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SLASHML Python client

This is a Python client for SLASHML. It lets you run transcription jobs from your Python code or Jupyter notebook. Do a transcription job with three lines of code

import speechtotext

speect_to_text = speechtotext.SpeechToText()
transcribe_id= speect_to_text.transcribe(audio_url,service_provider="aws")
status=speect_to_text.status(transcribe_id,service_provider=service_provider)

There is a daily limit (throttling) on the number of calls the user performs, transcription jobs can be done without specifying a token (API key). If the user intends on using the service more frequently, it is recommended to generate an token or API key from the dashboard @ Slashml.com.

Grab your token from [https://www.slashml.com/dashboard] (>settings> new api key) and authenticate by setting it as an environment variable (or when you initialize the service, see examples):

export SLASHML_API_KEY=[token]

or including it in your code as follows:

import speechtotext
API_KEY="your_api_key"
speect_to_text = speechtotext.SpeechToText(API_KEY)
transcribe_id= speect_to_text.transcribe(audio_url,service_provider="aws")
status=speect_to_text.status(transcribe_id,service_provider=service_provider)

-- update from this part, include examples, sign up, token, service providers, type of servies, benchmarking, link to pricing, Tutorial examples/examples

SDK for SlashML documentation:

  • methods: upload_audio, transcribe, status

Steps to Integrate 1 - (Optional) Upload files where the data points to your audio file

# call the class
speect_to_text = speechtotext.SpeechToText()
file_location="path/to/your/file.mp3"
# when
API_KEY="SLASH_ML_API_KEY"
model_choice="assembly"
result_upload = speect_to_text.upload_audio(file_location,API_KEY, model_choice)
print(result_upload)

Save the upload_url. You can use this url link in the rest of the calls.

2- Submit your audio file for transcription

upload_url=upload_url # you can skip step 1 and just input the accessible link of your # file)

result_transcribe = speect_to_text.transcribe(upload_url,API_KEY, model_choice)

print(result_transcribe)

Save the id in the response object.

3 - Check the status and get the text result of the transcription

job_id= id
result_status = speect_to_text.status(job_id,API_KEY, model_choice=model_choice)

### get the full details of the result
print(result_status)
### get the text reulst only
print(json.loads(result)["text"])

et voilà, Next steps:

  • pip install slashml
  • add SLASH_API_KEY to sys path