LCORE-1831: Implement Redaction Safety Capability in Pydantic AI#1915
LCORE-1831: Implement Redaction Safety Capability in Pydantic AI#1915arin-deloatch wants to merge 7 commits into
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WalkthroughThis pull request introduces a configurable PII redaction capability for Pydantic AI Lightspeed Core Stack. The implementation provides regex-based pattern matching and replacement logic, configuration models with compiled pattern caching, and integration with Pydantic AI's request/response lifecycle hooks. ChangesPII Redaction Capability Implementation
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anik120
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anik120
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I know this is not part of the scope of this PR, but is src/pydantic_ai... leaking implementation detail again @jrobertboos?
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| def _redact_message_parts( | ||
| parts: Sequence[Any], compiled_patterns: CompiledPatterns |
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Try to avoid Any in the whole module where possible.
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| def _redact_string_content( | ||
| text: str, compiled_patterns: CompiledPatterns | ||
| ) -> str | None: |
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Prefer using Optional in the whole module.
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Actionable comments posted: 2
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Verify each finding against current code. Fix only still-valid issues, skip the
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In `@src/pydantic_ai_lightspeed/capabilities/redaction/capability.py`:
- Line 1: Add module-level logging support by importing get_logger from log.py
and creating a logger instance at the top of the file after the module docstring
using logger = get_logger(__name__). This logger should then be used throughout
the capability module to audit PII redaction events, such as logging at debug
level when redaction rules match specific patterns and at info level for
redaction statistics and summaries. This approach aligns with coding guidelines
and provides valuable audit trails for the security-sensitive PII redaction
functionality.
- Line 5: Update all type annotations in the module to use modern pipe syntax
instead of Optional. Replace Optional[Type] with Type | None for all return type
annotations in the functions including _redact_text_content,
_redact_content_list, _redact_message_parts, and _redact_model_request. After
updating all function return types throughout the module, remove Optional from
the import statement at the top of the file since it will no longer be needed.
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src/pydantic_ai_lightspeed/capabilities/__init__.pysrc/pydantic_ai_lightspeed/capabilities/redaction/__init__.pysrc/pydantic_ai_lightspeed/capabilities/redaction/capability.pysrc/pydantic_ai_lightspeed/capabilities/redaction/config.pysrc/pydantic_ai_lightspeed/capabilities/redaction/core.pytests/unit/pydantic_ai_lightspeed/capabilities/__init__.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/__init__.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_capability.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_config.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_core.py
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📓 Path-based instructions (3)
tests/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
tests/**/*.py: Use pytest for all unit and integration tests; do not use unittest
Usepytest.mark.asynciomarker for async tests
Files:
tests/unit/pydantic_ai_lightspeed/capabilities/__init__.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/__init__.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_core.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_capability.pytests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_config.py
src/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
src/**/*.py: Use absolute imports for internal modules:from authentication import get_auth_dependency
Llama Stack imports: Usefrom llama_stack_client import AsyncLlamaStackClient
Checkconstants.pyfor shared constants before defining new ones
All modules must start with descriptive docstrings explaining purpose
Uselogger = get_logger(__name__)fromlog.pyfor module logging
All functions must have complete type annotations for parameters and return types, use modern syntax (str | int), and include descriptive docstrings
Use snake_case with descriptive, action-oriented names for functions (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying function parameters
Useasync deffor I/O operations and external API calls
Use standard log levels with clear purposes:debug()for diagnostic info,info()for program execution,warning()for unexpected events,error()for serious problems
All classes must have descriptive docstrings explaining purpose and use PascalCase with standard suffixes:Configuration,Error/Exception,Resolver,Interface
Abstract classes must use ABC with@abstractmethoddecorators
Follow Google Python docstring conventions with required sections: Parameters, Returns, Raises, and Attributes for classes
Files:
src/pydantic_ai_lightspeed/capabilities/__init__.pysrc/pydantic_ai_lightspeed/capabilities/redaction/__init__.pysrc/pydantic_ai_lightspeed/capabilities/redaction/core.pysrc/pydantic_ai_lightspeed/capabilities/redaction/config.pysrc/pydantic_ai_lightspeed/capabilities/redaction/capability.py
src/**/__init__.py
📄 CodeRabbit inference engine (AGENTS.md)
Package
__init__.pyfiles must contain brief package descriptions
Files:
src/pydantic_ai_lightspeed/capabilities/__init__.pysrc/pydantic_ai_lightspeed/capabilities/redaction/__init__.py
🔇 Additional comments (6)
src/pydantic_ai_lightspeed/capabilities/redaction/config.py (1)
14-107: LGTM!tests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_config.py (1)
1-157: LGTM!src/pydantic_ai_lightspeed/capabilities/redaction/capability.py (2)
31-258: LGTM!
261-325: LGTM!tests/unit/pydantic_ai_lightspeed/capabilities/redaction/test_capability.py (1)
1-316: LGTM!src/pydantic_ai_lightspeed/capabilities/redaction/__init__.py (1)
1-21: LGTM!
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/ok-to-test |
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I personally like this decomposition to capability, core and config modules.
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| @dataclass | ||
| class PiiRedactionCapability(AbstractCapability[Any]): |
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Use None for type argument as this corresponds to current implementation of lightspeed agent (with no dependencies). Use None as type annotation where possible.
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/ok-to-test |
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| """Configuration models for PII redaction rules.""" | |||
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IMHO this config (or rather config classes/models) should be added into src/models/config.py. At least to avoid circular dependencies, to allow us to generate documentation etc.
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Understood, it was my initial understanding that we were to keep everything pydantic_ai related separate to avoid any sorts of conflicts with the core source code.
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However, I am more than happy to make the changes necessary! Just to be thorough, it is expected that RedactionRule,RedactionConfig and RedactionResult are being moved to src/models/config.py, correct?
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Correct. This will be later part of LCORE config so it will be technically implementation agnostic.
…capability. Use Optional for nullable returns and substitute Any with UserContent, ModelRequestPart, and ModelResponsePart for type-safe message handling.
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Description
Add a regex-based PII redaction capability for pydantic-ai agents. This introduces:
core.py):redact_text()function and immutableRedactionResultmodel forsequential regex-based text substitution
config.py):RedactionRuleandRedactionConfigPydantic models withcompile-time pattern validation and per-rule/global case sensitivity controls
capability.py):PiiRedactionCapabilityintegrating with pydantic-ai'sAbstractCapabilityto redact user prompts before model requests and model response text beforereturning to the caller
Type of change
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Testing
uv run make format— passes, no reformatsuv run make verify— all linters pass (black, pylint 10/10, pyright 0 errors, ruff, pydocstyle,mypy, lint-openapi)
uv run pytest tests/unit/pydantic_ai_lightspeed/capabilities/ -v— 51/51 tests passcapability.py)Summary by CodeRabbit