# Code Samples Use the code samples below to quickly get started developing with the SDK. These examples require the [Rev AI Python SDK](/sdk/python). ## Submit a local file for transcription The following example demonstrates how to submit a local audio file for transcription. To use this example, replace the `` placeholder with the path to the file you wish to transcribe and the `` placeholder with your Rev AI account's access token. ```python from rev_ai import apiclient token = "" filePath = "" # create your client client = apiclient.RevAiAPIClient(token) # send a local file job = client.submit_job_local_file(filePath) # check job status job_details = client.get_job_details(job.id) # retrieve transcript as text transcript_text = client.get_transcript_text(job.id) # retrieve transcript as JSON transcript_json = client.get_transcript_json(job.id) # retrieve transcript as a Python object transcript_object = client.get_transcript_object(job.id) ``` ## Submit a remote file for transcription The following example demonstrates how to submit a remote audio file for transcription. To use this example, replace the `` placeholder with the public URL to the file you wish to transcribe and the `` placeholder with your Rev AI account's access token. ```python from rev_ai import apiclient token = "" source_url = "" # create your client client = apiclient.RevAiAPIClient(token) # submit a job with a link to the source file job = client.submit_job_url(source_config=CustomerUrlData(url=source_url)) # check job status job_details = client.get_job_details(job.id) # retrieve transcript as text transcript_text = client.get_transcript_text(job.id) # retrieve transcript as json transcript_json = client.get_transcript_json(job.id) # retrieve transcript as a python object transcript_object = client.get_transcript_object(job.id) ``` ## Stream and transcribe an audio file The following example can be used to configure your streaming client, send a stream of audio as a generator, and obtain the transcript as the audio is processed. To use this example, replace the `` placeholder with the path to the file you wish to transcribe and replace the `` placeholder with your Rev AI access token. ```python from rev_ai.models import MediaConfig from rev_ai.streamingclient import RevAiStreamingClient import io """ Name of file to be transcribed """ filename = "" """ String of your access token """ access_token = "" """ Media configuration of audio file. This includes the content type, layout, rate, format, and # of channels """ config = MediaConfig("audio/x-raw", "interleaved", 16000, "S16LE", 1) """ Create client with your access token and media configuration """ streamclient = RevAiStreamingClient(access_token, config) """ Open file and read data into array. Practically, stream data would be divided into chunks """ with io.open(filename, 'rb') as stream: MEDIA_GENERATOR = [stream.read()] """ Starts the streaming connection and creates a thread to send bytes from the MEDIA_GENERATOR. response_generator is a generator yielding responses from the server """ response_generator = streamclient.start(MEDIA_GENERATOR) """ Iterates through the responses from the server when obtained """ for response in response_generator: print(response) """ Ends the connection early. Not needed as the server will close the connection upon receiving an "EOS" message. """ streamclient.end() ``` ## Stream and transcribe microphone audio The following example can be used to configure your streaming client, send audio as a stream from your microphone input, and obtain the transcript as it is processed. To use this example, replace the `` placeholder with your Rev AI access token. ```python import pyaudio from rev_ai.models import MediaConfig from rev_ai.streamingclient import RevAiStreamingClient from six.moves import queue """ Insert your access token here """ access_token = "" class MicrophoneStream(object): """ Opens a recording stream as a generator yielding the audio chunks. """ def __init__(self, rate, chunk): self._rate = rate self._chunk = chunk """ Create a thread-safe buffer of audio data """ self._buff = queue.Queue() self.closed = True def __enter__(self): self._audio_interface = pyaudio.PyAudio() self._audio_stream = self._audio_interface.open( format=pyaudio.paInt16, """ The API currently only supports 1-channel (mono) audio """ channels=1, rate=self._rate, input=True, frames_per_buffer=self._chunk, """ Run the audio stream asynchronously to fill the buffer object. This is necessary so that the input device's buffer doesn't overflow while the calling thread makes network requests, etc. """ stream_callback=self._fill_buffer, ) self.closed = False return self def __exit__(self, type, value, traceback): self._audio_stream.stop_stream() self._audio_stream.close() self.closed = True """ Signal the generator to terminate so that the client's streaming_recognize method will not block the process termination. """ self._buff.put(None) self._audio_interface.terminate() def _fill_buffer(self, in_data, frame_count, time_info, status_flags): """ Continuously collect data from the audio stream, into the buffer. """ self._buff.put(in_data) return None, pyaudio.paContinue def generator(self): while not self.closed: """ Use a blocking get() to ensure there's at least one chunk of data, and stop iteration if the chunk is None, indicating the end of the audio stream. """ chunk = self._buff.get() if chunk is None: return data = [chunk] """ Now consume whatever other data's still buffered. """ while True: try: chunk = self._buff.get(block=False) if chunk is None: return data.append(chunk) except queue.Empty: break yield b''.join(data) """ Sampling rate of your microphone and desired chunk size """ rate = 44100 chunk = int(rate/10) """ Creates a media config with the settings set for a raw microphone input """ example_mc = MediaConfig('audio/x-raw', 'interleaved', 44100, 'S16LE', 1) streamclient = RevAiStreamingClient(access_token, example_mc) """ Opens microphone input. The input will stop after a keyboard interrupt. """ with MicrophoneStream(rate, chunk) as stream: """ Uses try method to enable users to manually close the stream """ try: """ Starts the server connection and thread sending microphone audio """ response_gen = streamclient.start(stream.generator()) """ Iterates through responses and prints them """ for response in response_gen: print(response) except KeyboardInterrupt: """ Ends the WebSocket connection. """ streamclient.end() pass ``` ## Create and use a custom vocabulary The following example can be used to create and submit custom vocabularies independently and directly to the custom vocabularies API, as well as check on their progress. To use this example, replace the `` placeholder with your Rev AI access token. ```python from rev_ai import custom_vocabularies_client from rev_ai.models import CustomVocabulary token = "" # create a client client = custom_vocabularies_client.RevAiCustomVocabulariesClient(token) # construct a CustomVocabulary object using your desired phrases custom_vocabulary = CustomVocabulary(["Patrick Henry Winston", "Robert C Berwick", "Noam Chomsky"]) # submit the CustomVocabulary custom_vocabularies_job = client.submit_custom_vocabularies([custom_vocabulary]) # view the job's progress job_state = client.get_custom_vocabularies_information(custom_vocabularies_job['id']) # get list of previously submitted custom vocabularies custom_vocabularies_jobs = client.get_list_of_custom_vocabularies() # delete the CustomVocabulary client.delete_custom_vocabulary(custom_vocabularies_job['id']) ``` Find [more examples on GitHub](https://github.com/revdotcom/revai-python-sdk/tree/master/examples).