Analyze Image with Imagga API on New Contact from Twilio SendGrid API

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New Contact from the Twilio SendGrid API

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Analyze Image with the Imagga API

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Getting Started#

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

Select this integration
Configure the New Contact trigger
1. Connect your Twilio SendGrid account
2. Configure timer
Configure the Analyze Image action
1. Connect your Imagga account
2. Optional- Configure Image URL
3. Optional- Configure Image File
4. Select a Image Process Type
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 Contact on Twilio SendGrid

Description:Emit new event when a new contact is created

Version:0.0.7

Key:sendgrid-new-contact

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 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: "0.0.7",
  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.

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.
	`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#

Analyze Image on Imagga

Description:Assign a category to a single image based on its visual content. [See the documentation](https://docs.imagga.com/?shell#categories-categorizer_id)

Version:0.0.1

Key:imagga-analyze-image

View on GitHub

Imagga Overview#

The Imagga API is a powerful image recognition tool that enables you to automate the process of analyzing and tagging images. With its AI-driven capabilities, you can extract a wealth of information from visual content. It offers features such as categorization, color extraction, and auto-tagging, making it incredibly useful for building workflows that require image analysis.

Action Code#

import { prepareAdditionalProps } from "../../common/constants.mjs";
import { prepareFile } from "../../common/utils.mjs";
import imagga from "../../imagga.app.mjs";

export default {
  key: "imagga-analyze-image",
  name: "Analyze Image",
  description: "Assign a category to a single image based on its visual content. [See the documentation](https://docs.imagga.com/?shell#categories-categorizer_id)",
  version: "0.0.1",
  type: "action",
  props: {
    imagga,
    imageUrl: {
      propDefinition: [
        imagga,
        "imageUrl",
      ],
      optional: true,
    },
    imageFile: {
      propDefinition: [
        imagga,
        "imageFile",
      ],
      optional: true,
    },
    imageProcessType: {
      propDefinition: [
        imagga,
        "imageProcessType",
      ],
      reloadProps: true,
    },
  },
  async additionalProps() {
    return prepareAdditionalProps({
      props: imagga.propDefinitions,
      type: this.imageProcessType,
    });
  },
  async run({ $ }) {
    const {
      imagga,
      imageUrl,
      imageFile,
      language = [],
      saveIndex,
      saveId,
      extractOverallColors,
      extractObjectColors,
      deterministic,
      verbose,
      threshold,
      decreaseParents,
      categorizerId,
      overallCount,
      separatedCount,
      imageProcessType,
      taggerId,
      ...params
    } = this;

    const file = await prepareFile({
      imageUrl,
      imageFile,
      imagga,
    });

    if (typeof extractOverallColors === "boolean") params.extract_overall_colors = +extractOverallColors;
    if (typeof extractObjectColors === "boolean") params.extract_object_colors = +extractObjectColors;
    if (typeof deterministic === "boolean") params.deterministic = +deterministic;
    if (typeof verbose === "boolean") params.verbose = +verbose;
    if (typeof decreaseParents === "boolean") params["decrease_parents"] = +decreaseParents;
    if (threshold) params.threshold = parseFloat(threshold);

    const response = await imagga.analyzeImage({
      $,
      taggerId,
      imageProcessType,
      categorizerId,
      params: {
        ...params,
        ...file,
        overall_count: overallCount,
        separated_count: separatedCount,
        language: language.toString(),
        save_index: saveIndex,
        save_id: saveId,
      },
    });

    $.export("$summary", "Image successfully assigned!");
    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
Imagga	`imagga`	`app`	This component uses the Imagga app.
Image URL	`imageUrl`	`string`	The URL of the image to analyze.
Image File	`imageFile`	`string`	The file path from `/tmp` dir of the image to analyze.
Image Process Type	`imageProcessType`	`string`	Select a value from the drop down menu:`{ "label": "Tags", "value": "tags" }{ "label": "Categories", "value": "categories" }{ "label": "Colors", "value": "colors" }`