Integrate the Temi API with the Python API

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

Popular Ways to Connect Temi with Python#

Run Python Code with Python API on New Transcript from Temi API

Temi + Python

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Popular Temi and Python Triggers#

New Transcript from the Temi API

Emit new event when a new transcript is created.

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Popular Temi and Python Actions#

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 Temi API

Submits a job passing a media URL. See the docs.

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Overview of Temi#

Temi API offers automated transcription services, converting audio and video files into text. With Pipedream's robust platform, you can exploit Temi's capabilities to activate a myriad of automated workflows, from transcribing meeting recordings for easy reference to triggering tasks based on the presence of keywords in transcribed text. The real power lies in connecting these transcriptions to other services for further analysis, archiving, or even real-time alerting.

Connect Temi#

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

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}}