Cloudinary and Google Vertex AI integration
Save yourself the work of writing custom integrations for Cloudinary and Google Vertex AI and use n8n instead. Build adaptable and scalable Development, workflows that work with your technology stack. All within a building experience you will love.
How to connect Cloudinary 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 Cloudinary and Google Vertex AI integration
Create custom Cloudinary 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 Cloudinary
Create asset
Creates new assets in the Cloudinary account.
Delete assets
Delete assets with Node.
Upload assets
Upload assets with the CLI.
List assets
Retrieve a list of all assets.
Update assets
Update the details of an existing asset.
Delete assets
Remove an existing asset.
Rename assets
Change the name of an existing asset.
Relate assets
Establish a relationship between assets.
Search for assets
Perform a search to find specific assets.
Analyze assets
Perform analysis on the specified assets.
Rename assets
Changes the name of a specified asset.
Moderate assets
Moderates the specified assets based on custom rules.
Restore deleted assets
Restores assets that were deleted.
Invalidate cache for assets
Invalidate cached assets to ensure the latest versions are served.
Upload assets in Node.js
Tutorial for uploading assets using Node.
Upload multiple files in Node.js
Guide for uploading multiple files with Node.
Upload videos in Node.js
Tutorial for uploading videos using Node.
Upload images in Python
Guide for uploading images using Python SDK.
Upload videos in Python
Tutorial for uploading videos using Python SDK.
Upload Widget
Overview of the Upload Widget functionality.
Get transformation reference
Retrieve the transformation reference details.
Get upload API reference
Retrieve the image upload API reference details.
Get admin API
Retrieve the admin API reference details.
Get provisioning API
Retrieve the provisioning API reference details.
Get analyze API
Retrieve the analyze API reference details.
Get live streaming API
Retrieve the live streaming API reference details.
Generate upload signature
Generates a signature for uploading assets.
Find your credentials
Steps to locate your Cloudinary credentials.
Enable automatic backups
Enables automatic backups for your media assets.
Restore asset versions
Restores specific versions of assets.
Manage custom metadata
Manage custom metadata for assets to enhance organization and searchability.
Live streaming (Beta)
Provides capabilities for live video streaming.
Upload API
API for uploading images and videos to Cloudinary.
Provisioning API
API for user provisioning in Cloudinary.
List images in Next.js
Tutorial for listing images in a Next.
To set up Cloudinary 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 Cloudinary 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 Cloudinary 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.
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!
Cloudinary 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 Cloudinary connect with Google Vertex AI?
Can I use Cloudinary’s API with n8n?
Can I use Google Vertex AI’s API with n8n?
Is n8n secure for integrating Cloudinary and Google Vertex AI?
How to get started with Cloudinary and Google Vertex AI integration in n8n.io?
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