- Renamed `build_skill_artifact_set` to `build_skill_bundle` for improved clarity in asset management.
- Updated references in `SkillManager` to reflect the new method name and ensure consistent handling of skill bundles.
- Added `AppAssetsAttrsInitializer` to `SandboxManager` to enhance asset initialization processes.
- Implemented output truncation in `SandboxBashTool` to manage long command outputs effectively.
- Replaced SkillArtifactSet with SkillBundle across various components, enhancing the organization of skill dependencies and references.
- Updated SkillManager methods to load and save bundles instead of artifacts, improving clarity in asset management.
- Refactored SkillCompiler to compile skills into bundles, streamlining the dependency resolution process.
- Adjusted DifyCli and SandboxBashSession to utilize ToolDependencies, ensuring consistent handling of tool references.
- Introduced AssetReferences for better management of file dependencies within skill bundles.
- Updated binary files for Dify CLI on various platforms (darwin amd64, darwin arm64, linux amd64, linux arm64).
- Refactored skill compilation in LLMNode to improve clarity and maintainability by explicitly naming parameters and incorporating AppAssets for base path management.
- Minor fix in AppAssetFileTree to remove unnecessary leading slash in path construction.
- Introduced SandboxManager.delete_storage method for improved storage management.
- Refactored skill loading and tool artifact handling in DifyCliInitializer and SandboxBashSession.
- Updated LLMNode to extract and compile tool artifacts, enhancing integration with skills.
- Improved attribute management in AttrMap for better error handling and retrieval methods.
- Moved sandbox-related classes and functions into a dedicated module for better organization.
- Updated the sandbox initialization process to streamline asset management and environment setup.
- Removed deprecated constants and refactored related code to utilize new sandbox entities.
- Enhanced the workflow context to support sandbox integration, allowing for improved state management during execution.
- Adjusted various components to utilize the new sandbox structure, ensuring compatibility across the application.
- Introduced DraftAppAssetsInitializer for handling draft assets.
- Updated SandboxLayer to conditionally set sandbox ID and storage based on workflow version.
- Improved asset initialization logging and error handling.
- Refactored ArchiveSandboxStorage to support exclusion patterns during archiving.
- Modified command and LLM nodes to retrieve sandbox from workflow context, supporting draft workflows.
- Add helpers.py with connection management utilities:
- with_connection: context manager for connection lifecycle
- submit_command: execute command and return CommandFuture
- execute: run command with auto connection, raise on failure
- try_execute: run command with auto connection, return result
- Add CommandExecutionError to exec.py for typed error handling
with access to exit_code, stderr, and full result
- Remove run_command method from VirtualEnvironment base class
(now available as submit_command helper)
- Update all call sites to use new helper functions:
- sandbox/session.py
- sandbox/storage/archive_storage.py
- sandbox/bash/bash_tool.py
- workflow/nodes/command/node.py
- Add comprehensive unit tests for helpers with connection reuse
