Classify Text with MonkeyLearn API on New Submission (Instant) from Jotform API

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New Submission (Instant) from the Jotform API

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Classify Text with the MonkeyLearn API

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Getting Started#

This integration creates a workflow with a Jotform trigger and MonkeyLearn action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Submission (Instant) trigger
1. Connect your Jotform account
2. Optional- Select a Team
3. Select a Form
Configure the Classify Text action
1. Connect your MonkeyLearn account
2. Select a Classifier Id
3. Configure Data
4. Optional- Configure Production Model
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 Submission (Instant) on Jotform

Description:Emit new event when a form is submitted

Version:0.1.5

Key:jotform-new-submission

View on GitHub

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.

Label	Prop	Type	Description
Jotform	`jotform`	`app`	This component uses the Jotform app.
N/A	`http`	`$.interface.http`	This component uses `$.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.
Team	`teamId`	`string`	Select a value from the drop down menu.
Form	`formId`	`string`	Select 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#

Classify Text on MonkeyLearn

Description:Classifies texts with a given classifier. [See the docs here](https://monkeylearn.com/api/v3/#classify)

Version:0.0.1

Key:monkeylearn-classify-text

View on GitHub

MonkeyLearn Overview#

MonkeyLearn is a text analysis platform that employs machine learning to extract and process data from chunks of text. By leveraging the MonkeyLearn API on Pipedream, you can automate the categorization of text, extract specific data, analyze sentiment, and more, all in real-time. This enables the development of powerful custom workflows that can analyze customer feedback, automate email processing, or provide insightful analytics on textual data from various sources.

Action Code#

import app from "../../monkeylearn.app.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  key: "monkeylearn-classify-text",
  name: "Classify Text",
  description: "Classifies texts with a given classifier. [See the docs here](https://monkeylearn.com/api/v3/#classify)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    classifierId: {
      propDefinition: [
        app,
        "classifierId",
      ],
    },
    data: {
      propDefinition: [
        app,
        "data",
      ],
    },
    productionModel: {
      propDefinition: [
        app,
        "productionModel",
      ],
    },
  },
  async run({ $ }) {
    const {
      classifierId,
      data,
      productionModel,
    } = this;
    if (!data || !Array.isArray(data) || data.length === 0) {
      throw new ConfigurationError("Data array is required and must have at least one string to be classified.");
    }
    const response = await this.app.classifyText($, classifierId, data, productionModel);
    $.export("$summary", "Successfully classified all elements");
    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
MonkeyLearn	`app`	`app`	This component uses the MonkeyLearn app.
Classifier Id	`classifierId`	`string`	Select a value from the drop down menu.
Data	`data`	`string[]`	A list of up to 500 data elements. Each element must be a string with the text.
Production Model	`productionModel`	`boolean`	Indicates if the extractions are performed by the production model. Only use this parameter on custom models. Note that you first need to deploy your model to production.

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Upload Training Data with MonkeyLearn API on New Submission (Instant) from Jotform API

Jotform + MonkeyLearn

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Popular Triggers#

New Submission (Instant) from the Jotform API

Emit new event when a form is submitted

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Popular Actions#

Get Form Submissions with the Jotform API

Gets a list of form responses See the docs here

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Get Monthly User Usage with the Jotform API

Gets number of form submissions received this month. Also, get number of SSL form submissions, payment form submissions and upload space used by user See the docs here

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Get User Submissions with the Jotform API

Gets a list of all submissions for all forms on the account See the docs here

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Classify Text with the MonkeyLearn API

Classifies texts with a given classifier. See the docs here

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Extract Text with the MonkeyLearn API

Extracts information from texts with a given extractor. See the docs here

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