Delete Vectors with Pinecone API on New Records Returned by CloudWatch Logs Insights Query from AWS API

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New Records Returned by CloudWatch Logs Insights Query 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.

Select this integration
Configure the New Records Returned by CloudWatch Logs Insights Query trigger
1. Connect your AWS account
2. Select a AWS Region
3. Select one or more CloudWatch Log Groups
4. Configure Logs Insights Query
5. Optional- Configure Emit query results as a single event
6. Configure Polling schedule
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 Records Returned by CloudWatch Logs Insights Query on AWS

Description:Executes a CloudWatch Logs Insights query on a schedule, and emits the records as invidual events (default) or in batch

Version:0.2.2

Key:aws-new-records-returned-by-cloudwatch-logs-insights-query

View on GitHub

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 common from "../../common/common-cloudwatch-logs.mjs";
import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";

export default {
  ...common,
  key: "aws-new-records-returned-by-cloudwatch-logs-insights-query",
  name: "New Records Returned by CloudWatch Logs Insights Query",
  // eslint-disable-next-line pipedream/source-description
  description: "Executes a CloudWatch Logs Insights query on a schedule, and emits the records as invidual events (default) or in batch",
  version: "0.2.2",
  type: "source",
  props: {
    aws: common.props.aws,
    region: common.props.region,
    db: "$.service.db",
    // eslint-disable-next-line pipedream/props-label
    logGroupNames: {
      ...common.props.logGroupName,
      type: "string[]",
      description: "The log groups you'd like to query",
    },
    queryString: {
      label: "Logs Insights Query",
      description: "The query you'd like to run. See [this AWS doc](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/CWL_QuerySyntax.html) for help with query syntax",
      type: "string",
    },
    emitResultsInBatch: {
      type: "boolean",
      label: "Emit query results as a single event",
      description: "If `true`, all events are emitted as an array, within a single Pipedream event. If `false`, each row of results is emitted as its own event. Defaults to `true`",
      optional: true,
      default: true,
    },
    timer: {
      label: "Polling schedule",
      description: "How often you want to query CloudWatch Logs Insights for results",
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
  },
  async run() {
    const now = +new Date();
    const startTime = this.db.get("startTime") || now - 1000 * 60 * 60;

    // First, start the query
    const params = {
      queryString: this.queryString,
      startTime,
      endTime: now,
      logGroupNames: this.logGroupNames,
    };

    const { queryId } = await this.startQuery(params);

    // Then poll for its status, emitting each record as its own event when completed
    async function sleep(ms) {
      return new Promise((r) => setTimeout(r, ms));
    }

    let result, res;
    do {
      await sleep(1000);
      res = await this.getQueryResults({
        queryId,
      });
      result = res.status;
    } while (result === "Running" || result === "Scheduled");

    if (result !== "Complete") {
      throw new Error(`Query ${queryId} failed with status ${result}`);
    }

    console.log(JSON.stringify(res, null, 2));
    const { results } = res;

    if (!results || !results.length) {
      console.log("No results, exiting");
      this.db.set("startTime", now);
      return;
    }

    if (this.emitResultsInBatch === true) {
      this.$emit(results, {
        summary: JSON.stringify(results),
      });
    } else {
      for (const item of results) {
        this.$emit(item, {
          summary: JSON.stringify(item),
        });
      }
    }

    // The next time this source runs, query for data starting now
    this.db.set("startTime", now);
  },
};

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
AWS	`aws`	`app`	This component uses the AWS app.
AWS Region	`region`	`string`	Select a value from the drop down menu.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
CloudWatch Log Groups	`logGroupNames`	`string[]`	Select a value from the drop down menu.
Logs Insights Query	`queryString`	`string`	The query you'd like to run. See this AWS doc for help with query syntax
Emit query results as a single event	`emitResultsInBatch`	`boolean`	If `true`, all events are emitted as an array, within a single Pipedream event. If `false`, each row of results is emitted as its own event. Defaults to `true`
Polling schedule	`timer`	`$.interface.timer`	How often you want to query CloudWatch Logs Insights for results

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#

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,

Open the Pinecone console and click "API Keys"
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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Delete Vectors with Pinecone API on New Records Returned by CloudWatch Logs Insights Query from AWS API

Pipedream makes it easy to connect APIs for Pinecone, AWS and 2,400+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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