Connect Figma and GPT-trainer to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Figma
Choose an Action
Automatically do this!
Create QA Source
Create URL Source
Create Source Tag
Enable Integrations or automations with these events of Figma and GPT-trainer
Enable Integrations or automations with these events of Figma and GPT-trainer
Actions
Create Comment
Create comment on a file.
Add Comment Reaction
Create a new comment reaction on a file comment.
Delete Comment Reaction
Deletes a specific comment reaction.
Delete Comment
Deletes a specific comment
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.
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Frequently Asked Questions
To start, connect both your Figma and GPT-trainer accounts to viaSocket. Once connected, you can set up a workflow where an event in Figma triggers actions in GPT-trainer (or vice versa).
Absolutely. You can customize how Figma 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 Figma 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 Figma 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 Figma
Figma is a collaborative interface design tool that allows teams to create, prototype, and share designs seamlessly. It is widely used by designers and developers to work together in real-time, making the design process more efficient and effective.
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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