← PostgreSQL + Pinecone integrations

Delete Vectors with Pinecone API on New Row from PostgreSQL API

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New Row from the PostgreSQL API
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Delete Vectors with the Pinecone API
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Getting Started

This integration creates a workflow with a PostgreSQL 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 Row trigger
    1. Connect your PostgreSQL account
    2. Configure Polling Interval
    3. Select a Schema
    4. Select a Table
    5. Optional- Select a Column
  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 row is added to a table. [See the documentation](https://node-postgres.com/features/queries)
Version:3.0.6
Key:postgresql-new-row

PostgreSQL Overview

On Pipedream, you can leverage the PostgreSQL app to create workflows that automate database operations, synchronize data across platforms, and react to database events in real-time. Think handling new row entries, updating records from webhooks, or even compiling reports on a set schedule. Pipedream's serverless platform provides a powerful way to connect PostgreSQL with a variety of apps, enabling you to create tailored automation that fits your specific needs.

Trigger Code

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

export default {
  ...common,
  name: "New Row",
  key: "postgresql-new-row",
  description: "Emit new event when a new row is added to a table. [See the documentation](https://node-postgres.com/features/queries)",
  version: "3.0.6",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    schema: {
      propDefinition: [
        common.props.postgresql,
        "schema",
      ],
    },
    table: {
      propDefinition: [
        common.props.postgresql,
        "table",
        (c) => ({
          schema: c.schema,
        }),
      ],
    },
    column: {
      propDefinition: [
        common.props.postgresql,
        "column",
        (c) => ({
          schema: c.schema,
          table: c.table,
        }),
      ],
      description: "An ID or timestamp column where new rows will always contain larger values than the previous row. Defaults to the table's primary key.",
      optional: true,
    },
  },
  hooks: {
    /** If column prop is left blank, get the table's primary key to use
     * for ordering and deduping. */
    async deploy() {
      const column = this.column
        ? this.column
        : await this.postgresql.getPrimaryKey(this.table, this.schema);
      this._setColumn(column);

      await this.initialRows(this.schema, this.table, column);
    },
  },
  methods: {
    ...common.methods,
    _getColumn() {
      return this.db.get("column");
    },
    _setColumn(column) {
      this.db.set("column", column);
    },
    generateMeta(row, column) {
      return {
        id: row[column],
        summary: "New Row Added",
        ts: Date.now(),
      };
    },
  },
  async run() {
    const column = this._getColumn();
    const isColumnUnique = await this.isColumnUnique(this.schema, this.table, column);
    if (!isColumnUnique) {
      throw new Error("The column selected contains duplicate values. Column must be unique");
    }

    await this.newRows(this.schema, this.table, column);
  },
};

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
PostgreSQLpostgresqlappThis component uses the PostgreSQL app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
Polling Intervaltimer$.interface.timer

Pipedream will poll the API on this schedule

SchemaschemastringSelect a value from the drop down menu.
TabletablestringSelect a value from the drop down menu.
ColumncolumnstringSelect a value from the drop down menu.

Trigger Authentication

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

Connecting to Restricted Databases

Either enable the shared static IP for this account below, or configure a VPC to deploy any workflow in your workspace to a private network with a dedicated static IP. Learn more in our docs.

SSL Setup

Configure SSL on your PostgreSQL database by providing the CA (Certificate Authority), and choosing between Full Verification, Verify Certificate Authority (CA), or Skip Verification. Skipping verification is not recommended as this has serious security implications.

About PostgreSQL

PostgreSQL is a free and open-source relational database management system emphasizing extensibility and SQL compliance.

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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