← Twilio SendGrid + Pinecone integrations

Delete Vectors with Pinecone API on New Contact from Twilio SendGrid API

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Trigger workflow on
New Contact from the Twilio SendGrid API
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Delete Vectors with the Pinecone API
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Getting Started

This integration creates a workflow with a Twilio SendGrid trigger and Pinecone 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 Delete Vectors action
    1. Connect your Pinecone account
    2. Select a Index Name
    3. Optional- Configure Prefix
    4. Optional- Configure Namespace
    5. Configure Vector IDs
  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:Deletes one or more vectors by ID, from a single namespace. [See the documentation](https://docs.pinecone.io/reference/api/data-plane/delete).
Version:0.0.2
Key:pinecone-delete-vectors

Pinecone Overview

The Pinecone API enables you to work with vector databases, which are essential for building and scaling applications with AI features like recommendation systems, image recognition, and natural language processing. On Pipedream, you can create serverless workflows integrating Pinecone with other apps, automate data ingestion, query vector databases in response to events, and orchestrate complex data processing pipelines that leverage Pinecone's similarity search.

Action Code

import app from "../../pinecone.app.mjs";
import utils from "../../common/utils.mjs";

export default {
  key: "pinecone-delete-vectors",
  name: "Delete Vectors",
  description: "Deletes one or more vectors by ID, from a single namespace. [See the documentation](https://docs.pinecone.io/reference/api/data-plane/delete).",
  type: "action",
  version: "0.0.2",
  props: {
    app,
    indexName: {
      propDefinition: [
        app,
        "indexName",
      ],
    },
    prefix: {
      propDefinition: [
        app,
        "prefix",
      ],
    },
    namespace: {
      propDefinition: [
        app,
        "namespace",
      ],
    },
    ids: {
      type: "string[]",
      label: "Vector IDs",
      description: "The IDs of the vectors. E.g. `[\"vec1\", \"vec2\"]`",
      propDefinition: [
        app,
        "vectorId",
      ],
    },
  },
  methods: {
    deleteVector(args = {}) {
      return this.app.post({
        path: "/vectors/delete",
        ...args,
      });
    },
  },
  async run({ $: step }) {
    const {
      deleteVector,
      indexName,
      ids,
      namespace,
    } = this;

    await deleteVector({
      step,
      indexName,
      data: {
        ids: utils.parseArray(ids),
        namespace,
      },
    });

    step.export("$summary", "Successfully deleted vectors");
    return {
      success: true,
    };
  },
};

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
PineconeappappThis component uses the Pinecone app.
Index NameindexNamestringSelect a value from the drop down menu.
Prefixprefixstring

The vector IDs to fetch. Does not accept values containing spaces. E.g. my-prefix

Namespacenamespacestring

The namespace to use.

Vector IDsidsstring[]

The IDs of the vectors. E.g. ["vec1", "vec2"]

Action Authentication

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

To connect your Pinecone account to Pipedream,

  1. Open the Pinecone console and click "API Keys"
  2. Copy the API key and Environment values and paste each below

About Pinecone

Long-term Memory for AI. The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.

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