← Jotform + TextCortex integrations

Create Social Media Post with TextCortex API on New Submission (Instant) from Jotform API

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Trigger workflow on
New Submission (Instant) from the Jotform API
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Create Social Media Post with the TextCortex API
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Getting Started

This integration creates a workflow with a Jotform trigger and TextCortex 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 Social Media Post action
    1. Connect your TextCortex account
    2. Configure Context
    3. Optional- Configure Keywords
    4. Optional- Configure Max Tokens
    5. Select a Mode
    6. Optional- Select a Model
    7. Optional- Configure N
    8. Optional- Select a Source Language
    9. Optional- Select a Target Language
    10. Optional- Configure Temperature
  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 social media post. [See the documentation](https://docs.textcortex.com/api/paths/texts-social-media-posts/post)
Version:0.0.1
Key:textcortex-create-social-media-post

TextCortex Overview

The TextCortex API enables automated creation of human-like text, making it a powerful tool for a variety of text generation tasks like drafting emails, creating content, or generating product descriptions. With Pipedream, you can integrate TextCortex into serverless workflows to harness AI writing assistance, trigger content creation based on events, or enhance data with generated text. The API's capability enhances automation and can be combined with other apps for more complex tasks.

Action Code

import app from "../../textcortex.app.mjs";
import constants from "../../common/constants.mjs";

export default {
  key: "textcortex-create-social-media-post",
  name: "Create Social Media Post",
  description: "Create a social media post. [See the documentation](https://docs.textcortex.com/api/paths/texts-social-media-posts/post)",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    context: {
      type: "string",
      label: "Context",
      description: "The context of the social media post.",
    },
    keywords: {
      type: "string[]",
      label: "Keywords",
      description: "Keywords to be included in the post.",
      optional: true,
    },
    maxTokens: {
      propDefinition: [
        app,
        "maxTokens",
      ],
    },
    mode: {
      type: "string",
      label: "Mode",
      description: "The platform, e.g. `twitter` to generate a Tweet. Allowed values: `twitter`, `linkedin`",
      options: Object.values(constants.SOCIAL_MEDIA_MODE),
    },
    model: {
      propDefinition: [
        app,
        "model",
      ],
    },
    n: {
      propDefinition: [
        app,
        "n",
      ],
    },
    sourceLang: {
      propDefinition: [
        app,
        "sourceLang",
      ],
    },
    targetLang: {
      propDefinition: [
        app,
        "targetLang",
      ],
    },
    temperature: {
      propDefinition: [
        app,
        "temperature",
      ],
    },
  },
  methods: {
    createSocialMediaPost(args = {}) {
      return this.app.post({
        path: "/texts/social-media-posts",
        ...args,
      });
    },
  },
  async run({ $: step }) {
    const {
      createSocialMediaPost,
      context,
      keywords,
      maxTokens,
      mode,
      model,
      n,
      sourceLang,
      targetLang,
      temperature,
    } = this;

    const response = await createSocialMediaPost({
      step,
      data: {
        context,
        keywords,
        max_tokens: maxTokens,
        mode,
        model,
        n,
        source_lang: sourceLang,
        target_lang: targetLang,
        temperature,
      },
    });

    step.export("$summary", `Successfully created social media post with status \`${response.status}\``);

    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
TextCortexappappThis component uses the TextCortex app.
Contextcontextstring

The context of the social media post.

Keywordskeywordsstring[]

Keywords to be included in the post.

Max TokensmaxTokensinteger

The maximum number of tokens to generate.

ModemodestringSelect a value from the drop down menu:twitterlinkedin
ModelmodelstringSelect a value from the drop down menu:velox-1aecus-1alta-1sophos-1chat-sophos-1
Nninteger

The number of outputs to generate.

Source LanguagesourceLangstringSelect a value from the drop down menu:{ "label": "English (Default)", "value": "en" }{ "label": "The API will attempt to detect the language of the text and translate it.", "value": "auto" }{ "label": "Bulgarian", "value": "bg" }{ "label": "Czech", "value": "cs" }{ "label": "Danish", "value": "da" }{ "label": "German", "value": "de" }{ "label": "Greek", "value": "el" }{ "label": "Spanish", "value": "es" }{ "label": "Estonian", "value": "et" }{ "label": "Finnish", "value": "fi" }{ "label": "French", "value": "fr" }{ "label": "Hungarian", "value": "hu" }{ "label": "Indonesian", "value": "id" }{ "label": "Italian", "value": "it" }{ "label": "Japanese", "value": "ja" }{ "label": "Korean", "value": "ko" }{ "label": "Lithuanian", "value": "lt" }{ "label": "Latvian", "value": "lv" }{ "label": "Norwegian", "value": "nb" }{ "label": "Dutch", "value": "nl" }{ "label": "Polish", "value": "pl" }{ "label": "Portuguese (all Portuguese varieties mixed)", "value": "pt" }{ "label": "Romanian", "value": "ro" }{ "label": "Russian", "value": "ru" }{ "label": "Slovak", "value": "sk" }{ "label": "Slovenian", "value": "sl" }{ "label": "Swedish", "value": "sv" }{ "label": "Turkish", "value": "tr" }{ "label": "Ukrainian", "value": "uk" }{ "label": "Chinese", "value": "zh" }
Target LanguagetargetLangstringSelect a value from the drop down menu:{ "label": "English (Default)", "value": "en" }{ "label": "The API will attempt to detect the language of the text and translate it.", "value": "auto" }{ "label": "Bulgarian", "value": "bg" }{ "label": "Czech", "value": "cs" }{ "label": "Danish", "value": "da" }{ "label": "German", "value": "de" }{ "label": "Greek", "value": "el" }{ "label": "Spanish", "value": "es" }{ "label": "Estonian", "value": "et" }{ "label": "Finnish", "value": "fi" }{ "label": "French", "value": "fr" }{ "label": "Hungarian", "value": "hu" }{ "label": "Indonesian", "value": "id" }{ "label": "Italian", "value": "it" }{ "label": "Japanese", "value": "ja" }{ "label": "Korean", "value": "ko" }{ "label": "Lithuanian", "value": "lt" }{ "label": "Latvian", "value": "lv" }{ "label": "Norwegian", "value": "nb" }{ "label": "Dutch", "value": "nl" }{ "label": "Polish", "value": "pl" }{ "label": "Portuguese (all Portuguese varieties mixed)", "value": "pt" }{ "label": "Romanian", "value": "ro" }{ "label": "Russian", "value": "ru" }{ "label": "Slovak", "value": "sk" }{ "label": "Slovenian", "value": "sl" }{ "label": "Swedish", "value": "sv" }{ "label": "Turkish", "value": "tr" }{ "label": "Ukrainian", "value": "uk" }{ "label": "Chinese", "value": "zh" }
Temperaturetemperaturestring

The sampling temperature to be used in text generation. The higher the temperature, the higher the risk of the output to sound "made up".

Action Authentication

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

Sign in and copy your API key directly from your dashboard under Settings >> API Key.

About TextCortex

Powerful AI Assistant To 12x Your Productivity 🚀

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