with Toggl Track and Google Vertex AI?
Emit new event when a time entry is started. See docs here
Emit new event when a time entry is created. See docs here
Emit new event when a time entry is updated. See docs here
Emit new event on receive a webhook event. See docs here
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
Get the time entry that is running now. [See docs here]https://developers.track.toggl.com/docs/api/time_entries#get-get-current-time-entry)
Toggl Track is a time tracking API that lets you start, stop, and manage timers and time entries, as well as manage projects, clients, and tasks associated with time records. With the Toggl Track API on Pipedream, you can automate time tracking activities, synchronize data across platforms, and generate insights from time tracking data to improve productivity and project management.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
toggl: {
type: "app",
app: "toggl",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.track.toggl.com/api/v9/me`,
auth: {
username: `${this.toggl.$auth.api_token}`,
password: `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}`,
},
})
},
})