← Twilio SendGrid + TextCortex integrations

Create Social Media Post with TextCortex API on New Contact from Twilio SendGrid API

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New Contact 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.

  1. Select this integration
  2. Configure the New Contact trigger
    1. Connect your Twilio SendGrid account
    2. Configure timer
  3. 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
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. 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

Description:Emit new event when a new contact is created
Version:0.0.6
Key:sendgrid-new-contact

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 orderBy from "lodash/orderBy.js";
import common from "../common/timer-based.mjs";

export default {
  ...common,
  key: "sendgrid-new-contact",
  name: "New Contact",
  description: "Emit new event when a new contact is created",
  version: "0.0.6",
  type: "source",
  dedupe: "unique",
  hooks: {
    async activate() {
      const currentTimestamp = Date.now();
      const state = {
        processedItems: [],
        lowerTimestamp: currentTimestamp,
        upperTimestamp: currentTimestamp,
      };
      this.db.set("state", state);
    },
  },
  methods: {
    ...common.methods,
    _maxDelayTime() {
      // There is no report from SendGrid as to how much time it takes
      // for a contact to be created and appear in search results, so
      // we're using a rough estimate of 30 minutes here.
      return 30 * 60 * 1000;  // 30 minutes, in milliseconds
    },
    _addDelayOffset(timestamp) {
      return timestamp - this._maxDelayTime();
    },
    _cleanupOldProcessedItems(processedItems, currentTimestamp) {
      return processedItems
        .map((item) => ({
          // We just need to keep track of the record ID and
          // its creation date.
          id: item.id,
          created_at: item.created_at,
        }))
        .filter((item) => {
          const { created_at: createdAt } = item;
          const createdAtTimestamp = Date.parse(createdAt);
          const cutoffTimestamp = this._addDelayOffset(currentTimestamp);
          return createdAtTimestamp > cutoffTimestamp;
        });
    },
    _makeSearchQuery(processedItems, lowerTimestamp, upperTimestamp) {
      const idList = processedItems
        .map((item) => item.id)
        .map((id) => `'${id}'`)
        .join(", ")
      || "''";
      const startTimestamp = this._addDelayOffset(lowerTimestamp);
      const startDate = this.toISOString(startTimestamp);
      const endDate = this.toISOString(upperTimestamp);
      return `
        contact_id NOT IN (${idList}) AND
        created_at BETWEEN
          TIMESTAMP '${startDate}' AND
          TIMESTAMP '${endDate}'
      `;
    },
    generateMeta(data) {
      const {
        item,
        eventTimestamp: ts,
      } = data;
      const {
        id,
        email,
      } = item;
      const slugifiedEmail = this.slugifyEmail(email);
      const summary = `New contact: ${slugifiedEmail}`;
      return {
        id,
        summary,
        ts,
      };
    },
    async processEvent(event) {
      // Transform the timer timestamp to milliseconds
      // to be consistent with how Javascript handles timestamps.
      const eventTimestamp = event.timestamp * 1000;

      // Retrieve the current state of the component.
      const {
        processedItems,
        lowerTimestamp,
        upperTimestamp,
      } = this.db.get("state");

      // Search for contacts within a specific timeframe, excluding
      // items that have already been processed.
      const query = this._makeSearchQuery(processedItems, lowerTimestamp, upperTimestamp);
      const {
        result: items,
        contact_count: contactCount,
      } = await this.sendgrid.searchContacts(query);

      // If no contacts have been retrieved via the API,
      // move the time window forward to possibly capture newer contacts.
      if (contactCount === 0) {
        const newState = {
          processedItems: this._cleanupOldProcessedItems(processedItems, lowerTimestamp),
          lowerTimestamp: upperTimestamp,
          upperTimestamp: eventTimestamp,
        };
        this.db.set("state", newState);
        return;
      }

      // We process the searched records from oldest to newest.
      const itemsToProcess = orderBy(items, "created_at");
      itemsToProcess
        .forEach((item) => {
          const meta = this.generateMeta({
            item,
            eventTimestamp,
          });
          this.$emit(item, meta);
        });

      // Use the timestamp of the last processed record as a lower bound for
      // following searches. This bound will be subjected to an offset so in
      // case older records appear in future search results, but have not
      // appeared until now, can be processed. We only adjust it if it means
      // moving forward, not backwards. Otherwise, we might start retrieving
      // older and older records indefinitely (and we're all about *new*
      // records!)
      const newLowerTimestamp = Math.max(
        lowerTimestamp,
        Date.parse(itemsToProcess[0].created_at),
      );

      // If the total contact count is less than 100, it means that during the
      // next iteration the search results count will most likely be less than
      // 50. In that case, if we extend the upper bound of the search time range
      // we might be able to retrieve more records.
      const newUpperTimestamp = contactCount < 100
        ? eventTimestamp
        : upperTimestamp;

      // The list of processed items can grow indefinitely.
      // Since we don't want to keep track of every processed record
      // ever, we need to clean up this list, removing any records
      // that are no longer relevant.
      const newProcessedItems = this._cleanupOldProcessedItems(
        [
          ...processedItems,
          ...itemsToProcess,
        ],
        newLowerTimestamp,
      );

      // Update the state of the component to reflect the computations
      // made above.
      const newState = {
        processedItems: newProcessedItems,
        lowerTimestamp: newLowerTimestamp,
        upperTimestamp: newUpperTimestamp,
      };
      this.db.set("state", newState);
    },
  },
};

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.
LabelPropTypeDescription
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
Twilio SendGridsendgridappThis component uses the Twilio SendGrid app.
timer$.interface.timer

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

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

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.

LabelPropTypeDescription
TextCortexappappThis component uses the TextCortex app.
Contextcontextstring

The context of the social media post.

Keywordskeywordsstring[]

Keywords to be included in the post.

Max TokensmaxTokensinteger

The maximum number of tokens to generate.

ModemodestringSelect a value from the drop down menu:twitterlinkedin
ModelmodelstringSelect a value from the drop down menu:velox-1aecus-1alta-1sophos-1chat-sophos-1
Nninteger

The number of outputs to generate.

Source LanguagesourceLangstringSelect 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 LanguagetargetLangstringSelect 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" }
Temperaturetemperaturestring

The sampling temperature to be used in text generation. The higher the temperature, the higher the risk of the output to sound "made up".

Action Authentication

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

Sign in and copy your API key directly from your dashboard under Settings >> API Key.

About TextCortex

Powerful AI Assistant To 12x Your Productivity 🚀

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