with Google Vertex AI and Azure Storage?
Emit new event when a blob is deleted from a specified container in Azure Storage. See the documentation
Emit new event when a new blob is created to a specified container in Azure Storage. See the documentation
Emit new event when a new container is created in the specified Azure Storage account. See the documentation
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
Creates a new container under the specified account. If a container with the same name already exists, the operation fails. See the documentation
Groups a provided text into predefined categories. See the documentation
Deletes a specific blob from a container in Azure Storage. See the documentation
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}`,
},
})
},
})
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
azure_storage: {
type: "app",
app: "azure_storage",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://graph.microsoft.com/v1.0/me`,
headers: {
Authorization: `Bearer ${this.azure_storage.$auth.oauth_access_token}`,
},
})
},
})