Improved API and Command Specifications: The activate command has been revised to allow for more precise control over the number of workers and resources.
Separate AI Pack Namespaces: You can now choose to deploy an AI Pack into its own dedicated namespace, which helps with isolation and resource management.
Entry Point Configuration: You can now specify a custom entry point when using the AI Logic Deployer (ALD), enabling more flexible deployment configurations.
Detailed Solution Descriptions: New functionality allows you to write and save an overview and description for your solutions, which helps with documentation and management.
Port Validation Alert: The system now provides an alert during the register process if the specified port is not 80, helping to prevent common configuration errors.
Enhanced Deployment Feedback: The activate command now waits for the deployment to be fully successful before returning a success message, providing more reliable feedback.
Version Information: The list of activated solutions now displays the version of each, providing a clearer overview of all active deployments.
Introduction of ALO CLI (alm): A new command-line interface (CLI), alm, has been introduced to allow users to perform AI solution development, deployment, and management tasks directly from the terminal. This significantly enhances user convenience and workflow efficiency.
End-to-End Solution Lifecycle Management: Provides the functionality to manage the entire lifecycle of a Service API, from creation to deletion, through intuitive commands including register, deploy, activate, deactivate, and delete.
Official Python 3.12 Support: The system now officially supports Python 3.12, allowing developers to leverage the latest features and performance improvements of the language.
Support for uv for Faster Dependency Installation: Integration with uv, an extremely fast Python package installer, is now supported. This can significantly speed up the setup and deployment process by reducing the time spent on dependency installation.
Local API Testing (alm api): Added the alm api command, which enables immediate testing of solutions under development in a local environment without deploying to the cloud. This facilitates rapid development and debugging.
Internal API for S3 Bucket Address Retrieval: A new internal API endpoint is available for programmatically retrieving S3 bucket addresses, making it easier to manage and access data storage locations from within your solutions.
Secure Authentication (alm login): The alm login feature allows for secure authentication into the AI Conductor system and manages the authentication tokens and workspace settings required for subsequent operations.