Integrate the Rev.ai API with the Python API

Setup the Rev.ai API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Rev.ai and Python remarkably fast. Free for developers.

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Popular Rev.ai and Python Actions#

Get Transcript By Id with the Rev.ai API

Returns the transcript for a completed transcription job. Transcript can be returned as either JSON or plaintext format.

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Submit Transcription Job with the Rev.ai API

Starts an asynchronous job to transcribe speech-to-text for a media file. Add an optional callback URL to invoke when processing is complete.

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Overview of Rev.ai#

Rev.ai offers speech recognition and transcription capabilities, making it possible to convert audio into text with high accuracy. This API provides developers access to advanced speech-to-text functions, allowing you to transcribe interviews, meetings, or any audio content quickly. Using Pipedream, these transcriptions can be integrated into workflows that trigger actions in other apps, enriching your data and automating repetitive tasks.

Connect Rev.ai#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    rev_ai: {
      type: "app",
      app: "rev_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.rev.ai/speechtotext/v1/account`,
      headers: {
        Authorization: `Bearer ${this.rev_ai.$auth.access_token}`,
      },
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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