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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Tiny URL
Triggers when new short url is created.
Do thisActions
Action is the task that follows automatically within your TinyURL integrations.
Create Tiny URL
Creates a tiny url.
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 TinyURL and GPT-trainer accounts to viaSocket. Once connected, you can set up a workflow where an event in TinyURL triggers actions in GPT-trainer (or vice versa).
Absolutely. You can customize how TinyURL 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 TinyURL 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 TinyURL 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 TinyURL
TinyURL is a URL shortening service that allows users to convert long web addresses into shorter, more manageable links. This service is particularly useful for sharing links on social media, in emails, or any platform where space is limited. TinyURL ensures that the shortened links are easy to remember and share, while still directing users to the intended destination.
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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