feat(robot): NamespaceCacheMeta with python_executable, namespace caching, and weakref finalizer

[Copilot]

Namespace-level resource docs were cached using only file path + mtime, meaning a Python environment change (e.g. switching venvs with same Python version) would silently serve stale cache. Adds a dedicated NamespaceCacheMeta that includes the Python executable as a cache key, plus a weakref.finalize hook on Namespace.

Changes

data_cache.py

• Added CacheSection.NAMESPACE = "namespace" — dedicated cache section separate from RESOURCE.

imports_manager.py

• NamespaceCacheMeta — new dataclass extending the RobotFileMeta pattern with python_executable: str:

  @dataclass
  class NamespaceCacheMeta:
      meta_version: str
      source: str
      mtime_ns: int
      python_executable: str  # distinguishes caches across Python environments

• get_namespace_meta() — static factory that captures sys.executable at read time.
• _get_namespace_doc_cached() / _save_namespace_doc_cache() — read/write ResourceDoc under CacheSection.NAMESPACE, validating the full NamespaceCacheMeta including python_executable.
• get_libdoc_from_model() and get_resource_doc_from_document() — switched from the python_executable-unaware resource cache to the new namespace cache.

namespace.py

• Added weakref.finalize(self, Namespace._finalize, weakref.ref(imports_manager)) in __init__ (atexit=False). The static _finalize method documents the automatic cleanup contracts (event listeners via WeakMethod, import entry sentinels via existing weakref.finalize registrations in ImportsManager) and provides an explicit hook for future cleanup.

Tests

• 10 new regression tests covering CacheSection.NAMESPACE, NamespaceCacheMeta equality/differentiation by python_executable and mtime_ns, filepath_base generation, and get_namespace_meta() behaviour on existing vs missing files.

Original prompt

Delegate: "Delegate to cloud agent"

[Chronological Review: The conversation began with discussions about implementing a weak reference finalizer, followed by requests for documentation and commit messages related to recent changes. The user expressed concerns about variable resolution and namespace management, leading to deeper discussions about language server implementations and the handling of imports. The conversation evolved to address the need for caching mechanisms, diagnostics, and reference management for keywords and variables. The user emphasized the importance of regression tests and the overall architecture of the namespace and language server. The final phase involved the user requesting a detailed implementation plan and confirming readiness to start the implementation.]

[Intent Mapping:

1. "könnte man hier nicht auch einen weakref finalizer verwenden?" - Inquiry about using weak references.
2. "kannst du das mal implemetieren?" - Request for implementation of the weak reference finalizer.
3. "dann dokumentier mal das wir das umgesetzt haben" - Request for documentation of the implementation.
4. "dann schreib mal ein commit message für diese änderungen" - Request for a commit message.
5. "wir haben jetzt im Namespace noch eine eigene auflösung für variablen..." - Discussion about variable resolution in the namespace.
6. "ich frage mich gerade wie es language server implementationen wie für rust oder python machen?" - Inquiry about language server implementations.
7. "was ist mit dem import handling und so?" - Question about import handling.
8. "ok, an welchen stellen brauchen wir denn das ast-model..." - Inquiry about the use of the AST model.
9. "C mit einplanen." - Request to include caching in the implementation plan.
10. "ja, das sollst du" - Confirmation to proceed with the plan.
11. "ja, nur bei den NamespaceCacheMeta brauchst du die python_executable: str..." - Clarification about cache requirements.
12. "ja, es gibt noch mehr offene punkte..." - Discussion about the need for regression tests.
13. "Start implementation" - Request to begin implementation.
14. "Delegate: 'Delegate to cloud agent'" - Command to delegate the task to a cloud agent.]

[Technical Inventory:

• Weak Reference Finalizer: Discussed as a potential implementation.
• Namespace Management: Emphasis on variable resolution and caching.
• Language Server Protocol (LSP): Considerations for handling imports and diagnostics.
• AST Model: Discussed in terms of memory efficiency and necessity.
• Regression Testing: Highlighted as a requirement for ensuring code reliability.]

[Code Archaeology:

• No specific code files or functions were directly modified during the conversation, but discussions revolved around the architecture and implementation strategies for the namespace and language server.]

[Progress Assessment:

• Completed Tasks: Discussion of weak reference finalizer and namespace management.
• Partially Complete Work: Implementation plan for caching and variable resolution is in progress.
• Validated Outcomes: No specific features confirmed working yet, as implementation has just begun.]

[Context Validation: All critical information for continuation is captured, including user requests for implementation, documentation, and testing.]

[Recent Commands Analysis:

• Last Agent Commands: "Start implementation" and "Delegate: 'Delegate to cloud agent'".
• Tool Results Summary: The agent was preparing to start the implementation of the discussed features and delegate tasks to a cloud agent.
• Pre-Summary State: The agent was actively working on finalizing the implementation plan and preparing to delegate tasks.
• Operation Context: These commands were executed to initiate the implementation phase of the project, aligning with the user's goals of enhancing the language server and namespace management.]

1. Conversation Overview: - Primary Objectives: The user requested the implementation of a weak reference finalizer, documentation of changes, commit messages, and discussions on namespace management and language server protocols. - Session Context: The conversation flowed from initial inquiries about weak references to detailed discussions on variable resolution, caching, and the architecture of the language server. - User Intent Evolution: The user moved from specific implementation requests to broader architectural considerations, culminating in a readiness to start the implementation.

2. Technical Foundation:

• Weak Reference Finalizer: Proposed to manage memory more efficiently.
• Namespace Management: Focus on variable resolution and caching strategies.
• Language Server Protocol (LSP): Considerations for handling imports and diagnostics.
• AST Model: Discussed for its memory implications.

3. Codebase Status:

• No specific files were modified, but discussions centered around the architecture of the namespace and language server.

4. Problem Resolution:

• Issues Encountere...

Created from VS Code.

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