Delete Vectors with Pinecone API on New or Removed Documents in a Collection from Fauna API

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New or Removed Documents in a Collection from the Fauna API

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Delete Vectors with the Pinecone API

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Getting Started#

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

Select this integration
Configure the New or Removed Documents in a Collection trigger
1. Configure timer
2. Connect your Fauna account
3. Select a Collection
4. Optional- Configure Emit changes as a single event
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
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 or Removed Documents in a Collection on Fauna

Description:Emit new event each time you add or remove a document from a specific collection, with the details of the document.

Version:0.0.8

Key:faunadb-changes-to-collection

View on GitHub

Fauna Overview#

Fauna API offers a powerful serverless database solution for modern applications. Its unique capabilities allow for highly scalable, secure, and flexible data management. With Pipedream, you can harness the power of Fauna to create intricate serverless workflows that react to various triggers, manage data efficiently, and connect seamlessly with other services and APIs to automate complex tasks.

Trigger Code#

import fauna from "../../faunadb.app.mjs";
import _ from "lodash";
import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";

export default {
  type: "source",
  key: "faunadb-changes-to-collection",
  name: "New or Removed Documents in a Collection",
  description: "Emit new event each time you add or remove a document from a specific collection, with the details of the document.",
  version: "0.0.8",
  dedupe: "unique", // Dedupe events based on the concatenation of event + document ref id
  props: {
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    db: "$.service.db",
    fauna,
    collection: {
      propDefinition: [
        fauna,
        "collections",
      ],
    },
    emitEventsInBatch: {
      type: "boolean",
      label: "Emit changes as a single event",
      description:
        "If `true`, all events are emitted as an array, within a single Pipedream event. Defaults to `false`, emitting each event in Fauna as its own event in Pipedream",
      optional: true,
      default: false,
    },
  },
  async run() {
    // As soon as the script runs, mark the start time so we can fetch changes
    // since this time on the next run. Fauna expects epoch ms as its cursor.
    const ts = +new Date() * 1000;
    const cursor = this.db.get("cursor") || ts;

    const events = await this.fauna.getEventsInCollectionAfterTs(
      this.collection,
      cursor,
    );

    if (!events.length) {
      console.log(`No new events in collection ${this.collection}`);
      this.db.set("cursor", ts);
      return;
    }

    console.log(`${events.length} new events in collection ${this.collection}`);

    // Batched emits do not take advantage of the built-in deduper
    if (this.emitEventsInBatch) {
      this.$emit({
        events,
      }, {
        summary: `${events.length} new event${events.length > 1
          ? "s"
          : ""}`,
        id: cursor,
      });
    } else {
      for (const event of events) {
        this.$emit(event, {
          summary: `${event.action.toUpperCase()} - ${event.document.id}`,
          id: `${event.action}-${event.document.id}`, // dedupes events based on this ID
        });
      }
    }

    // Finally, set cursor for the next run to the max timestamp of the changed events, ensuring we
    // get all events after that on the next run. We need to add 1 since the timestamp filter in
    // Fauna is inclusive: https://docs.fauna.com/fauna/current/api/fql/functions/paginate
    const maxEventTs = _.maxBy(events, (event) => event.ts).ts + 1;

    this.db.set("cursor", maxEventTs);
  },
};

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
	`timer`	`$.interface.timer`
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Fauna	`fauna`	`app`	This component uses the Fauna app.
Collection	`collection`	`string`	Select a value from the drop down menu.
Emit changes as a single event	`emitEventsInBatch`	`boolean`	If `true`, all events are emitted as an array, within a single Pipedream event. Defaults to `false`, emitting each event in Fauna as its own event in Pipedream

Trigger Authentication#

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

Create a key in the Security section of your FaunaDB dashboard, then enter the Secret below.

About Fauna#

The distributed serverless database combining the flexibility of NoSQL with the relational querying capabilities of SQL systems.

Action#

Delete Vectors on Pinecone

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

View on GitHub

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.

Label	Prop	Type	Description
Pinecone	`app`	`app`	This component uses the Pinecone app.
Index Name	`indexName`	`string`	Select a value from the drop down menu.
Prefix	`prefix`	`string`	The vector IDs to fetch. Does not accept values containing spaces. E.g. `my-prefix`
Namespace	`namespace`	`string`	The namespace to use.
Vector IDs	`ids`	`string[]`	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,