with Twitch and AssemblyAI?
Blocks a user; that is, adds a specified target user to your blocks list
Export your completed transcripts in SRT (srt) or VTT (vtt) format, which can be used for subtitles and closed captions in videos. See the documentation
Checks if you are subscribed to the specified user's channel
Fetches a specific transcribed result from the AssemblyAI API. See the documentation
The Twitch API unlocks a world of possibilities for engaging with live streaming communities and understanding audience behaviors. With Pipedream, you can harness this API to automate many aspects of Twitch interaction and analysis. From tracking stream stats to automating chat messages, the Twitch API lets you create workflows that interact with Twitch's vast live streaming ecosystem. Pipedream's serverless platform streamlines these tasks, making it simple to connect Twitch with other services for enhanced functionalities.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
twitch: {
type: "app",
app: "twitch",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.twitch.tv/helix/users`,
headers: {
Authorization: `Bearer ${this.twitch.$auth.oauth_access_token}`,
"Client-ID": `${this.twitch.$auth.oauth_client_id}`,
},
})
},
})
The AssemblyAI API provides powerful speech recognition and natural language processing capabilities. It allows users to transcribe audio, analyze sentiment, detect topics, and more. In Pipedream, you can leverage these features to create automated workflows that process audio and text data. Connect AssemblyAI to various apps and services, trigger actions based on the API's output, and build robust, serverless data pipelines.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
assemblyai: {
type: "app",
app: "assemblyai",
}
},
async run({steps, $}) {
const data = {
"audio_url": `{{your_audio_url}}`,
//for testing, try: https://storage.googleapis.com/aai-web-samples/espn-bears.m4a
}
return await axios($, {
method: "POST",
url: `https://api.assemblyai.com/v2/transcript`,
headers: {
"authorization": `${this.assemblyai.$auth.api_key}`,
},
data,
})
},
})