📄 CodeRabbit inference engine (AGENTS.md)

src/**/*.py: Use absolute imports for internal modules: from authentication import get_auth_dependency
Llama Stack imports: Use from llama_stack_client import AsyncLlamaStackClient
Check constants.py for shared constants before defining new ones
All modules must start with descriptive docstrings explaining purpose
Use logger = get_logger(__name__) from log.py for 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
Use async def for 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 @abstractmethod decorators
Follow Google Python docstring conventions with required sections: Parameters, Returns, Raises, and Attributes for classes

Files:

• src/pydantic_ai_lightspeed/llamastack/__init__.py
• src/pydantic_ai_lightspeed/__init__.py
• src/utils/pydantic_ai.py
• src/pydantic_ai_lightspeed/llamastack/_provider.py
• src/pydantic_ai_lightspeed/llamastack/_transport.py

📄 CodeRabbit inference engine (AGENTS.md)

Package __init__.py files must contain brief package descriptions

Files:

• src/pydantic_ai_lightspeed/llamastack/__init__.py
• src/pydantic_ai_lightspeed/__init__.py

📄 CodeRabbit inference engine (AGENTS.md)

tests/**/*.py: Use pytest for all unit and integration tests; do not use unittest
Use pytest.mark.asyncio marker for async tests

Files:

• tests/unit/pydantic_ai_lightspeed/llamastack/__init__.py
• tests/unit/pydantic_ai_lightspeed/__init__.py
• tests/unit/pydantic_ai_lightspeed/llamastack/test_provider.py
• tests/unit/pydantic_ai_lightspeed/llamastack/test_transport.py
• tests/unit/utils/test_pydantic_ai.py

📄 CodeRabbit inference engine (AGENTS.md)

src/**/*.py: Use absolute imports for internal modules: from authentication import get_auth_dependency
Llama Stack imports: Use from llama_stack_client import AsyncLlamaStackClient
Check constants.py for shared constants before defining new ones
All modules must start with descriptive docstrings explaining purpose
Use logger = get_logger(__name__) from log.py for 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
Use async def for 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 @abstractmethod decorators
Follow Google Python docstring conventions with required sections: Parameters, Returns, Raises, and Attributes for classes

Files:

• src/utils/pydantic_ai.py

📄 CodeRabbit inference engine (AGENTS.md)

tests/**/*.py: Use pytest for all unit and integration tests; do not use unittest
Use pytest.mark.asyncio marker for async tests

Files:

• tests/unit/utils/test_pydantic_ai.py

Learnt from: CR
Repo: lightspeed-core/lightspeed-stack PR: 0
File: AGENTS.md:0-0
Timestamp: 2026-05-06T06:57:52.173Z
Learning: Applies to src/**/*.py : Llama Stack imports: Use `from llama_stack_client import AsyncLlamaStackClient`

Applied to files:

• src/utils/pydantic_ai.py

Learnt from: asimurka
Repo: lightspeed-core/lightspeed-stack PR: 1211
File: src/models/responses.py:8-16
Timestamp: 2026-02-25T07:46:39.608Z
Learning: In the lightspeed-stack codebase, src/models/requests.py uses OpenAIResponseInputTool as Tool while src/models/responses.py uses OpenAIResponseTool as Tool. This type difference is intentional - input tools and output/response tools have different schemas in llama-stack-api.

Applied to files:

• src/utils/pydantic_ai.py

Learnt from: max-svistunov
Repo: lightspeed-core/lightspeed-stack PR: 1580
File: src/llama_stack_configuration.py:651-683
Timestamp: 2026-05-20T08:09:43.391Z
Learning: In `src/llama_stack_configuration.py`, the `apply_high_level_inference` function currently emits `provider_id: p_type` (underscore form, e.g. `sentence_transformers`) directly from the high-level type key, which collides with Llama Stack's hyphenated provider IDs (e.g. `sentence-transformers`). This is a known PoC divergence documented in the spike doc ("Findings discovered during PoC") and tracked in the implementation JIRA "Unified llama_stack.config schema + synthesizer". Decision S5 mandates that each backend-specific synthesizer translates LCORE's canonical type Literal vocabulary to the target backend's expected shape (hyphenated provider_id for Llama Stack; model-string prefixes for Pydantic AI). The PoC code will be removed before merge; the fix belongs in the implementation ticket.

Applied to files:

• src/utils/pydantic_ai.py