Create Document Transcription Task with Scale AI 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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Create Document Transcription Task with the Scale AI API

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Getting Started#

This integration creates a workflow with a AWS trigger and Scale AI 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 Create Document Transcription Task action
1. Connect your Scale AI account
2. Optional- Select a Project
3. Optional- Configure Instruction
4. Optional- Configure Callback URL
5. Optional- Configure Attachment
6. Optional- Configure Attachments
7. Optional- Configure Language
8. Optional- Select a Geometry
9. Optional- Configure Unique ID
10. Configure Number Of Features
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:0.2.3

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: "0.2.3",
  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#

Create Document Transcription Task on Scale AI

Description:Create a document transcription task. [See the documentation](https://docs.scale.com/reference/document-transcription-1)

Version:0.0.3

Key:scale_ai-create-document-transcription-task

View on GitHub

Scale AI Overview#

Scale AI offers an API to automate and streamline data labeling for machine learning applications, providing access to a global workforce and sophisticated tools. With Scale AI's API on Pipedream, you can integrate scalable data annotation workflows directly into your apps. Trigger tasks, manage datasets, and receive annotated data, all within Pipedream's serverless platform. This enables seamless automation of labeling tasks, integration with machine learning pipelines, and real-time updates on annotations.

Action Code#

import app from "../../scale_ai.app.mjs";
import utils from "../../common/utils.mjs";
import constants from "../../common/constants.mjs";

export default {
  key: "scale_ai-create-document-transcription-task",
  name: "Create Document Transcription Task",
  description: "Create a document transcription task. [See the documentation](https://docs.scale.com/reference/document-transcription-1)",
  type: "action",
  version: "0.0.3",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: false,
  },
  props: {
    app,
    project: {
      propDefinition: [
        app,
        "project",
      ],
    },
    instruction: {
      propDefinition: [
        app,
        "instruction",
      ],
    },
    callbackUrl: {
      propDefinition: [
        app,
        "callbackUrl",
      ],
    },
    attachment: {
      description: "The url of the attachment of the data to be collected. We will use the HTTP content type to determine the type of the attachment. Either **Attachment** or **Attachments** is required. You can supply attachments instead of attachment if needed.",
      propDefinition: [
        app,
        "attachment",
      ],
    },
    attachments: {
      type: "string[]",
      label: "Attachments",
      description: "Used instead of **Attachment** - The urls of a multi-page document. Either **Attachment** or **Attachments** is required.",
      optional: true,
    },
    lang: {
      type: "string",
      label: "Language",
      description: "Language of the attachment. Defaults to `en-U`.",
      optional: true,
      default: "en-US",
    },
    geometry: {
      type: "string",
      label: "Geometry",
      description: "Geometry type for the annotations. Supported values are `box` for axis-aligned rectangles or `polygon` for rotated rectangles. Defaults to `box`.",
      optional: true,
      options: Object.values(constants.GEOMETRY_TYPE),
      default: constants.GEOMETRY_TYPE.BOX,
    },
    uniqueId: {
      propDefinition: [
        app,
        "uniqueId",
      ],
    },
    numberOfFeatures: {
      type: "integer",
      label: "Number Of Features",
      description: "The number of features to be collected. Defaults to `1`.",
      default: 1,
      reloadProps: true,
    },
  },
  methods: {
    featuresPropsMapper(prefix) {
      const {
        [`${prefix}type`]: type,
        [`${prefix}label`]: label,
        [`${prefix}title`]: title,
        [`${prefix}flags`]: flags,
      } = this;

      return {
        type,
        label,
        title,
        flags,
      };
    },
    getFeaturesPropDefinitions({
      prefix,
      label,
    } = {}) {
      return {
        [`${prefix}type`]: {
          type: "string",
          label: `${label} - Type`,
          description: "One of `text`, `block`, or `group`. See \"Feature Types\" for more information.",
          options: Object.values(constants.FEATURE_TYPE),
        },
        [`${prefix}label`]: {
          type: "string",
          label: `${label} - Label`,
          description: "Label for the annotation. It is required for block and text features.",
          optional: true,
        },
        [`${prefix}title`]: {
          type: "string",
          label: `${label} - Title`,
          description: "For `group`-type features, a group title must be provided as opposed to a label since a group itself is not labeled.",
          optional: true,
        },
        [`${prefix}flags`]: {
          type: "string[]",
          label: `${label} - Flags`,
          description: "A list of ContentFlag values. Content flags allow Scale to transcribe documents more effectively by enabling special tooling or modifying the default behavior for certain features.",
          optional: true,
          options: Object.values(constants.CONTENT_FLAG),
        },
      };
    },
    createDocumentTranscriptionTask(args = {}) {
      return this.app.post({
        path: "/task/documenttranscription",
        ...args,
      });
    },
  },
  async additionalProps() {
    const {
      numberOfFeatures,
      getFeaturesPropDefinitions,
    } = this;

    return utils.getAdditionalProps({
      numberOfFields: numberOfFeatures,
      fieldName: "feature",
      getPropDefinitions: getFeaturesPropDefinitions,
    });
  },
  async run({ $: step }) {
    const {
      createDocumentTranscriptionTask,
      project,
      instruction,
      callbackUrl,
      attachment,
      attachments,
      lang,
      geometry,
      uniqueId,
      numberOfFeatures,
      featuresPropsMapper,
    } = this;

    const response = await createDocumentTranscriptionTask({
      step,
      data: {
        project,
        instruction,
        callback_url: callbackUrl,
        attachment,
        attachments,
        lang,
        geometry,
        unique_id: uniqueId,
        features: utils.getFieldsProps({
          numberOfFields: numberOfFeatures,
          fieldName: "feature",
          propsMapper: featuresPropsMapper,
        }),
      },
    });

    step.export("$summary", `Successfully created document transcription task with ID  \`${response.task_id}\``);

    return response;
  },
};

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
Scale AI	`app`	`app`	This component uses the Scale AI app.
Project	`project`	`string`	Select a value from the drop down menu.
Instruction	`instruction`	`string`	A markdown-enabled string or iframe embedded Google Doc explaining how to do the task. You can use markdown to show example images, give structure to your instructions, and more. See our instruction best practices for more details. For Scale Rapid projects, DO NOT set this field unless you specifically want to override the project level instructions.
Callback URL	`callbackUrl`	`string`	The full url (including the scheme `http://` or `https://`) or email address of the callback that will be used when the task is completed.
Attachment	`attachment`	`string`	The url of the attachment of the data to be collected. We will use the HTTP content type to determine the type of the attachment. Either Attachment or Attachments is required. You can supply attachments instead of attachment if needed.
Attachments	`attachments`	`string[]`	Used instead of Attachment - The urls of a multi-page document. Either Attachment or Attachments is required.
Language	`lang`	`string`	Language of the attachment. Defaults to `en-U`.
Geometry	`geometry`	`string`	Select a value from the drop down menu:`boxpolygon`
Unique ID	`uniqueId`	`string`	A arbitrary ID that you can assign to a task and then query for later. This ID must be unique across all projects under your account, otherwise the task submission will be rejected. See Avoiding Duplicate Tasks for more details.
Number Of Features	`numberOfFeatures`	`integer`	The number of features to be collected. Defaults to `1`.

Action Authentication#

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

About Scale AI#

Make the best models with the best data. Scale Data Engine leverages your enterprise data, and with Scale Generative AI Platform, safely unlocks the value of AI.

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Pipedream makes it easy to connect APIs for Scale AI, AWS and 2,900+ other apps remarkably fast.

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

Developers ♥ Pipedream

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