with ecwid and Google Vertex AI?
Search for new orders which are PAID and AWAITING_PROCESSING. Emits events for each order and sets order fulfilment status to PROCESSING
Examines an image or video following given instructions. Results will contain the analysis findings. See the documentation
Update the Status of an Ecwid Order. Makes use of the Update Order API
Analyzes a specified text for its underlying sentiment. See the documentation
Groups a provided text into predefined categories. See the documentation
Ecwid's API offers dynamic access to an online store's data, allowing for the automation of tasks such as inventory management, order processing, and customer data analysis. With Pipedream's serverless integration platform, you can create custom workflows that trigger actions within Ecwid or synchronize data across various other apps and services. This capability can streamline operations, save time, and reduce the likelihood of human error.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
ecwid: {
type: "app",
app: "ecwid",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://app.ecwid.com/api/v3/${this.ecwid.$auth.storeId}/profile`,
headers: {
Authorization: `Bearer ${this.ecwid.$auth.client_secret}`,
},
})
},
})
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}`,
},
})
},
})