Create Text Annotation Task with Scale AI API on New Render Completed from MoDeck API

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New Render Completed from the MoDeck 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 MoDeck 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 Render Completed trigger
1. Connect your MoDeck account
2. Configure Polling interval
3. Select a Deck Name
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 Render Completed on MoDeck

Description:Emit new event when a render is completed.

Version:0.0.1

Key:modeck-render-complete

View on GitHub

MoDeck Overview#

The MoDeck API offers an interface for managing playlists and videos within their platform, providing endpoints for various operations like retrieving video details, updating playlists, or managing users. Integrating MoDeck with Pipedream allows you to automate interactions with your MoDeck data, such as syncing playlists, updating video statuses, or triggering actions based on video analytics. With Pipedream's serverless platform, you can build powerful workflows that react to events in real-time, schedule tasks, and connect MoDeck with hundreds of other services.

Trigger Code#

import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";
import modeck from "../../modeck.app.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  key: "modeck-render-complete",
  name: "New Render Completed",
  version: "0.0.1",
  description: "Emit new event when a render is completed.",
  type: "source",
  dedupe: "unique",
  props: {
    modeck,
    db: "$.service.db",
    timer: {
      label: "Polling interval",
      description: "Pipedream will poll the MoDeck on this schedule",
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    deck: {
      propDefinition: [
        modeck,
        "deck",
      ],
    },
  },
  methods: {
    _getLastDate() {
      return this.db.get("lastDate") || 0;
    },
    _setLastDate(lastDate) {
      this.db.set("lastDate", lastDate);
    },
    async startEvent(maxResults = 0) {
      const {
        modeck,
        deck,
      } = this;

      const lastDate = this._getLastDate();

      const { renderList } = await modeck.listRenders({
        data: {
          deck,
        },
      });

      let responseArray = [];
      let count = 0;

      for (const render of renderList) {
        if (new Date(render.data) <= new Date(lastDate)) break;
        responseArray.push(render);
        if (maxResults && (++count === maxResults)) break;
      }
      if (responseArray.length) this._setLastDate(responseArray[0].date);

      for (const render of responseArray.reverse()) {
        this.$emit(
          render,
          {
            id: render.id,
            summary: `The render with id: "${render.id}" has been completed!`,
            ts: render.date,
          },
        );
      }
    },
  },
  hooks: {
    async deploy() {
      await this.startEvent(25);
    },
  },
  async run() {
    await this.startEvent();
  },
  sampleEmit,
};

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
MoDeck	`modeck`	`app`	This component uses the MoDeck app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Polling interval	`timer`	`$.interface.timer`	Pipedream will poll the MoDeck on this schedule
Deck Name	`deck`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

About MoDeck#

Create video templates in After Effects, make them editable online by anyone. You control the creative, let your team control the content.

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:0.0.2

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: "0.0.2",
  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