Snowflake
A data warehouse built for the cloud
Integrate the Snowflake API with the Google Vertex AI API
Setup the Snowflake API trigger to run a workflow which integrates with the Google Vertex AI API. Pipedream's integration platform allows you to integrate Snowflake and Google Vertex AI remarkably fast. Free for developers.
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Popular Ways to Connect Snowflake with Google Vertex AI#
Popular Snowflake and Google Vertex AI Triggers#
Popular Snowflake and Google Vertex AI Actions#
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
Groups a provided text into predefined categories. See the documentation
Overview of Snowflake#
Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.
Getting Started
1. Create a user, role and warehouse in Snowflake
Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI.
We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.
2. Enter those details in Pipedream
Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.
You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.
3. Build your first workflow
Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.
Learn more at Pipedream University.
Connect Snowflake#
import snowflake from '@pipedream/snowflake';
export default defineComponent({
props: {
snowflake,
},
async run({ $ }) {
// Component source code:
// https://github.com/PipedreamHQ/pipedream/tree/master/components/snowflake
return this.snowflake.executeQuery({
sqlText: `SELECT CURRENT_TIMESTAMP()`,
binds: [],
});
},
});Overview of Google Vertex AI#
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.
Connect Google Vertex AI#
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}`,
},
})
},
})
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