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Databricks and Google Vertex AI integration
Save yourself the work of writing custom integrations for Databricks and Google Vertex AI and use n8n instead. Build adaptable and scalable Data & Storage, workflows that work with your technology stack. All within a building experience you will love.
How to connect Databricks 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 Databricks and Google Vertex AI integration
Create custom Databricks 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.
Databricks supported actions
Execute Query
Execute a SQL query and wait for results
Create Directory
Create a directory in volume
Delete Directory
Delete a directory in volume
Delete File
Delete a file from a volume
Download File
Download file content from a volume
Get File Metadata
Get file metadata from a volume
List Directory
List directory contents in volume
Upload File
Upload a file (up to 5 GiB) to Databricks volumes
Create Conversation Message
Create a new conversation message
Execute Message SQL Query
Execute a SQL query from a message attachment
Get Conversation Message
Get a conversation message by ID
Get Genie Space
Get details of a Genie space
Get Query Results
Get results of a SQL query execution
Start Conversation
Start a new conversation
Query Endpoint
Query a serving endpoint. The input format is automatically detected from the endpoint schema.
Create Catalog
Create a new catalog
Create Function
Create a new function
Create Table
Register a new table
Create Volume
Create a new volume
Delete Catalog
Delete a catalog
Delete Function
Delete a function
Delete Table
Delete a table
Delete Volume
Delete a volume
Get Catalog
Get catalog information
Get Function
Get function information
Get Table
Get table information
Get Volume
Get volume information
List Catalogs
List all catalogs
List Functions
List functions in schema
List Tables
List tables in schema
List Volumes
List volumes in schema
Update Catalog
Update catalog information
Create Index
Create a new vector search index
Get Index
Get details of a vector search index
List Indexes
List all vector search indexes
Query Index
Query a vector search index with text or vectors
Supported API Endpoints for Google Vertex AI
POST
Generate content
This endpoint generates content based on the input provided.
/vertex-ai/generative-ai/docs/model-reference/inference
POST
Call function
This endpoint allows for calling functions as part of the generative tasks.
/vertex-ai/generative-ai/docs/model-reference/function-calling
POST
Ground content
This endpoint grounds the content to ensure relevance and context.
/vertex-ai/generative-ai/docs/model-reference/grounding
GET
List API errors
This endpoint retrieves potential API errors that can occur during requests.
/vertex-ai/generative-ai/docs/model-reference/api-errors
POST
Generate text embeddings
This endpoint generates embeddings for given text inputs.
/vertex-ai/generative-ai/docs/model-reference/text-embeddings-api
POST
Generate multimodal embeddings
This endpoint generates embeddings that leverage multiple modalities.
/vertex-ai/generative-ai/docs/model-reference/multimodal-embeddings-api
POST
Generate and edit images
This endpoint is used for generating and editing images based on input specifications.
/vertex-ai/generative-ai/docs/model-reference/imagen-api
GET
Use code completions
API for generating code completion suggestions.
/vertex-ai/generative-ai/docs/model-reference/code-completion
GET
Perform batch predictions
API for executing batch predictions on data.
/vertex-ai/generative-ai/docs/model-reference/batch-prediction-api
POST
Batch prediction
API for performing batch prediction.
/vertex-ai/generative-ai/docs/model-reference/batch-prediction-api
GET
Tune models
API for tuning machine learning models.
/vertex-ai/generative-ai/docs/model-reference/tuning
POST
Tuning model parameters
API for tuning model parameters.
/vertex-ai/generative-ai/docs/model-reference/tuning
GET
Rapid evaluation
API for quickly evaluating model performance.
/vertex-ai/generative-ai/docs/model-reference/evaluation
POST
Evaluate model performance
API for rapid evaluation of models.
/vertex-ai/generative-ai/docs/model-reference/evaluation
GET
Use LlamaIndex
API for accessing the LlamaIndex for retrieval-augmented generations.
/vertex-ai/generative-ai/docs/model-reference/rag-api
GET
Manage extensions
API for managing custom extensions.
/vertex-ai/generative-ai/docs/model-reference/extension
POST
Manage extensions
API for handling extensions.
/vertex-ai/generative-ai/docs/model-reference/extension
GET
Count tokens
API for counting tokens in text inputs.
/vertex-ai/generative-ai/docs/model-reference/count-tokens
GET
Use reasoning engine
API for performing reasoning tasks.
/vertex-ai/generative-ai/docs/model-reference/reasoning-engine
POST
Utilize reasoning engine
API for using the reasoning engine capabilities.
/vertex-ai/generative-ai/docs/model-reference/reasoning-engine
GET
Use MedLM API
API for accessing medical language models.
/vertex-ai/generative-ai/docs/model-reference/medlm
POST
Access MedLM
API for accessing MedLM functionality.
/vertex-ai/generative-ai/docs/model-reference/medlm
POST
Generate and edit images
API for generating and editing images.
/vertex-ai/generative-ai/docs/model-reference/code-completion
POST
Access LlamaIndex
API for accessing LlamaIndex functionality.
/vertex-ai/generative-ai/docs/model-reference/rag-api
POST
Count tokens
API for counting tokens in text.
/vertex-ai/generative-ai/docs/model-reference/count-tokens
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!
Databricks and Google Vertex AI integration details
Databricks
Related categories
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
FAQs
FAQ
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