Create Text Annotation Task with Scale AI API on New DynamoDB Stream Event from AWS API

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New DynamoDB Stream Event from the AWS API

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Create Text Annotation 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 DynamoDB Stream Event trigger
1. Connect your AWS account
2. Configure timer
3. Select a AWS Region
4. Select a Stream
Configure the Create Text Annotation Task action
1. Connect your Scale AI account
2. Optional- Select a Project
3. Optional- Configure Batch
4. Optional- Configure Instruction
5. Optional- Configure Callback URL
6. Optional- Configure Title
7. Optional- Configure Description
8. Optional- Configure Responses Required
9. Optional- Configure Priority
10. Optional- Configure Unique ID
11. Optional- Configure Clear Unique ID on Error
12. Configure Number of Fields
13. Configure Number of Attachments
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 DynamoDB Stream Event on AWS

Description:Emit new event when a DynamoDB stream receives new events. [See the docs here](https://docs.aws.amazon.com/amazondynamodb/latest/APIReference/API_streams_GetRecords.html)

Version:0.0.6

Key:aws-new-dynamodb-stream-event

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-dynamodb-streams.mjs";

export default {
  ...common,
  key: "aws-new-dynamodb-stream-event",
  name: "New DynamoDB Stream Event",
  description: "Emit new event when a DynamoDB stream receives new events. [See the docs here](https://docs.aws.amazon.com/amazondynamodb/latest/APIReference/API_streams_GetRecords.html)",
  type: "source",
  version: "0.0.6",
  dedupe: "unique",
  props: {
    ...common.props,
    stream: {
      type: "string",
      label: "Stream",
      description: "ARN of the Stream to watch for new events",
      async options({ prevContext }) {
        const {
          streams,
          lastEvaluatedStreamArn,
        } = await this.listEnabledStreams({
          ExclusiveStartStreamArn: prevContext.lastEvaluatedStreamArn,
        });
        const options = streams.map((stream) => ({
          label: `${stream.TableName} - Created ${stream.StreamLabel}`,
          value: stream.StreamArn,
        }));
        return {
          options,
          context: {
            lastEvaluatedStreamArn,
          },
        };
      },
    },
  },
  hooks: {
    async deploy() {
      const {
        stream,
        _getShardIterators,
        _setShardIterators,
        listShards,
        getShardIterator,
      } = this;

      const shardIterators = _getShardIterators();

      const { StreamDescription: streamDescription } = await listShards({
        StreamArn: stream,
        Limit: 100,
      });

      if (streamDescription?.Shards?.length === 0) {
        throw new Error("No shards found in stream");
      }

      const activeShards =
        streamDescription.Shards
          .filter((shard) => !shard.SequenceNumberRange.EndingSequenceNumber);

      if (activeShards.length === 0) {
        throw new Error("No active shards found");
      }

      const shardIds = activeShards.map(({ ShardId }) => ShardId);

      for (const shardId of shardIds) {
        const { ShardIterator: shardIterator } = await getShardIterator({
          ShardId: shardId,
          StreamArn: stream,
          ShardIteratorType: "LATEST",
        });
        shardIterators[shardId] = shardIterator;
      }

      _setShardIterators(shardIterators);
    },
  },
  methods: {
    ...common.methods,
    _getShardIterators() {
      return this.db.get("shardIterators") || {};
    },
    _setShardIterators(value) {
      this.db.set("shardIterators", value);
    },
    generateMeta({
      eventID, eventName, dynamodb,
    }) {
      return {
        id: eventID,
        summary: `New Event: ${eventName}`,
        ts: Date.parse(dynamodb.ApproximateCreationDateTime),
      };
    },
  },
  async run() {
    const {
      stream,
      isStreamEnabled,
      _getShardIterators,
      _setShardIterators,
      getRecords,
      generateMeta,
    } = this;

    if (!(await isStreamEnabled(stream))) {
      throw new Error("Stream is no longer enabled.");
    }

    const shardIterators = _getShardIterators();

    for (const [
      shardId,
      shardIterator,
    ] of Object.entries(shardIterators)) {
      if (!shardIterator) {
        continue;
      }

      const {
        Records: records,
        NextShardIterator: nextShardIterator,
      } = await getRecords({
        ShardIterator: shardIterator,
        Limit: 100,
      });

      for (const record of records) {
        const meta = generateMeta(record);
        this.$emit(record, meta);
      }

      shardIterators[shardId] = nextShardIterator;
    }

    _setShardIterators(shardIterators);
  },
};

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.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
AWS Region	`region`	`string`	Select a value from the drop down menu.
Stream	`stream`	`string`	Select a value from the drop down menu.

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 Text Annotation Task on Scale AI

Description:Create a text annotation task. [See the documentation](https://docs.scale.com/reference/text-collection)

Version:0.0.3

Key:scale_ai-create-text-annotation-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-text-annotation-task",
  name: "Create Text Annotation Task",
  description: "Create a text annotation task. [See the documentation](https://docs.scale.com/reference/text-collection)",
  type: "action",
  version: "0.0.3",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: false,
  },
  props: {
    app,
    project: {
      propDefinition: [
        app,
        "project",
      ],
    },
    batch: {
      propDefinition: [
        app,
        "batch",
      ],
    },
    instruction: {
      propDefinition: [
        app,
        "instruction",
      ],
    },
    callbackUrl: {
      propDefinition: [
        app,
        "callbackUrl",
      ],
    },
    title: {
      type: "string",
      label: "Title",
      description: "The title of the task to be shown to scalers.",
      optional: true,
    },
    description: {
      type: "string",
      label: "Description",
      description: "The description of the task to be shown to scalers.",
      optional: true,
    },
    responsesRequired: {
      type: "integer",
      label: "Responses Required",
      description: "The number of responses required for the task to build consensus before returning the callback response. Upper bound of 100.",
      optional: true,
    },
    priority: {
      propDefinition: [
        app,
        "priority",
      ],
    },
    uniqueId: {
      propDefinition: [
        app,
        "uniqueId",
      ],
    },
    clearUniqueIdOnError: {
      type: "boolean",
      label: "Clear Unique ID on Error",
      description: "If set to be true, if a task errors out after being submitted, the **Unique ID** on the task will be unset. This param allows workflows where you can re-submit the same **Unique ID** to recover from errors automatically.",
      optional: true,
    },
    numberOfFields: {
      type: "integer",
      label: "Number of Fields",
      description: "The number of fields to be labeled",
      default: 1,
      reloadProps: true,
    },
    numberOfAttachments: {
      type: "integer",
      label: "Number of Attachments",
      description: "The number of attachments to be labeled",
      default: 1,
      reloadProps: true,
    },
  },
  methods: {
    choiceFieldsPropsMapper(prefix) {
      const {
        [`${prefix}label`]: label,
        [`${prefix}value`]: value,
        [`${prefix}hint`]: hint,
      } = this;

      return {
        label,
        value,
        hint,
      };
    },
    getChoiceFieldPropDefinitions({
      prefix, label,
    } = {}) {
      return {
        [`${prefix}label`]: {
          type: "string",
          label: `${label} - Label`,
          description: "The label of the choice.",
        },
        [`${prefix}value`]: {
          type: "string",
          label: `${label} - Value`,
          description: "The value of the choice.",
        },
        [`${prefix}hint`]: {
          type: "string",
          label: `${label} - Hint`,
          description: "The hint of the choice.",
          optional: true,
        },
      };
    },
    fieldsPropsMapper(prefix) {
      const {
        [`${prefix}type`]: type,
        [`${prefix}fieldId`]: fieldId,
        [`${prefix}title`]: title,
        [`${prefix}numberOfChoices`]: numberOfChoices,
        choiceFieldsPropsMapper,
      } = this;

      return {
        type,
        field_id: fieldId,
        title,
        choices: utils.getFieldsProps({
          numberOfFields: numberOfChoices,
          fieldName: "choice",
          prefix,
          propsMapper: choiceFieldsPropsMapper,
        }),
      };
    },
    getFieldsPropDefinitions({
      prefix,
      label,
    } = {}) {
      const {
        [`${prefix}numberOfChoices`]: numberOfChoices,
        getChoiceFieldPropDefinitions,
      } = this;

      return {
        [`${prefix}type`]: {
          type: "string",
          label: `${label} - Type`,
          description: "The type of field to be labeled.",
          optional: true,
          options: Object.values(constants.FIELD_CHOICE_TYPE),
        },
        [`${prefix}fieldId`]: {
          type: "string",
          label: `${label} - Field ID`,
          description: "A unique identifier for the field.",
          optional: true,
        },
        [`${prefix}title`]: {
          type: "string",
          label: `${label} - Title`,
          description: "The title of the field.",
          optional: true,
        },
        [`${prefix}numberOfChoices`]: {
          type: "integer",
          label: `${label} - Number of Choices`,
          description: "The number of choices for the field.",
          optional: true,
          default: 1,
          reloadProps: true,
        },
        ...utils.getAdditionalProps({
          numberOfFields: numberOfChoices,
          fieldName: "choice",
          prefix,
          label,
          getPropDefinitions: getChoiceFieldPropDefinitions,
        }),
      };
    },
    attachmentsPropsMapper(prefix) {
      const {
        [`${prefix}type`]: type,
        [`${prefix}content`]: content,
      } = this;

      return {
        type,
        content,
      };
    },
    getAttachmentsPropDefinitions({
      prefix,
      label,
    } = {}) {
      return {
        [`${prefix}type`]: {
          type: "string",
          label: `${label} - Type`,
          description: "The type of attachment. See [TextCollectionAttachment](https://docs.scale.com/reference/textcollectionattachment). One of `pdf`, `image`, `text`, `video`, `website`, or `audio`.",
          optional: true,
          options: Object.values(constants.ATTACHMENT_TYPE),
        },
        [`${prefix}content`]: {
          type: "string",
          label: `${label} - Content`,
          description: "The content of the attachment. See [TextCollectionAttachment](https://docs.scale.com/reference/textcollectionattachment).",
          optional: true,
        },
      };
    },
    createTextAnnotationTask(args = {}) {
      return this.app.post({
        path: "/task/textcollection",
        ...args,
      });
    },
  },
  async additionalProps() {
    const {
      numberOfFields,
      numberOfAttachments,
      getFieldsPropDefinitions,
      getAttachmentsPropDefinitions,
    } = this;

    const fields =  utils.getAdditionalProps({
      numberOfFields,
      fieldName: "field",
      getPropDefinitions: getFieldsPropDefinitions,
    });

    const attachments =  utils.getAdditionalProps({
      numberOfFields: numberOfAttachments,
      fieldName: "attachment",
      getPropDefinitions: getAttachmentsPropDefinitions,
    });

    return {
      ...fields,
      ...attachments,
    };
  },
  async run({ $: step }) {
    const {
      createTextAnnotationTask,
      project,
      batch,
      instruction,
      callbackUrl,
      title,
      description,
      responsesRequired,
      priority,
      uniqueId,
      clearUniqueIdOnError,
      numberOfFields,
      fieldsPropsMapper,
      numberOfAttachments,
      attachmentsPropsMapper,
    } = this;

    const response = await createTextAnnotationTask({
      step,
      data: {
        project,
        batch,
        instruction,
        callback_url: callbackUrl,
        title,
        description,
        responses_required: responsesRequired,
        priority,
        unique_id: uniqueId,
        clear_unique_id_on_error: clearUniqueIdOnError,
        fields: utils.getFieldsProps({
          numberOfFields,
          fieldName: "field",
          propsMapper: fieldsPropsMapper,
        }),
        attachments: utils.getFieldsProps({
          numberOfFields: numberOfAttachments,
          fieldName: "attachment",
          propsMapper: attachmentsPropsMapper,
        }),
      },
    });

    step.export("$summary", `Successfully created text annotation task with ID \`${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.
Batch	`batch`	`string`	The name of the batch to associate this task with. Note that if a batch is specified, you need not specify the project, as the task will automatically be associated with the batch's project. For Scale Rapid projects specifying a batch is required. See Batches section for more details.
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.
Title	`title`	`string`	The title of the task to be shown to scalers.
Description	`description`	`string`	The description of the task to be shown to scalers.
Responses Required	`responsesRequired`	`integer`	The number of responses required for the task to build consensus before returning the callback response. Upper bound of 100.
Priority	`priority`	`integer`	A value of 10, 20, or 30 that defines the priority of a task within a project. The higher the number, the higher the priority.
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.
Clear Unique ID on Error	`clearUniqueIdOnError`	`boolean`	If set to be true, if a task errors out after being submitted, the Unique ID on the task will be unset. This param allows workflows where you can re-submit the same Unique ID to recover from errors automatically.
Number of Fields	`numberOfFields`	`integer`	The number of fields to be labeled
Number of Attachments	`numberOfAttachments`	`integer`	The number of attachments to be labeled

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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