Trint

Trint’s speech-to-text platform makes audio and video searchable, editable and shareable.

Integrate the Trint API with the Python API

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

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.

 
Try it

Overview of Trint

The Trint API allows you to harness the power of automated transcription and translation. With Trint, you can convert audio and video files into searchable, editable text. It supports multiple languages and provides features like speaker identification and timestamping. Using the Trint API within Pipedream, you can create automated workflows that process media files, extract valuable insights, and integrate transcribed content into databases, content management systems, or other third-party services.

Connect Trint

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    trint: {
      type: "app",
      app: "trint",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.trint.com/transcripts`,
      headers: {
        "Accept": `application/json`,
        "api-key": `${this.trint.$auth.api_key}`,
      },
      params: {
        limit: `{your_limit}`,
        skip: `{your_skip}`,
      },
    })
  },
})

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

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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}}