with TestMonitor and Google Vertex AI?
Examines an image or video following given instructions. Results will contain the analysis findings. See the documentation
Analyzes a specified text for its underlying sentiment. See the documentation
TestMonitor API taps into the robust testing and project management platform, allowing you to automate issue tracking and test management processes. With this API, you can create, update, and retrieve issues, manage test cases and results, and integrate testing workflows with other systems. Leveraging Pipedream's serverless execution model, you can craft workflows that trigger on specific events within TestMonitor, reflect changes in real-time across other applications, or systematically analyze and report test outcomes.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
testmonitor: {
type: "app",
app: "testmonitor",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.testmonitor.$auth.domain}.testmonitor.com/api/v1/users`,
headers: {
Authorization: `Bearer ${this.testmonitor.$auth.api_token}`,
},
})
},
})
With the Google Vertex AI API, you can tap into a robust suite of AI tools offered by Google Cloud to build, deploy, and scale machine learning models. Whether you're processing data, training custom models, or using pre-trained ones, Vertex AI provides a unified platform for AI development. In Pipedream, you can create serverless workflows that interact with Vertex AI, allowing you to automate tasks like model training, prediction, and resource management without provisioning your own infrastructure.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
google_vertex_ai: {
type: "app",
app: "google_vertex_ai",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/oauth2/v1/userinfo`,
headers: {
Authorization: `Bearer ${this.google_vertex_ai.$auth.oauth_access_token}`,
},
})
},
})