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    revai-node-sdk
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    3.5.1 • Public • Published

    Rev AI Node SDK · npm version CI

    Documentation

    See the API docs for more information about the API.

    Examples

    Examples can be found in the examples/ directory

    Installation

    To install the package, run:

    npm install revai-node-sdk
    

    Support

    We support Node 8, 10, 12, 14, 16 and 17.

    Usage

    All you need to get started is your Access Token, which can be generated on your Settings Page. Create a client with the given Access Token:

    import { RevAiApiClient } from 'revai-node-sdk';
    
    // Initialize your client with your Rev AI access token
    const accessToken = "Your Access Token";
    const client = new RevAiApiClient(accessToken);

    Checking credits remaining

    const accountInfo = await client.getAccount();

    Submitting a job

    Once you've set up your client with your Access Token sending a file is easy!

    // You can submit a local file
    const job = await client.submitJobLocalFile("./path/to/file.mp4");
    
    // or submit via a public url
    const jobOptions = { source_config: { url: "https://www.rev.ai/FTC_Sample_1.mp3" } }
    const job = await client.submitJob(jobOptions);
    
    // or from audio data, the filename is optional
    const stream = fs.createReadStream("./path/to/file.mp3");
    const job = await client.submitJobAudioData(stream, "file.mp3");

    You can also submit a job to be handled by a human transcriber using our Human Transcription option.

    const job = await client.submitJobLocalFile("./path/to/file.mp4", {
        transcriber: "human",
        verbatim: false,
        rush: false,
        test_mode: true,
        segments_to_transcribe: [{
            start: 1.0,
            end: 2.4
        }]
    });

    job will contain all the information normally found in a successful response from our Submit Job endpoint.

    If you want to get fancy, both send job methods can take a RevAiJobOptions object containing optional parameters. These are described in the request body of the Submit Job endpoint.

    Submitting urls with authorization headers

    Both the source_config and notification_config job options support using a customer-provided authorization header to access the URLs. This optional argument should be in the format { "Authorization": "TokenScheme TokenValue" }

    Example:

    var notificationConfig = { url: 'https://example.com', auth_headers: { "Authorization": "Bearer <token>" } };
    

    For more information see https://github.com/revdotcom/revai-node-sdk/blob/develop/examples/async_transcribe_media_from_url.js

    Checking your job's status

    You can check the status of your transcription job using its id

    const jobDetails = await client.getJobDetails(job.id);

    jobDetails will contain all information normally found in a successful response from our Get Job endpoint

    Checking multiple files

    You can retrieve a list of transcription jobs with optional parameters

    const jobs = await client.getListOfJobs();
    
    // limit amount of retrieved jobs
    const jobs = await client.getListOfJobs(3);
    
    // get jobs starting after a certain job id
    const jobs = await client.getListOfJobs(undefined, 'Umx5c6F7pH7r');

    jobs will contain a list of job details having all information normally found in a successful response from our Get List of Jobs endpoint

    Deleting a job

    You can delete a transcription job using its id

    await client.deleteJob(job.id);

    All data related to the job, such as input media and transcript, will be permanently deleted. A job can only by deleted once it's completed (either with success or failure).

    Getting your transcript

    Once your file is transcribed, you can get your transcript in a few different forms:

    // as plain text
    const transcriptText = await client.getTranscriptText(job.id);
    
    // or as an object
    const transcriptObject = await client.getTranscriptObject(job.id);

    The text output is a string containing just the text of your transcript. The object form of the transcript contains all the information outlined in the response of the Get Transcript endpoint when using the json response schema.

    Any of these outputs can we retrieved as a stream for easy file writing:

    const textStream = await client.getTranscriptTextStream(job.id);
    const transcriptStream = await client.getTranscriptObjectStream(job.id);

    Getting captions output

    Another way to retrieve your file is captions output. We support both .srt and .vtt outputs. See below for an example showing how you can get captions as a readable stream. If your job was submitted with multiple speaker channels you are required to provide the id of the channel you would like captioned.

    const captionsStream = await client.getCaptions(job.id, CaptionType.SRT);
    
    // with speaker channels
    const channelId = 1;
    const captionsStream = await client.getCaptions(job.id, CaptionType.VTT, channelId);

    Streaming Audio

    In order to stream audio, you will need to setup a streaming client and a media configuration for the audio you will be sending.

    import { RevAiStreamingClient } from 'revai-node-sdk';
    
    const audioConfig = new AudioConfig() // Initialize audio configuration for the streaming client
    const streamingClient = new RevAiStreamingClient("ACCESS TOKEN", audioConfig);

    You can set up event responses for your client's streaming sessions. This allows you to handle events such as the connection closing, failing, or successfully connecting! Look at the examples for more details.

    streamingClient.on('close', (code, reason) => {
        console.log(`Connection closed, ${code}: ${reason}`);
    });
    
    streamingClient.on('connect', connectionMessage => {
        console.log(`Connected with job id: ${connectionMessage.id}`);
    })

    Now you will be able to start the streaming session by simply calling the streamingClient.start() method! You can supply an optional SessionConfig object to the function as well in order to provide additional information for that session, such as metadata, or a custom vocabulary's ID to be used with your streaming session.

    const sessionConfig = new SessionConfig(metadata='my metadata', customVocabularyID='myCustomVocabularyID');
    
    const stream = streamingClient.start(sessionConfig);

    You can then stream data to this stream from a local file or other sources of your choosing and the session will end when the data stream to the stream session ends or when you would like to end it, by calling streamingClient.end(). For more details, take a look at our examples.

    Submitting custom vocabularies

    You can now submit any custom vocabularies independently through the new CustomVocabularies client! The main benefit is that users of the SDK can now submit their custom vocabularies for preprocessing and then include these processed custom vocabularies in their streaming jobs.

    Below you can see an example of how to create, submit and check on the status and other associated information of your submitted custom vocabulary!

    For more information, check out our examples.

    import { RevAiCustomVocabulariesClient } from 'revai-node-sdk';
    
    // Initialize your client with your Rev AI access token
    const accessToken = "Your Access Token";
    const client = new RevAiCustomVocabulariesClient(accessToken);
    
    // Construct custom vocabularies object and submit it through the client
    const customVocabularies = [{phrases: ["Noam Chomsky", "Robert Berwick", "Patrick Winston"]}];
    const customVocabularySubmission = await client.submitCustomVocabularies(customVocabularies);
    
    // Get information regarding the custom vocabulary submission and its progress
    const customVocabularyInformation = await client.getCustomVocabularyInformation(customVocabularySubmission.id)
    
    // Get a list of information on previously submitted custom vocabularies
    const customVocabularyInformations = await client.getListOfCustomVocabularyInformations()
    
    // Delete a custom vocabulary
    await client.deleteCustomVocabulary(customVocabularySubmission.id)

    For Rev AI Node SDK Developers

    After cloning and installing required npm modules, you should follow these practices when developing:

    1. Use the scripts defined in package.json in this manner npm run [command_name]:
      1. lint checks that you are not violating any code style standards. This ensures our code's style quality stays high improving readability and reducing room for errors.
      2. build transpiles the Typescript into Javascript with the options specified in tsconfig.json
      3. unit-test runs our unit tests which live in the unit test directory.
      • Note that integration-test is currently configured to work with a certain account specified in our continuous integration build environment, as such for now you can check the automated continuous integration checks to pass the integration tests.
      1. build-examples performs the same action as build and in addition, copies the src to the node_modules directory in examples such that you can test examples with local changes.
    2. Add any relevant test logic if you add or modify any features in the source code and check that the tests pass using the scripts mentioned above.
    3. Update the examples provided to illustrate any relevant changes you made, and check that they work properly with your changed local revai-node-sdk.
      • One way to use your changed local package in the examples is to copy the output of the build script into the examples/node_modules/revai-node-sdk. On Unix, this can be simply done with the following command when in the root directory: $ cp -r dist/src examples/node_modules/revai-node-sdk/.
    4. Update the documentation to reflect any relevant changes and improve the development section.

    Install

    npm i revai-node-sdk

    DownloadsWeekly Downloads

    3,162

    Version

    3.5.1

    License

    MIT

    Unpacked Size

    137 kB

    Total Files

    122

    Last publish

    Collaborators

    • revkyle
    • revai-eng