with Google Cloud and Relevance AI?
Executes a specific tool within Relevance AI and waits for a response for up to 60 seconds. See the documentation
Sends a message directly to an agent in Relevance AI. This action doesn't wait for an agent response.
Inserts rows into a BigQuery table. See the docs and for an example here
Creates a scheduled query in Google Cloud. See the documentation
The Google Cloud API opens a world of possibilities for enhancing cloud operations and automating tasks. It empowers you to manage, scale, and fine-tune various services within the Google Cloud Platform (GCP) programmatically. With Pipedream, you can harness this power to create intricate workflows, trigger cloud functions based on events from other apps, manage resources, and analyze data, all in a serverless environment. The ability to interconnect GCP services with numerous other apps enriches automation, making it easier to synchronize data, streamline development workflows, and deploy applications efficiently.
module.exports = defineComponent({
props: {
google_cloud: {
type: "app",
app: "google_cloud",
}
},
async run({steps, $}) {
// Required workaround to get the @google-cloud/storage package
// working correctly on Pipedream
require("@dylburger/umask")()
const { Storage } = require('@google-cloud/storage')
const key = JSON.parse(this.google_cloud.$auth.key_json)
const storage = new Storage({
projectId: key.project_id,
credentials: {
client_email: key.client_email,
private_key: key.private_key,
}
})
await storage.authClient.getCredentials()
return {
status: "success",
authenticated: true,
projectId: key.project_id,
serviceAccount: key.client_email
}
},
})
Relevance AI is a powerful tool for handling complex data operations like clustering, vector search, and data visualization. On Pipedream, you can use the Relevance AI API to automate data enrichment, analysis, and integration tasks. This integration opens up possibilities for dynamic data workflows, enabling real-time data processing and insights generation across various platforms.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
relevance_ai: {
type: "app",
app: "relevance_ai",
}
},
async run({steps, $}) {
return await axios($, {
method: "post",
url: `https://api-${this.relevance_ai.$auth.region}.stack.tryrelevance.com/latest/agents/list`,
headers: {
"authorization": `${this.relevance_ai.$auth.project}:${this.relevance_ai.$auth.api_key}`,
},
})
},
})