- Removed obsolete file upload/download functions and related constants from the Assistant struct, streamlining the codebase.
- Updated the connector type in load tests to use "gpt-3_5-turbo" for improved compatibility with current models.
- Introduced VisionCapableModels to support a range of models with vision capabilities, enhancing AI functionality.
- Enhanced the File struct to include additional fields for description, URL, and document IDs, improving data management for file handling.
These changes improve the overall structure and maintainability of the Neo API, paving the way for future enhancements in assistant capabilities.
- Added the github.com/spf13/cast dependency to improve type conversion capabilities.
- Enhanced the requestMessages function to include prompts, allowing for more dynamic message handling.
- Updated the LoadBuiltIn function to ensure the "Built-in" tag is added if it doesn't already exist, improving assistant organization.
- Refactored sorting logic to utilize the cast package for better type safety.
These changes support improved functionality and maintainability in the assistant management process.
- Removed unused assistant-related functions and types from the Neo API, including local chat and file handling, to streamline the codebase.
- Refactored the assistant initialization process, consolidating the loading and configuration of assistants, including Vision and Connector settings.
- Updated the DSL struct to enhance clarity and maintainability, ensuring better configuration management for assistants.
- Improved error handling and modularity in the assistant loading process, paving the way for future enhancements in AI functionalities.
- Simplified the assistant loading process by removing the asynchronous query for the assistant list and replacing it with a direct call to retrieve the default assistant.
- Introduced a new method, defaultAssistant, to streamline the retrieval of the default assistant based on the current configuration.
- Enhanced the LoadStore function to support loading assistants from a specified path, improving flexibility in assistant management.
- Updated the overall structure for better readability and maintainability, ensuring a more efficient assistant initialization process.
