Deepgram
Intelligent, high accuracy speech recognition built for business
Integrate the Deepgram API with the Python API
Setup the Deepgram API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Deepgram and Python remarkably fast. Free for developers.
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Popular Deepgram and Python Actions#
Retrieves details about the specified balance. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Retrieves basic information about the specified project. See the documentation
Retrieves the details of the specified request sent to the Deepgram API for the specified project. See the documentation
Generates a list of outstanding balances for the specified project. See the documentation
Overview of Deepgram#
The Deepgram API offers powerful speech recognition capabilities, enabling you to transcribe, search, and analyze audio data with ease. With its cutting-edge machine learning models, you can uncover insights from voice conversations, automate content moderation, and enhance user experience by converting spoken words into text. Pipedream, as a serverless integration platform, empowers you to craft custom workflows that harness the potential of Deepgram. By connecting to various apps, you can automate complex tasks, analyze audio data on-the-fly, and respond to audio-driven events.
Connect Deepgram#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
deepgram: {
type: "app",
app: "deepgram",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.deepgram.com/v1/projects`,
headers: {
"Authorization": `Token ${this.deepgram.$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}}Community Posts#
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