chore: stabilize baseline audit and optional deployment imports

[hudsonaikins]

Summary

• make package imports resilient when optional Docker dependency is unavailable
• fix deployment module lint/exception chaining issues
• add repeatable audit targets in Makefile and document the hardening PR plan

Validation

• make audit
• ruff check neural tests scripts utils
• mypy neural
• pytest tests/

Greptile Summary

This PR stabilizes the baseline audit infrastructure and makes package imports resilient when optional Docker dependencies are unavailable. The changes enable the package to be imported and tested without Docker SDK installed, fix linter and exception chaining issues in the deployment module, and add repeatable quality/security audit targets to the Makefile.

Key Changes:

• Made neural.deployment module optional when Docker SDK is missing via try/except import pattern in neural/__init__.py
• Added proper exception chaining (from e) in deployment provider for better error traceability
• Removed unused imports (os, subprocess) from deployment code
• Added make audit, make audit-security, and make audit-deps targets for quality gates
• Created HARDENING_PR_PLAN.md documenting 6-phase improvement plan
• Upgraded GitHub Actions artifact actions from v3 to v4 across all workflows
• Added conditional script checks in workflows to gracefully handle missing documentation scripts
• Fixed YAML indentation issues in docs.yml and pr-docs.yml
• Added explicit permissions block to pr-docs.yml

The PR successfully achieves its stated goal of establishing baseline audit capabilities while maintaining backward compatibility.

Confidence Score: 4/5

• This PR is safe to merge with minor style considerations
• The changes are well-structured infrastructure improvements focusing on resilience and audit capabilities. All Python code changes follow best practices (proper exception chaining, optional imports, removing unused code). The workflow changes add defensive checks for missing scripts. Minor style improvements could be made (heredoc indentation, redundant type annotation), but these don't affect functionality. No logic errors or security issues detected.
• Pay attention to .github/workflows/pr-docs.yml to verify validate_docs.py provides equivalent functionality to check_api_docs.py

Important Files Changed

Filename	Overview
neural/init.py	Added optional import for deployment module when Docker SDK is missing
neural/deployment/base.py	Fixed import formatting and made cleanup() abstract method
neural/deployment/docker/provider.py	Added exception chaining (from e) for better error traceability, removed unused imports
Makefile	Added audit, audit-security, and audit-deps targets for quality gates
HARDENING_PR_PLAN.md	New documentation file outlining 6-phase hardening plan
.github/workflows/docs-monitoring.yml	Upgraded artifact actions to v4, added fallback heredoc for placeholder dashboard
.github/workflows/pr-docs.yml	Added permissions block, fixed indentation, changed script reference

_{Last reviewed commit: eaea8ff}

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📚 Documentation Status

✅ Code changes detected

• Docstring coverage checked
• API documentation validation completed
  ✅ Example changes detected
• Example documentation validated
• Code syntax verified

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Additional Comments (1)

neural/deployment/base.py
Made cleanup() an abstract method requiring all providers to implement resource cleanup. This prevents providers from accidentally omitting cleanup logic.

_{Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!}

Prompt To Fix With AI

This is a comment left during a code review.
Path: neural/deployment/base.py
Line: 140-147

Comment:
Made `cleanup()` an abstract method requiring all providers to implement resource cleanup. This prevents providers from accidentally omitting cleanup logic.

<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>

How can I resolve this? If you propose a fix, please make it concise.