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This extends the previous fix to handle capitalized fields across ALL guardrail types,
including Presidio, Azure, Lakera, Bedrock, etc.
Discovery:
- Database investigation revealed the issue affects multiple guardrail types
- Found 4 affected guardrails in staging: 3 Presidio + 1 Azure
- All had default_action: 'Deny' causing the same validation failures
- The initial fix only covered ToolPermissionGuardrailConfigModel
Root Cause (Deeper):
- LitellmParams inherits from 13+ different guardrail config models
- Models use ConfigDict(extra="allow") allowing any field to be set
- Users can set default_action/on_disallowed_action on ANY guardrail type
- Only ToolPermissionGuardrailConfigModel was validating these fields
Solution:
- Added field validators to LitellmParams class (parent of all guardrails)
- Validators run for ALL guardrail types: Presidio, Azure, Bedrock, Lakera, etc.
- Added comprehensive tests covering multiple guardrail types
Changes:
- litellm/types/guardrails.py:
* Added @field_validator for default_action in LitellmParams
* Added @field_validator for on_disallowed_action in LitellmParams
* Added normalization in LitellmParams.__init__ as backup
* Imported field_validator from pydantic
- tests/test_litellm/types/test_guardrails_case_normalization.py:
* New test file with 7 tests covering multiple guardrail types
* Tests verify Presidio, Azure, Tool Permission, Lakera, Bedrock
* All tests passing
Impact:
- Previous fix: Only tool_permission guardrails protected
- This fix: ALL guardrail types now protected (13+ types)
- Handles both new writes and existing database records
- Tested against actual database with Presidio/Azure guardrails
Testing:
- 7 new cross-guardrail tests (all passing)
- 27 existing tool_permission tests (all passing)
- Verified fix works for real database records
This fixes a critical issue where capitalized values in tool_permission guardrail
configurations (e.g., "Deny" instead of "deny") caused Pydantic validation errors
during proxy startup, leading to repeated initialization failures and latency issues.
Problem:
- Users could save guardrails with capitalized values through UI/API
- Data was written to database without validation (e.g., default_action: "Deny")
- On proxy startup, loading from DB triggered strict Pydantic validation
- ValidationError caused guardrail initialization to fail in a retry loop
- This resulted in startup delays and repeated error logging
Root Cause:
- Write path had no case normalization
- Read path enforced strict lowercase Literal validation
- Asymmetry between write and read caused latent data corruption
Solution:
Added field validators to normalize case before Pydantic validation:
1. ToolPermissionRule.decision ("allow"/"deny")
- Normalizes decision field in rules array
2. ToolPermissionGuardrailConfigModel.default_action ("allow"/"deny")
- Normalizes default fallback action
3. ToolPermissionGuardrailConfigModel.on_disallowed_action ("block"/"rewrite")
- Normalizes disallowed tool behavior
4. ToolPermissionGuardrail.__init__ normalization
- Defensive normalization for direct instantiation
- Ensures normalization regardless of code path
Impact:
- Prevents validation errors during guardrail initialization
- Eliminates startup retry loops and latency issues
- Handles existing database records with capitalized values
- Accepts case-insensitive input from all sources (UI, API, direct calls)
- Fully backward compatible with existing lowercase configurations
Testing:
- Added 3 comprehensive tests for case-insensitive handling
- All 27 existing tests still pass
- Tests verify normalization across all affected fields
Files Changed:
- litellm/types/proxy/guardrails/guardrail_hooks/tool_permission.py
Added @field_validator decorators for case normalization
- litellm/proxy/guardrails/guardrail_hooks/tool_permission.py
Added runtime normalization in __init__ method
- tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_permission.py
Added case-insensitive validation tests
* refactor: migrate utils.py lazy imports to registry pattern
- Refactored utils.py __getattr__ to use cached registry pattern (similar to __init__.py)
- Added UTILS_MODULE_NAMES tuple and _UTILS_MODULE_IMPORT_MAP to _lazy_imports_registry.py
- Added _get_utils_globals() helper function to _lazy_imports.py
- Added _lazy_import_utils_module() handler function for utils module lazy imports
- Updated _get_lazy_import_registry() to include utils module lazy imports
- Removed redundant _get_utils_globals() from utils.py (now in _lazy_imports.py)
- Added comprehensive tests for utils module lazy imports in test_lazy_imports.py
This refactoring:
- Reduces code duplication (from 670+ lines to ~10 lines in __getattr__)
- Improves maintainability (new lazy imports just need registry entry)
- Maintains consistency with __init__.py lazy import pattern
- All existing functionality preserved and tested
* Fix NameError: get_coroutine_checker not defined in check_coroutine function
* Fix lazy loading for get_coroutine_checker in function_setup and check_coroutine
- Add lazy loading for get_coroutine_checker at start of function_setup to ensure all calls use lazy-loaded version
- Fix check_coroutine function to use lazy loading pattern via getattr
- All direct calls to get_coroutine_checker() now properly use lazy import mechanism
- Added DatadogLLMObsInitParams to TYPES_NAMES in _lazy_imports_registry.py
- Added import map entry for DatadogLLMObsInitParams in _TYPES_IMPORT_MAP
- Moved DatadogLLMObsInitParams import from module level to TYPE_CHECKING block in __init__.py
- Follows existing lazy import patterns for type classes
- Automatically tested by existing test_types_lazy_imports() function
- Keep **kwargs approach (no exec()) for security
- Integrate path traversal validation from main branch
- Add URL encoding for path parameters
- Merge both test suites (edge cases + security tests)
- All 14 tests passing
