Voice Monkey is a free Skill that allows you to trigger Alexa Routines from external sources such as IFTTT. It also allows you to make dynamic and custom Text to Speech announcements over your Amazon Echo or other Alexa smart speaker.
This action will display an image on your device with a screen e.g. Echo Show. See docs here
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
This action will display a video on your device with a screen e.g. Echo Show. See docs here
This action will make an annoucement on your device using the text you supply. See docs here
This action will make an annoucement on your device using any parameters you set. See docs here
The Voice Monkey API provides a bridge between Alexa and Pipedream, enabling you to send custom announcements, notifications, or commands to your Alexa devices. With this API, you can trigger Alexa to speak a custom message or execute routines, leveraging the power of voice interaction in your automated workflows. It's particularly useful for smart home enthusiasts, productivity hackers, and businesses looking to integrate voice notifications into their services.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
voice_monkey: {
type: "app",
app: "voice_monkey",
}
},
async run({steps, $}) {
const data = {
"access_token": `${this.voice_monkey.$auth.access_token}`,
"secret_token": `${this.voice_monkey.$auth.secret_token}`,
"monkey": `pipedream-monkey-1`,
}
return await axios($, {
method: "post",
url: `https://api.voicemonkey.io/trigger`,
data,
})
},
})
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}}