Google Vertex AI and LeadBoxer integration
Save yourself the work of writing custom integrations for Google Vertex AI and LeadBoxer and use n8n instead. Build adaptable and scalable AI, workflows that work with your technology stack. All within a building experience you will love.
How to connect Google Vertex AI and LeadBoxer
Create a new workflow and add the first step
In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.
Build your own Google Vertex AI and LeadBoxer integration
Create custom Google Vertex AI and LeadBoxer workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.
Supported API Endpoints for Google Vertex AI
Generate content
This endpoint generates content based on the input provided.
Call function
This endpoint allows for calling functions as part of the generative tasks.
Ground content
This endpoint grounds the content to ensure relevance and context.
List API errors
This endpoint retrieves potential API errors that can occur during requests.
Generate text embeddings
This endpoint generates embeddings for given text inputs.
Generate multimodal embeddings
This endpoint generates embeddings that leverage multiple modalities.
Generate and edit images
This endpoint is used for generating and editing images based on input specifications.
Use code completions
API for generating code completion suggestions.
Perform batch predictions
API for executing batch predictions on data.
Batch prediction
API for performing batch prediction.
Tune models
API for tuning machine learning models.
Tuning model parameters
API for tuning model parameters.
Rapid evaluation
API for quickly evaluating model performance.
Evaluate model performance
API for rapid evaluation of models.
Use LlamaIndex
API for accessing the LlamaIndex for retrieval-augmented generations.
Manage extensions
API for managing custom extensions.
Manage extensions
API for handling extensions.
Count tokens
API for counting tokens in text inputs.
Use reasoning engine
API for performing reasoning tasks.
Utilize reasoning engine
API for using the reasoning engine capabilities.
Use MedLM API
API for accessing medical language models.
Access MedLM
API for accessing MedLM functionality.
Generate and edit images
API for generating and editing images.
Access LlamaIndex
API for accessing LlamaIndex functionality.
Count tokens
API for counting tokens in text.
To set up Google Vertex AI integration, add the HTTP Request node to your workflow canvas and authenticate it using a generic authentication method. The HTTP Request node makes custom API calls to Google Vertex AI to query the data you need using the API endpoint URLs you provide.
See the example hereThese API endpoints were generated using n8n
n8n AI workflow transforms web scraping into an intelligent, AI-powered knowledge extraction system that uses vector embeddings to semantically analyze, chunk, store, and retrieve the most relevant API documentation from web pages. Remember to check the Google Vertex AI official documentation to get a full list of all API endpoints and verify the scraped ones!
Supported API Endpoints for LeadBoxer
Get companies
Retrieve companies with associated leads based on specified criteria.
Get events
Retrieve your top leads with fine grained filtering criteria.
Get sessions
Retrieve sessions based on specified criteria.
Get leads
Retrieve your leads as per specified criteria.
Add dataset
Adds new dataset to the account.
Remove dataset
Removes the given dataset from the account.
Update form tracking
Updates form tracking of the given dataset.
Update dataset name
Updates human name of the given dataset.
Remove user dataset
To remove association between user and dataset.
List user datasets
To fetch users and their associated datasets for given account
Add user
Adds new user to the account.
Get user datasets
To retrieve datasets for the user.
Get leadscore formula
To retrieve your leadscore formula.
Update leadscore formula
To update leadscore formula.
Remove user
Removes the given user from the account.
Update user name
Updates name of the given user.
Resend user invite
Resends invitation to the specified user.
Update user role
Updates role of the given user.
Check URL validation
Validates the format and availability of a specified URL.
Get reports
Retrieves a list of reports from the dashboard.
To set up LeadBoxer integration, add the HTTP Request node to your workflow canvas and authenticate it using a generic authentication method. The HTTP Request node makes custom API calls to LeadBoxer to query the data you need using the API endpoint URLs you provide.
See the example hereThese API endpoints were generated using n8n
n8n AI workflow transforms web scraping into an intelligent, AI-powered knowledge extraction system that uses vector embeddings to semantically analyze, chunk, store, and retrieve the most relevant API documentation from web pages. Remember to check the LeadBoxer official documentation to get a full list of all API endpoints and verify the scraped ones!
Google Vertex AI and LeadBoxer integration details
Google Vertex AI
Google Vertex AI is a unified machine learning platform that enables developers to build, deploy, and manage models efficiently. It provides a wide range of tools and services, such as AutoML and datasets, to accelerate the deployment of AI solutions.
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FAQ
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