japanese", "value": "ja" }{ "label": "Korean", "value": "ko" }{ "label": "Lithuanian", "value": "lt" }{ "label": "Latvian", "value": "lv" }{ "label": "Norwegian", "value": "nb" }{ "label": "Dutch", "value": "nl" }{ "label": "Polish", "value": "pl" }{ "label": "Portuguese (all Portuguese varieties mixed)", "value": "pt" }{ "label": "Romanian", "value": "ro" }{ "label": "Russian", "value": "ru" }{ "label": "Slovak", "value": "sk" }{ "label": "Slovenian", "value": "sl" }{ "label": "Swedish", "value": "sv" }{ "label": "Turkish", "value": "tr" }{ "label": "Ukrainian", "value": "uk" }{ "label": "Chinese", "value": "zh" }`
Target Language	`targetLang`	`string`	Select a value from the drop down menu:`{ "label": "English (Default)", "value": "en" }{ "label": "The API will attempt to detect the language of the text and translate it.", "value": "auto" }{ "label": "Bulgarian", "value": "bg" }{ "label": "Czech", "value": "cs" }{ "label": "Danish", "value": "da" }{ "label": "German", "value": "de" }{ "label": "Greek", "value": "el" }{ "label": "Spanish", "value": "es" }{ "label": "Estonian", "value": "et" }{ "label": "Finnish", "value": "fi" }{ "label": "French", "value": "fr" }{ "label": "Hungarian", "value": "hu" }{ "label": "Indonesian", "value": "id" }{ "label": "Italian", "value": "it" }{ "label": "Japanese", "value": "ja" }{ "label": "Korean", "value": "ko" }{ "label": "Lithuanian", "value": "lt" }{ "label": "Latvian", "value": "lv" }{ "label": "Norwegian", "value": "nb" }{ "label": "Dutch", "value": "nl" }{ "label": "Polish", "value": "pl" }{ "label": "Portuguese (all Portuguese varieties mixed)", "value": "pt" }{ "label": "Romanian", "value": "ro" }{ "label": "Russian", "value": "ru" }{ "label": "Slovak", "value": "sk" }{ "label": "Slovenian", "value": "sl" }{ "label": "Swedish", "value": "sv" }{ "label": "Turkish", "value": "tr" }{ "label": "Ukrainian", "value": "uk" }{ "label": "Chinese", "value": "zh" }`
Temperature	`temperature`	`string`	The sampling temperature to be used in text generation. The higher the temperature, the higher the risk of the output to sound "made up".