← AWS + Pinecone integrations

Delete Vectors with Pinecone API on New Deleted S3 File from AWS API

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New Deleted S3 File from the AWS API
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Delete Vectors with the Pinecone API
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Getting Started

This integration creates a workflow with a AWS 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 Deleted S3 File trigger
    1. Connect your AWS account
    2. Select a AWS Region
    3. Select a S3 Bucket Name
    4. Configure Ignore Delete Markers
  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 file is deleted from a S3 bucket
Version:0.1.2
Key:aws-s3-deleted-file

AWS Overview

The AWS API unlocks endless possibilities for automation with Pipedream. With this powerful combo, you can manage your AWS services and resources, automate deployment workflows, process data, and react to events across your AWS infrastructure. Pipedream offers a serverless platform for creating workflows triggered by various events that can execute AWS SDK functions, making it an efficient tool to integrate, automate, and orchestrate tasks across AWS services and other apps.

Trigger Code

import base from "../common/s3.mjs";

export default {
  ...base,
  type: "source",
  key: "aws-s3-deleted-file",
  name: "New Deleted S3 File",
  description: "Emit new event when a file is deleted from a S3 bucket",
  version: "0.1.2",
  dedupe: "unique",
  props: {
    ...base.props,
    ignoreDeleteMarkers: {
      type: "boolean",
      label: "Ignore Delete Markers",
      description: "When ignoring delete markers this will only emit events for permanently deleted files",
      default: false,
    },
  },
  methods: {
    ...base.methods,
    getEvents() {
      return [
        this.ignoreDeleteMarkers
          ? "s3:ObjectRemoved:Delete"
          : "s3:ObjectRemoved:*",
      ];
    },
    generateMeta(data) {
      const { "x-amz-request-id": id } = data.responseElements;
      const { key } = data.s3.object;
      const { eventTime: isoTimestamp } = data;
      return {
        id,
        summary: `Deleted file: '${key}'`,
        ts: Date.parse(isoTimestamp),
      };
    },
  },
};

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
AWSawsappThis component uses the AWS app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
N/Ahttp$.interface.httpThis 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.
AWS RegionregionstringSelect a value from the drop down menu.
S3 Bucket NamebucketstringSelect a value from the drop down menu.
Ignore Delete MarkersignoreDeleteMarkersboolean

When ignoring delete markers this will only emit events for permanently deleted files

Trigger Authentication

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

Follow the AWS Instructions for creating an IAM user with an associated access and secret key.

As a best practice, attach the minimum set of IAM permissions necessary to perform the specific task in Pipedream. If your workflow only needs to perform a single API call, you should create a user and associate an IAM group / policy with permission to do only that task. You can create as many linked AWS accounts in Pipedream as you'd like.

Enter your access and secret key below.

About AWS

Amazon Web Services (AWS) offers reliable, scalable, and inexpensive cloud computing services.

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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