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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Order
Triggers when a new order is created.
Do thisActions
Action is the task that follows automatically within your Starshipit integrations.
Create a Order
Create an outbound order.
List Shipped Orders
Retrieve details of orders that have been shipped.
Create QA Source
Create a QA source for a chatbot specified by chatbot uuid
Create URL Source
Creates a URL source for a chatbot specified by chatbot uuid.
Create Source Tag
Create a source tag for a chatbot.
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Frequently Asked Questions
To start, connect both your Starshipit and GPT-trainer accounts to viaSocket. Once connected, you can set up a workflow where an event in Starshipit triggers actions in GPT-trainer (or vice versa).
Absolutely. You can customize how Starshipit data is recorded in GPT-trainer. This includes choosing which data fields go into which fields of GPT-trainer, setting up custom formats, and filtering out unwanted information.
The data sync between Starshipit and GPT-trainer typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Starshipit and GPT-trainer. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Starshipit
Starshipit is an integrated shipping and tracking software that helps businesses automate their shipping processes. The app allows users to manage orders, print shipping labels, and provide real-time tracking updates to customers, enhancing the efficiency of e-commerce operations.
Learn MoreAbout GPT-trainer
GPT Trainer is a platform designed to enhance and customize the training of AI models, particularly those based on the GPT architecture. It provides tools and resources for developers and researchers to fine-tune and optimize AI models for specific tasks and applications.
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