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.
Create custom Fluent Support 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.
List tickets
Retrieves all tickets available in the system.
Get ticket
Fetches a specific ticket by its ID.
Create ticket
Creates a new ticket by the customer.
Reply to ticket
Submits a reply to an existing ticket as an agent.
Update reply
Updates a reply to a specific ticket.
Get ticket
Retrieve a specific ticket by Ticket ID.
Create ticket
Create a new Ticket using agent.
Create ticket
This endpoint creates a new ticket.
Reply to ticket
This endpoint adds a reply to a ticket.
Update reply
This endpoint updates a specific reply for a ticket.
Delete ticket(s)
This endpoint deletes one or more tickets.
Add tag to ticket
This endpoint adds a tag to a specific ticket.
Remove tag from ticket
This endpoint removes a tag from a specific ticket.
Update ticket properties
This endpoint updates properties associated with the ticket.
List customers
Retrieves a list of all customers.
Get customer
Fetches details of a specific customer by ID.
List customers
This endpoint gets all customers.
Get specific customer
This endpoint retrieves a specific customer.
Get customer
This endpoint retrieves a specific customer by customer ID.
Get overall reports
Retrieves overall reports based on tickets.
Get overall reports
This endpoint returns overall reports.
Get ticket stats
This endpoint returns ticket growth statistics.
Get Ticket Resolve Stats
This endpoint will return closed tickets.
Get Ticket Response Growth
This endpoint will return the stats of total replies by agents.
Get Agents Summary
This endpoint will returns total summary of agents.
List saved replies
Retrieves all saved replies.
Get user overall stats
This endpoint will return user's personal overall stats
Get ticket resolve stats
This endpoint returns total ticket closed by user.
Get ticket response growth
This endpoint returns total replies done by user.
Get user summary
This endpoint returns total summary of the current agent.
Get specific saved reply
This endpoint returns a specific saved reply.
List activities
This endpoint returns all activities.
Get activity settings
This endpoint returns activity settings.
List mailboxes
This endpoint returns all mailboxes.
Get mailbox
This endpoint returns a specific mailbox.
Get mailbox email configs
This endpoint returns mailbox email configs in JSON structure.
To set up Fluent Support 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 Fluent Support 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 Fluent Support official documentation to get a full list of all API endpoints and verify the scraped ones!
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!
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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