← Jotform + Scale AI integrations

Create Text Annotation Task with Scale AI API on New Submission (Instant) from Jotform API

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New Submission (Instant) from the Jotform 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 Jotform trigger and Scale AI action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Select this integration
  2. Configure the New Submission (Instant) trigger
    1. Connect your Jotform account
    2. Optional- Select a Team
    3. Select a Form
  3. 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
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. 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

Description:Emit new event when a form is submitted
Version:0.1.5
Key:jotform-new-submission

Jotform Overview

Jotform’s API is a powerhouse for automating form and survey data management. With Pipedream, harness this API to trigger workflows from new form submissions, manipulate and analyze your form data, and sync it across various platforms. Think streamlined data entry to CRMs, instant notifications for new leads or feedback, and timely data backups to cloud storage.

Trigger Code

import jotform from "../../jotform.app.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  key: "jotform-new-submission",
  name: "New Submission (Instant)",
  description: "Emit new event when a form is submitted",
  version: "0.1.5",
  type: "source",
  dedupe: "unique",
  props: {
    jotform,
    http: "$.interface.http",
    teamId: {
      propDefinition: [
        jotform,
        "teamId",
      ],
    },
    formId: {
      propDefinition: [
        jotform,
        "formId",
        (c) => ({
          teamId: c.teamId,
          excludeDeleted: true,
        }),
      ],
    },
  },
  hooks: {
    async deploy() {
      const { content: form } = await this.jotform.getForm(this.formId, this.teamId);
      const { content: submissions } = await this.jotform.getFormSubmissions({
        formId: this.formId,
        teamId: this.teamId,
        params: {
          limit: 25,
          orderby: "created_at",
        },
      });
      for (let submission of submissions.reverse()) {
        const meta = {
          id: submission.id,
          summary: form.title,
          ts: Date.now(),
        };
        this.$emit(submission, meta);
      }
    },
    async activate() {
      return (await this.jotform.createHook({
        endpoint: this.http.endpoint,
        formId: this.formId,
        teamId: this.teamId,
      }));
    },
    async deactivate() {
      return (await this.jotform.deleteHook({
        endpoint: this.http.endpoint,
        formId: this.formId,
        teamId: this.teamId,
      }));
    },
  },
  async run(event) {
    const { body } = event;
    let { content: submission } = await this.jotform.getFormSubmission({
      submissionId: body.submissionID,
      teamId: this.teamId,
    });

    // insert answers from the webhook event
    const rawRequest = JSON.parse(body.rawRequest);
    for (const key of Object.keys(rawRequest)) {
      const regex = /^q(\d+)_/;
      const match = key.match(regex);
      if (match && match[1]) {
        submission.answers[match[1]].answer = rawRequest[key];
      }
    }

    this.$emit(submission, {
      summary: body.formTitle || JSON.stringify(body),
      id: body.submissionID,
      ts: Date.now(),
    });
  },
  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.
LabelPropTypeDescription
JotformjotformappThis component uses the Jotform app.
N/Ahttp$.interface.httpThis component uses $.interface.http to generate a unique URL when the component is first instantiated. Each request to the URL will trigger the run() method of the component.
TeamteamIdstringSelect a value from the drop down menu.
FormformIdstringSelect a value from the drop down menu.

Trigger Authentication

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

About Jotform

Jotform enables you to create online forms, collect responses directly in your email, and create fillable PDF forms.

Action

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

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.

LabelPropTypeDescription
Scale AIappappThis component uses the Scale AI app.
ProjectprojectstringSelect a value from the drop down menu.
Batchbatchstring

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.

Instructioninstructionstring

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 URLcallbackUrlstring

The full url (including the scheme http:// or https://) or email address of the callback that will be used when the task is completed.

Titletitlestring

The title of the task to be shown to scalers.

Descriptiondescriptionstring

The description of the task to be shown to scalers.

Responses RequiredresponsesRequiredinteger

The number of responses required for the task to build consensus before returning the callback response. Upper bound of 100.

Prioritypriorityinteger

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 IDuniqueIdstring

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 ErrorclearUniqueIdOnErrorboolean

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 FieldsnumberOfFieldsinteger

The number of fields to be labeled

Number of AttachmentsnumberOfAttachmentsinteger

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.

Sign in and copy your API key directly from your dashboard.

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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