Research lab exploring new frontiers of Voice AI. Deploying tools for prime long-form synthetic speech, voice cloning and automatic dubbing.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Download one or more history items to your workflow's tmp
directory. If one history item ID is provided, we will return a single audio file. If more than one history item IDs are provided, we will provide the history items packed into a .zip file. See the documentation
Returns the audio of an history item and converts it to a file. See the documentation
The ElevenLabs API offers text-to-speech capabilities with realistic voice synthesis. Integrating this API on Pipedream allows you to build automated workflows that convert text content into spoken audio files. You can trigger these conversions from various events, process the text data, send it to the ElevenLabs API, and handle the audio output—all within a serverless environment.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
elevenlabs: {
type: "app",
app: "elevenlabs",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.elevenlabs.io/v1/user`,
headers: {
"Accept": `application/json`,
"xi-api-key": `${this.elevenlabs.$auth.api_key}`,
},
})
},
})
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:
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}}