Generate Image From Text with Tisane Labs API on New Submission (Instant) from Jotform API

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New Submission (Instant) from the Jotform API

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Generate Image From Text with the Tisane Labs API

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Getting Started#

This integration creates a workflow with a Jotform trigger and Tisane Labs 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 Generate Image From Text action
1. Connect your Tisane Labs account
2. Select a Language
3. Configure Content
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#

Generate Image From Text on Tisane Labs

Description:Finds and returns a URL of an image (Creative Commons) best describing the text. [See the documentation](https://docs.tisane.ai/#b61cf454-1e78-42c4-a239-7fa580781729)

Version:0.0.1

Key:tisane_labs-generate-image-from-text

View on GitHub

Tisane Labs Overview#

The Tisane Labs API offers advanced text analysis capabilities, focusing on abusive content detection and linguistic insights. With it, you can automate content moderation, extract entities, detect the sentiment, and identify the language of the text. In Pipedream, Tisane Labs API can be integrated into workflows to process text from various sources such as user comments, support tickets, or social media posts. By leveraging Pipedream's serverless platform, you can create real-time, event-driven applications that respond to text analyses, connect with other services, and perform actions based on the insights gained from the Tisane Labs API.

Action Code#

import tisaneLabs from "../../tisane_labs.app.mjs";

export default {
  key: "tisane_labs-generate-image-from-text",
  name: "Generate Image From Text",
  description: "Finds and returns a URL of an image (Creative Commons) best describing the text. [See the documentation](https://docs.tisane.ai/#b61cf454-1e78-42c4-a239-7fa580781729)",
  version: "0.0.1",
  type: "action",
  props: {
    tisaneLabs,
    language: {
      propDefinition: [
        tisaneLabs,
        "language",
      ],
    },
    content: {
      type: "string",
      label: "Content",
      description: "The content to analyze",
    },
  },
  async run({ $ }) {
    const response = await this.tisaneLabs.generateImageFromText({
      data: {
        language: this.language,
        content: this.content,
      },
      $,
    });

    if (response.length) {
      $.export("$summary", "Successfully generated image from text.");
    }

    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
Tisane Labs	`tisaneLabs`	`app`	This component uses the Tisane Labs app.
Language	`language`	`string`	Select a value from the drop down menu.
Content	`content`	`string`	The content to analyze

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Analyze Text with Tisane Labs API on New Submission (Instant) from Jotform API

Jotform + Tisane Labs

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Translate Text with Tisane Labs API on New Submission (Instant) from Jotform API

Jotform + Tisane Labs

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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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Analyze Text with the Tisane Labs API

Analyze text for language, entities, sentiment, and other insights. See the documentation

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Detect Language with the Tisane Labs API

Detects languages used in the specified text fragment. See the documentation

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