Google Vertex AI and Lark Integration

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Automate AI-powered insights: Use Google Vertex AI to analyze Lark messages and route urgent issues to the right teams. Latenode's visual editor and flexible JavaScript nodes make custom logic easy, all while you pay only for execution time.

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Google Vertex AI

Lark

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Vertex AI and Lark

Create a New Scenario to Connect Google Vertex AI and Lark

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Vertex AI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Vertex AI or Lark will be your first step. To do this, click "Choose an app," find Google Vertex AI or Lark, and select the appropriate trigger to start the scenario.

Add the Google Vertex AI Node

Select the Google Vertex AI node from the app selection panel on the right.

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Google Vertex AI

Configure the Google Vertex AI

Click on the Google Vertex AI node to configure it. You can modify the Google Vertex AI URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the Lark Node

Next, click the plus (+) icon on the Google Vertex AI node, select Lark from the list of available apps, and choose the action you need from the list of nodes within Lark.

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Authenticate Lark

Now, click the Lark node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Lark settings. Authentication allows you to use Lark through Latenode.

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Configure the Google Vertex AI and Lark Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Run node once

Set Up the Google Vertex AI and Lark Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Google Vertex AI, Lark, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Google Vertex AI and Lark integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Lark (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Google Vertex AI and Lark

Lark + Google Vertex AI + Google Sheets: When a new message is received in a Lark group chat, the content is analyzed using Google Vertex AI to determine its sentiment. The message and its sentiment score are then logged in a Google Sheet for tracking customer feedback.

Lark + Google Vertex AI + Jira: When a new message is received in a Lark group chat, the message content is analyzed using Google Vertex AI to classify the incident type. A Jira ticket is then created with the classified incident type and assigned a priority based on the AI analysis.

Google Vertex AI and Lark integration alternatives

About Google Vertex AI

Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.

About Lark

Use Lark within Latenode to centralize team comms & automate notifications based on workflow triggers. Aggregate messages, streamline approvals, and post updates to specific channels. Benefit from Latenode's visual editor and logic tools for advanced routing that keeps everyone informed and aligned.

See how Latenode works

FAQ Google Vertex AI and Lark

How can I connect my Google Vertex AI account to Lark using Latenode?

To connect your Google Vertex AI account to Lark on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google Vertex AI and click on "Connect".
  • Authenticate your Google Vertex AI and Lark accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically summarize customer feedback in Lark from Vertex AI?

Yes! Latenode lets you build no-code workflows to analyze feedback with Vertex AI and post summaries to Lark. This improves team awareness and speeds response times.

What types of tasks can I perform by integrating Google Vertex AI with Lark?

Integrating Google Vertex AI with Lark allows you to perform various tasks, including:

  • Analyze support tickets with Vertex AI and notify relevant teams in Lark.
  • Generate meeting summaries using Vertex AI and share them in Lark channels.
  • Create a knowledge base by posting Vertex AI-analyzed documents to Lark.
  • Translate customer inquiries from Lark to English using Vertex AI.
  • Moderate Lark group chats for toxic content using Vertex AI's content filter.

How does Latenode enhance Google Vertex AI integration capabilities?

Latenode enables complex Google Vertex AI workflows using visual tools, JavaScript, and custom logic, beyond standard integrations.

Are there any limitations to the Google Vertex AI and Lark integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Large data transfers may require optimization for performance.
  • Real-time processing is subject to Google Vertex AI and Lark API rate limits.
  • Complex prompt engineering requires familiarity with Google Vertex AI best practices.

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