Create Transcription (Whisper) with OpenAI (ChatGPT) API on New Placement Test Result (Instant) from Linguapop API

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New Placement Test Result (Instant) from the Linguapop API

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Create Transcription (Whisper) with the OpenAI (ChatGPT) API

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Getting Started#

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

Select this integration
Configure the New Placement Test Result (Instant) trigger
1. Connect your Linguapop account
Configure the Create Transcription (Whisper) action
1. Connect your OpenAI (ChatGPT) account
2. Select a Audio Upload Type
3. Optional- Select a Language
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 Placement Test Result (Instant) on Linguapop

Description:Emit new event when a placement test is completed. Must setup the source's URL as the `callbackUrl` when sending the test invitation. [See the documentation](https://docs.linguapop.eu/api/#sendcreate-an-invitation-to-a-placement-test)

Version:0.0.1

Key:linguapop-new-placement-test-result-instant

View on GitHub

Linguapop Overview#

The Linguapop API offers functionalities for language learning applications, focusing on vocabulary, grammar, and language exercises. Through integrating this API with Pipedream, you can automate language learning processes, personalize educational content delivery, and streamline language proficiency assessments. Pipedream’s ability to connect with numerous other APIs and services enables the development of customized, efficient workflows that enhance the learning experience.

Trigger Code#

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

export default {
  key: "linguapop-new-placement-test-result-instant",
  name: "New Placement Test Result (Instant)",
  description: "Emit new event when a placement test is completed. Must setup the source's URL as the `callbackUrl` when sending the test invitation. [See the documentation](https://docs.linguapop.eu/api/#sendcreate-an-invitation-to-a-placement-test)",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  props: {
    linguapop,
    http: "$.interface.http",
  },
  methods: {
    generateMeta(result) {
      return {
        id: result.invitationId,
        summary: `Test completed by ${result.email}`,
        ts: Date.parse(result.completedOn),
      };
    },
  },
  async run(event) {
    const { body } = event;
    const meta = this.generateMeta(body);
    this.$emit(body, meta);
  },
  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
Linguapop	`linguapop`	`app`	This component uses the Linguapop 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.

Trigger Authentication#

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

About Linguapop#

Linguapop gives you the ability to quickly send branded, CEFR-aligned language skill tests to your candidates anywhere, anytime.

Action#

Create Transcription (Whisper) on OpenAI (ChatGPT)

Description:Transcribes audio into the input language. [See the documentation](https://platform.openai.com/docs/api-reference/audio/create).

Version:0.1.14

Key:openai-create-transcription

View on GitHub

OpenAI (ChatGPT) Overview#

OpenAI provides a suite of powerful AI models through its API, enabling developers to integrate advanced natural language processing and generative capabilities into their applications. Here’s an overview of the services offered by OpenAI's API:

Use Python or Node.js code to make fully authenticated API requests with your OpenAI account:

Action Code#

import ffmpegInstaller from "@ffmpeg-installer/ffmpeg";
import { ConfigurationError } from "@pipedream/platform";
import axios from "axios";
import Bottleneck from "bottleneck";
import { exec } from "child_process";
import FormData from "form-data";
import fs from "fs";
import {
  extname,
  join,
} from "path";
import stream from "stream";
import { promisify } from "util";
import openai from "../../openai.app.mjs";
import common from "../common/common.mjs";
import constants from "../../common/constants.mjs";
import lang from "../common/lang.mjs";

const COMMON_AUDIO_FORMATS_TEXT = "Your audio file must be in one of these formats: mp3, mp4, mpeg, mpga, m4a, wav, or webm.";
const CHUNK_SIZE_MB = 20;

const execAsync = promisify(exec);
const pipelineAsync = promisify(stream.pipeline);

export default {
  name: "Create Transcription (Whisper)",
  version: "0.1.14",
  key: "openai-create-transcription",
  description: "Transcribes audio into the input language. [See the documentation](https://platform.openai.com/docs/api-reference/audio/create).",
  type: "action",
  props: {
    openai,
    uploadType: {
      label: "Audio Upload Type",
      description: "Are you uploading an audio file from [your workflow's `/tmp` directory](https://pipedream.com/docs/code/nodejs/working-with-files/#the-tmp-directory), or providing a URL to the file?",
      type: "string",
      options: [
        "File",
        "URL",
      ],
      reloadProps: true,
    },
    language: {
      label: "Language",
      description: "**Optional**. The language of the input audio. Supplying the input language will improve accuracy and latency.",
      type: "string",
      optional: true,
      options: lang.LANGUAGES.map((l) => ({
        label: l.label,
        value: l.value,
      })),
    },
  },
  async additionalProps() {
    const props = {};
    switch (this.uploadType) {
    case "File":
      props.path = {
        type: "string",
        label: "File Path",
        description: `A path to your audio file to transcribe, e.g. \`/tmp/audio.mp3\`. ${COMMON_AUDIO_FORMATS_TEXT} Add the appropriate extension (mp3, mp4, etc.) on your filename — OpenAI uses the extension to determine the file type. [See the Pipedream docs on saving files to \`/tmp\`](https://pipedream.com/docs/code/nodejs/working-with-files/#writing-a-file-to-tmp)`,
      };
      break;
    case "URL":
      props.url = {
        type: "string",
        label: "URL",
        description: `A public URL to the audio file to transcribe. This URL must point directly to the audio file, not a webpage that links to the audio file. ${COMMON_AUDIO_FORMATS_TEXT}`,
      };
      break;
    default:
      throw new ConfigurationError("Invalid upload type specified. Please provide 'File' or 'URL'.");
    }
    // Because we need to display the file or URL above, and not below, these optional props
    // TODO: Will be fixed when we render optional props correctly when used with additionalProps
    props.prompt = {
      label: "Prompt",
      description: "**Optional** text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text/prompting) should match the audio language.",
      type: "string",
      optional: true,
    };
    props.responseFormat = {
      label: "Response Format",
      description: "**Optional**. The format of the response. The default is `json`.",
      type: "string",
      default: "json",
      optional: true,
      options: constants.TRANSCRIPTION_FORMATS,
    };
    props.temperature = common.props.temperature;

    return props;
  },
  methods: {
    createForm({
      file, outputDir,
    }) {
      const form = new FormData();
      form.append("model", "whisper-1");
      if (this.prompt) form.append("prompt", this.prompt);
      if (this.temperature) form.append("temperature", this.temperature);
      if (this.language) form.append("language", this.language);
      if (this.responseFormat) form.append("response_format", this.responseFormat);
      const readStream = fs.createReadStream(join(outputDir, file));
      form.append("file", readStream);
      return form;
    },
    async splitLargeChunks(files, outputDir) {
      for (const file of files) {
        if (fs.statSync(`${outputDir}/${file}`).size / (1024 * 1024) > CHUNK_SIZE_MB) {
          await this.chunkFile({
            file: `${outputDir}/${file}`,
            outputDir,
            index: file.slice(6, 9),
          });
          await execAsync(`rm -f "${outputDir}/${file}"`);
        }
      }
    },
    async chunkFileAndTranscribe({
      file, $,
    }) {
      const outputDir = join("/tmp", "chunks");
      await execAsync(`mkdir -p "${outputDir}"`);
      await execAsync(`rm -f "${outputDir}/*"`);

      await this.chunkFile({
        file,
        outputDir,
      });

      let files = await fs.promises.readdir(outputDir);
      // ffmpeg will sometimes return chunks larger than the allowed size,
      // so we need to identify large chunks and break them down further
      await this.splitLargeChunks(files, outputDir);
      files = await fs.promises.readdir(outputDir);

      return this.transcribeFiles({
        files,
        outputDir,
        $,
      });
    },
    async chunkFile({
      file, outputDir, index,
    }) {
      const ffmpegPath = ffmpegInstaller.path;
      const ext = extname(file);

      const fileSizeInMB = fs.statSync(file).size / (1024 * 1024);
      // We're limited to 26MB per request. Because of how ffmpeg splits files,
      // we need to be conservative in the number of chunks we create
      const conservativeChunkSizeMB = CHUNK_SIZE_MB;
      const numberOfChunks = !index
        ? Math.ceil(fileSizeInMB / conservativeChunkSizeMB)
        : 2;

      if (numberOfChunks === 1) {
        await execAsync(`cp "${file}" "${outputDir}/chunk-000${ext}"`);
        return;
      }

      const { stdout } = await execAsync(`${ffmpegPath} -i "${file}" 2>&1 | grep "Duration"`);
      const duration = stdout.match(/\d{2}:\d{2}:\d{2}\.\d{2}/s)[0];
      const [
        hours,
        minutes,
        seconds,
      ] = duration.split(":").map(parseFloat);

      const totalSeconds = (hours * 60 * 60) + (minutes * 60) + seconds;
      const segmentTime = Math.ceil(totalSeconds / numberOfChunks);

      const command = `${ffmpegPath} -i "${file}" -f segment -segment_time ${segmentTime} -c copy "${outputDir}/chunk-${index
        ? `${index}-`
        : ""}%03d${ext}"`;
      await execAsync(command);
    },
    transcribeFiles({
      files, outputDir, $,
    }) {
      const limiter = new Bottleneck({
        maxConcurrent: 1,
        minTime: 1000 / 59,
      });

      return Promise.all(files.map((file) => {
        return limiter.schedule(() => this.transcribe({
          file,
          outputDir,
          $,
        }));
      }));
    },
    transcribe({
      file, outputDir, $,
    }) {
      const form = this.createForm({
        file,
        outputDir,
      });
      return this.openai.createTranscription({
        $,
        form,
      });
    },
    getFullText(transcriptions = []) {
      return transcriptions.map((t) => t.text || t).join(" ");
    },
  },
  async run({ $ }) {
    const {
      url,
      path,
    } = this;

    if (!url && !path) {
      throw new ConfigurationError("Must specify either File URL or File Path");
    }

    let file;

    if (path) {
      if (!fs.existsSync(path)) {
        throw new ConfigurationError(`${path} does not exist`);
      }

      file = path;
    } else if (url) {
      const ext = extname(url).split("?")[0];

      const response = await axios({
        method: "GET",
        url,
        responseType: "stream",
        timeout: 250000,
      });

      const bufferStream = new stream.PassThrough();
      response.data.pipe(bufferStream);

      const downloadPath = join("/tmp", `audio${ext}`);
      const writeStream = fs.createWriteStream(downloadPath);

      await pipelineAsync(bufferStream, writeStream);

      file = downloadPath;
    }

    const transcriptions = await this.chunkFileAndTranscribe({
      file,
      $,
    });

    if (transcriptions.length) {
      $.export("$summary", "Successfully created transcription");
    }

    return {
      transcription: this.getFullText(transcriptions),
      transcriptions,
    };
  },
};

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
OpenAI (ChatGPT)	`openai`	`app`	This component uses the OpenAI (ChatGPT) app.
Audio Upload Type	`uploadType`	`string`	Select a value from the drop down menu:`FileURL`
Language	`language`	`string`	Select a value from the drop down menu:`{ "label": "Afar", "value": "aa" }{ "label": "Abkhaz", "value": "ab" }{ "label": "Avestan", "value": "ae" }{ "label": "Afrikaans", "value": "af" }{ "label": "Akan", "value": "ak" }{ "label": "Amharic", "value": "am" }{ "label": "Aragonese", "value": "an" }{ "label": "Arabic", "value": "ar" }{ "label": "Arabic (Algeria)", "value": "ar-dz" }{ "label": "Arabic (Bahrain)", "value": "ar-bh" }{ "label": "Arabic (Egypt)", "value": "ar-eg" }{ "label": "Arabic (Iraq)", "value": "ar-iq" }{ "label": "Arabic (Jordan)", "value": "ar-jo" }{ "label": "Arabic (Kuwait)", "value": "ar-kw" }{ "label": "Arabic (Lebanon)", "value": "ar-lb" }{ "label": "Arabic (Libya)", "value": "ar-ly" }{ "label": "Arabic (Morocco)", "value": "ar-ma" }{ "label": "Arabic (Oman)", "value": "ar-om" }{ "label": "Arabic (Qatar)", "value": "ar-qa" }{ "label": "Arabic (Saudi Arabia)", "value": "ar-sa" }{ "label": "Arabic (Syria)", "value": "ar-sy" }{ "label": "Arabic (Tunisia)", "value": "ar-tn" }{ "label": "Arabic (U.A.E.)", "value": "ar-ae" }{ "label": "Arabic (Yemen)", "value": "ar-ye" }{ "label": "Assamese", "value": "as" }{ "label": "Avaric", "value": "av" }{ "label": "Aymara", "value": "ay" }{ "label": "Azerbaijani", "value": "az" }{ "label": "Bashkir", "value": "ba" }{ "label": "Belarusian", "value": "be" }{ "label": "Bulgarian", "value": "bg" }{ "label": "Bislama", "value": "bi" }{ "label": "Bambara", "value": "bm" }{ "label": "Bengali", "value": "bn" }{ "label": "Tibetan", "value": "bo" }{ "label": "Breton", "value": "br" }{ "label": "Bosnian", "value": "bs" }{ "label": "Catalan", "value": "ca" }{ "label": "Chechen", "value": "ce" }{ "label": "Chamorro", "value": "ch" }{ "label": "Corsican", "value": "co" }{ "label": "Cree", "value": "cr" }{ "label": "Czech", "value": "cs" }{ "label": "Old Church Slavonic", "value": "cu" }{ "label": "Chuvash", "value": "cv" }{ "label": "Welsh", "value": "cy" }{ "label": "Danish", "value": "da" }{ "label": "German", "value": "de" }{ "label": "Divehi", "value": "dv" }{ "label": "Dzongkha", "value": "dz" }{ "label": "Ewe", "value": "ee" }{ "label": "Greek", "value": "el" }{ "label": "English", "value": "en" }{ "label": "Esperanto", "value": "eo" }{ "label": "Spanish", "value": "es" }{ "label": "Estonian", "value": "et" }{ "label": "Basque", "value": "eu" }{ "label": "Persian", "value": "fa" }{ "label": "Fula", "value": "ff" }{ "label": "Finnish", "value": "fi" }{ "label": "Fijian", "value": "fj" }{ "label": "Faroese", "value": "fo" }{ "label": "French", "value": "fr" }{ "label": "Western Frisian", "value": "fy" }{ "label": "Irish", "value": "ga" }{ "label": "Scottish Gaelic", "value": "gd" }{ "label": "Galician", "value": "gl" }{ "label": "Guaraní", "value": "gn" }{ "label": "Gujarati", "value": "gu" }{ "label": "Manx", "value": "gv" }{ "label": "Hausa", "value": "ha" }{ "label": "Hebrew", "value": "he" }{ "label": "Hindi", "value": "hi" }{ "label": "Hiri Motu", "value": "ho" }{ "label": "Croatian", "value": "hr" }{ "label": "Haitian", "value": "ht" }{ "label": "Hungarian", "value": "hu" }{ "label": "Armenian", "value": "hy" }{ "label": "Herero", "value": "hz" }{ "label": "Interlingua", "value": "ia" }{ "label": "Indonesian", "value": "id" }{ "label": "Interlingue", "value": "ie" }{ "label": "Igbo", "value": "ig" }{ "label": "Nuosu", "value": "ii" }{ "label": "Inupiaq", "value": "ik" }{ "label": "Ido", "value": "io" }{ "label": "Icelandic", "value": "is" }{ "label": "Italian", "value": "it" }{ "label": "Inuktitut", "value": "iu" }{ "label": "Japanese", "value": "ja" }{ "label": "Javanese", "value": "jv" }{ "label": "Georgian", "value": "ka" }{ "label": "Kongo", "value": "kg" }{ "label": "Kikuyu", "value": "ki" }{ "label": "Kwanyama", "value": "kj" }{ "label": "Kazakh", "value": "kk" }{ "label": "Kalaallisut", "value": "kl" }{ "label": "Khmer", "value": "km" }{ "label": "Kannada", "value": "kn" }{ "label": "Korean", "value": "ko" }{ "label": "Kanuri", "value": "kr" }{ "label": "Kashmiri", "value": "ks" }{ "label": "Kurdish", "value": "ku" }{ "label": "Komi", "value": "kv" }{ "label": "Cornish", "value": "kw" }{ "label": "Kyrgyz", "value": "ky" }{ "label": "Latin", "value": "la" }{ "label": "Luxembourgish", "value": "lb" }{ "label": "Ganda", "value": "lg" }{ "label": "Limburgish", "value": "li" }{ "label": "Lingala", "value": "ln" }{ "label": "Lao", "value": "lo" }{ "label": "Lithuanian", "value": "lt" }{ "label": "Luba-Katanga", "value": "lu" }{ "label": "Latvian", "value": "lv" }{ "label": "Malagasy", "value": "mg" }{ "label": "Marshallese", "value": "mh" }{ "label": "Māori", "value": "mi" }{ "label": "Macedonian", "value": "mk" }{ "label": "Malayalam", "value": "ml" }{ "label": "Mongolian", "value": "mn" }{ "label": "Marathi", "value": "mr" }{ "label": "Malay", "value": "ms" }{ "label": "Maltese", "value": "mt" }{ "label": "Burmese", "value": "my" }{ "label": "Nauru", "value": "na" }{ "label": "Norwegian Bokmål", "value": "nb" }{ "label": "Northern Ndebele", "value": "nd" }{ "label": "Nepali", "value": "ne" }{ "label": "Ndonga", "value": "ng" }{ "label": "Dutch", "value": "nl" }{ "label": "Norwegian Nynorsk", "value": "nn" }{ "label": "Norwegian", "value": "no" }{ "label": "Southern Ndebele", "value": "nr" }{ "label": "Navajo", "value": "nv" }{ "label": "Chichewa", "value": "ny" }{ "label": "Occitan", "value": "oc" }{ "label": "Ojibwe", "value": "oj" }{ "label": "Oromo", "value": "om" }{ "label": "Oriya", "value": "or" }{ "label": "Ossetian", "value": "os" }{ "label": "Panjabi", "value": "pa" }{ "label": "Pāli", "value": "pi" }{ "label": "Polish", "value": "pl" }{ "label": "Pashto", "value": "ps" }{ "label": "Portuguese", "value": "pt" }{ "label": "Quechua", "value": "qu" }{ "label": "Romansh", "value": "rm" }{ "label": "Kirundi", "value": "rn" }{ "label": "Romanian", "value": "ro" }{ "label": "Russian", "value": "ru" }{ "label": "Kinyarwanda", "value": "rw" }{ "label": "Sanskrit", "value": "sa" }{ "label": "Sardinian", "value": "sc" }{ "label": "Sindhi", "value": "sd" }{ "label": "Northern Sami", "value": "se" }{ "label": "Sango", "value": "sg" }{ "label": "Sinhala", "value": "si" }{ "label": "Slovak", "value": "sk" }{ "label": "Slovenian", "value": "sl" }{ "label": "Samoan", "value": "sm" }{ "label": "Shona", "value": "sn" }{ "label": "Somali", "value": "so" }{ "label": "Albanian", "value": "sq" }{ "label": "Serbian", "value": "sr" }{ "label": "Swati", "value": "ss" }{ "label": "Southern Sotho", "value": "st" }{ "label": "Sundanese", "value": "su" }{ "label": "Swedish", "value": "sv" }{ "label": "Swahili", "value": "sw" }{ "label": "Tamil", "value": "ta" }{ "label": "Telugu", "value": "te" }{ "label": "Tajik", "value": "tg" }{ "label": "Thai", "value": "th" }{ "label": "Tigrinya", "value": "ti" }{ "label": "Turkmen", "value": "tk" }{ "label": "Tagalog", "value": "tl" }{ "label": "Tswana", "value": "tn" }{ "label": "Tonga", "value": "to" }{ "label": "Turkish", "value": "tr" }{ "label": "Tsonga", "value": "ts" }{ "label": "Tatar", "value": "tt" }{ "label": "Twi", "value": "tw" }{ "label": "Tahitian", "value": "ty" }{ "label": "Uyghur", "value": "ug" }{ "label": "Ukrainian", "value": "uk" }{ "label": "Urdu", "value": "ur" }{ "label": "Uzbek", "value": "uz" }{ "label": "Venda", "value": "ve" }{ "label": "Vietnamese", "value": "vi" }{ "label": "Volapük", "value": "vo" }{ "label": "Walloon", "value": "wa" }{ "label": "Wolof", "value": "wo" }{ "label": "Xhosa", "value": "xh" }{ "label": "Yiddish", "value": "yi" }{ "label": "Yoruba", "value": "yo" }{ "label": "Zhuang", "value": "za" }{ "label": "Chinese", "value": "zh" }{ "label": "Zulu", "value": "zu" }`

Action Authentication#

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

About OpenAI (ChatGPT)#

OpenAI is an AI research and deployment company with the mission to ensure that artificial general intelligence benefits all of humanity. They are the makers of popular models like ChatGPT, DALL-E, and Whisper.

More Ways to Connect OpenAI (ChatGPT) + Linguapop#

Other Popular Integrations#

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Create Transcription (Whisper) with OpenAI (ChatGPT) API on New Placement Test Result (Instant) from Linguapop API

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