Connect Hubstaff and GPT-trainer to Build Intelligent Automations
Enable Integrations or automations with these events of Hubstaff and GPT-trainer
Enable Integrations or automations with these events of Hubstaff and GPT-trainer
Actions
Create a Project
Create a new project in Hubstaff for the selected organization, with optional name, description, client, and billable settings.
Create a Client
Create a new client in Hubstaff for a selected organization, including optional name, emails, phone, address, project associations, invoice notes, and net payment terms.
Create a To-Do
Create a task in a selected Hubstaff project and assign it to a team member.
List Organization
list all the organization
Get User
Get the user of HUbstaff.
Create QA Source
Create a QA source for a chatbot specified by chatbot uuid
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Frequently Asked Questions
To start, connect both your Hubstaff and GPT-trainer accounts to viaSocket. Once connected, you can set up a workflow where an event in Hubstaff triggers actions in GPT-trainer (or vice versa).
Absolutely. You can customize how Hubstaff 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 Hubstaff 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 Hubstaff 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 Hubstaff
Hubstaff is a time tracking software that helps remote managers see what their workers are doing and track time to specific projects. It also provides detailed reports and productivity analytics.
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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