Create Transcription (Whisper) with OpenAI (ChatGPT) API on New Tweet Posted by User from X (Twitter) API

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New Tweet Posted by User from the X (Twitter) 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 X (Twitter) 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 Tweet Posted by User trigger
1. Connect your X (Twitter) account
2. Configure timer
3. Optional- Configure User Name or ID
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 Tweet Posted by User on X (Twitter)

Description:Emit new event when the specified User posts a Tweet [See the documentation](https://developer.twitter.com/en/docs/twitter-api/tweets/timelines/api-reference/get-users-id-tweets)

Version:2.1.0

Key:twitter-new-tweet-posted-by-user

View on GitHub

X (Twitter) Overview#

The Twitter API on Pipedream enables you to automate interactions with Twitter, from posting tweets to analyzing social media trends. Pipedream's serverless platform provides the tools to create workflows that trigger on specific Twitter activities, process data, and connect with countless other apps for extensive automation scenarios. With Pipedream's integration, you can listen for events such as new tweets, mentions, or followers, and execute actions like tweeting, retweeting, or even leveraging sentiment analysis to gauge public perception.

Trigger Code#

import { defineSource } from "@pipedream/types";
import common from "../common/base.mjs";
import { getTweetSummary as getItemSummary } from "../common/getItemSummary.mjs";
import { getTweetFields } from "../../common/methods.mjs";
import { DOCS_LINK, MAX_RESULTS_PER_PAGE, } from "../../actions/list-user-tweets/list-user-tweets.mjs";
import cacheUserId from "../common/cacheUserId.mjs";
import { getObjIncludes, getTweetIncludeIds, } from "../../common/addObjIncludes.mjs";
export default defineSource({
    ...common,
    key: "twitter-new-tweet-posted-by-user",
    name: "New Tweet Posted by User",
    description: `Emit new event when the specified User posts a Tweet [See the documentation](${DOCS_LINK})`,
    version: "2.1.0",
    type: "source",
    props: {
        ...common.props,
        userNameOrId: {
            propDefinition: [
                common.props.app,
                "userNameOrId",
            ],
        },
    },
    methods: {
        ...common.methods,
        ...cacheUserId,
        getTweetFields,
        getItemSummary,
        getEntityName() {
            return "Tweet";
        },
        async getResources(maxResults) {
            const userId = await this.getCachedUserId();
            const params = {
                $: this,
                maxPerPage: MAX_RESULTS_PER_PAGE,
                maxResults: maxResults ?? MAX_RESULTS_PER_PAGE,
                params: this.getTweetFields(),
                userId,
            };
            const { data, includes, } = await this.app.getUserTweets(params);
            data.forEach((tweet) => tweet.includes = getObjIncludes(tweet, includes, getTweetIncludeIds));
            return data;
        },
    },
});

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
X (Twitter)	`app`	`app`	This component uses the X (Twitter) app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
User Name or ID	`userNameOrId`	`string`	A Twitter username (handle) prefixed with `@` (e.g. `@pipedream`). You can also use the string `me` to use the authenticated user (default), or a numeric User ID.

Trigger Authentication#

X (Twitter) uses OAuth authentication. When you connect your X (Twitter) account, Pipedream will open a popup window where you can sign into X (Twitter) and grant Pipedream permission to connect to your account. Pipedream securely stores and automatically refreshes the OAuth tokens so you can easily authenticate any X (Twitter) API.

Pipedream requests the following authorization scopes when you connect your account:

About X (Twitter)#

Formerly known as Twitter. From breaking news and entertainment to sports and politics, get the full story with all the live commentary. Use a X developer app you've created to send API requests.

Action#

Create Transcription (Whisper) on OpenAI (ChatGPT)

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

Version:0.1.8

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: "0.1.8",
  key: "openai-create-transcription",
  description: "Transcribes audio into the input language. [See docs here](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);

      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" }`

Create Transcription (Whisper) with OpenAI (ChatGPT) API on New Tweet Posted by User from X (Twitter) API

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