Connect Short URL and GPT-trainer to Build Intelligent Automations
Enable Integrations or automations with these events of Short URL and GPT-trainer
Enable Integrations or automations with these events of Short URL and GPT-trainer
Actions
Shorten URL
Creates a shortened version of a given 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 Short URL and GPT-trainer accounts to viaSocket. Once connected, you can set up a workflow where an event in Short URL triggers actions in GPT-trainer (or vice versa).
Absolutely. You can customize how Short URL 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 Short URL 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 Short URL 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 Short URL
ShortURL.at is a service that allows users to shorten long URLs into more manageable and shareable links. This tool is ideal for social media, email campaigns, and any other platform where space is limited or a clean, concise link is preferred. It helps in tracking clicks and analyzing the performance of the shortened URLs.
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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