BrowserStack and Google Vertex AI integration
How to connect BrowserStack and Google Vertex AI
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 BrowserStack and Google Vertex AI integration
Create custom BrowserStack and Google Vertex AI 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 BrowserStack
Get plan details
Retrieve details about your Automate plan.
Get plan details
Obtain information about your Automate plan including the number of parallel sessions allowed and currently running.
Get browser list
Obtain a list of available OS, browsers, and real mobile devices.
Get browser list
Retrieve the list of available browsers for automation.
Get project list
Fetch a list of projects associated with your account.
Get project details
Retrieve the details of a specific project.
Get status badge
Obtain the status badge for a project.
Update project details
Modify the details of an existing project.
Delete project
Remove a specific project from your account.
Get project list
Fetch a list of projects associated with the user.
Get project details
Retrieve detailed information about a specific project.
Get status badge
Obtain the status badge for a specific project.
Get build list
Fetch a list of builds related to your projects.
Update build details
Change the details of an existing build.
Delete build
Remove a specific build from your account.
Get build list
Retrieve a list of builds under a project.
Get session list
Retrieve a list of all sessions associated with your account.
Get session details
Obtain detailed information about a specific session.
Delete session
Remove a specific session from your account.
Get session list
Fetch a list of sessions associated with the user's account.
Get session details
Get detailed information about a specific session.
Upload media file
Upload a media file to your account.
List uploaded media files
Retrieve a list of files uploaded to the account.
Upload media file
Upload a media file for use in tests.
Delete media file
Remove a specific media file from the user's account.
List builds
Fetch the 10 recent test builds that have run on BrowserStack using your username and access key.
Update build
Update a specific build name.
Delete multiple builds
Delete multiple builds at the same time.
List builds
Retrieve a list of builds with optional filtering by parameters.
List builds with offset
Retrieve builds starting from a specific offset.
List builds by status
Retrieve builds filtered by their status.
List builds by project ID
Retrieve builds associated with a specific project ID.
Update build
Update the name of a completed build using its ID.
Delete multiple builds
Delete up to five builds at once using their IDs.
Upload terminal logs
Upload terminal logs for a specified build using its ID.
Get browser list
Retrieve the complete list of OS, browser, and mobile device combinations that BrowserStack supports.
To set up BrowserStack 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 BrowserStack to query the data you need using the API endpoint URLs you provide.
These 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 BrowserStack official documentation to get a full list of all API endpoints and verify the scraped ones!
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.
These 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!
BrowserStack and Google Vertex AI 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.
Related categories
FAQ
Can BrowserStack connect with Google Vertex AI?
Can I use BrowserStack’s API with n8n?
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