📄 CodeRabbit inference engine (.cursor/rules/nat-test-llm.mdc)

**/*.{py,yaml,yml}: Configure response_seq as a list of strings; values cycle per call, and [] yields an empty string.
Configure delay_ms to inject per-call artificial latency in milliseconds for nat_test_llm.

Files:

• packages/nvidia_nat_adk/src/nat/plugins/adk/llm.py
• src/nat/llm/register.py
• src/nat/llm/litellm_llm.py

📄 CodeRabbit inference engine (.cursor/rules/nat-test-llm.mdc)

**/*.py: Programmatic use: create TestLLMConfig(response_seq=[...], delay_ms=...), add with builder.add_llm("", cfg).
When retrieving the test LLM wrapper, use builder.get_llm(name, wrapper_type=LLMFrameworkEnum.) and call the framework’s method (e.g., ainvoke, achat, call).

**/*.py: In code comments/identifiers use NAT abbreviations as specified: nat for API namespace/CLI, nvidia-nat for package name, NAT for env var prefixes; do not use these abbreviations in documentation
Follow PEP 20 and PEP 8; run yapf with column_limit=120; use 4-space indentation; end files with a single trailing newline
Run ruff check --fix as linter (not formatter) using pyproject.toml config; fix warnings unless explicitly ignored
Respect naming: snake_case for functions/variables, PascalCase for classes, UPPER_CASE for constants
Treat pyright warnings as errors during development
Exception handling: use bare raise to re-raise; log with logger.error() when re-raising to avoid duplicate stack traces; use logger.exception() when catching without re-raising
Provide Google-style docstrings for every public module, class, function, and CLI command; first line concise and ending with a period; surround code entities with backticks
Validate and sanitize all user input, especially in web or CLI interfaces
Prefer httpx with SSL verification enabled by default and follow OWASP Top-10 recommendations
Use async/await for I/O-bound work; profile CPU-heavy paths with cProfile or mprof before optimizing; cache expensive computations with functools.lru_cache or external cache; leverage NumPy vectorized operations when beneficial

Files:

• packages/nvidia_nat_adk/src/nat/plugins/adk/llm.py
• src/nat/llm/register.py
• src/nat/llm/litellm_llm.py

📄 CodeRabbit inference engine (.cursor/rules/general.mdc)

Importable Python code inside packages must live under packages//src/

Files:

• packages/nvidia_nat_adk/src/nat/plugins/adk/llm.py

📄 CodeRabbit inference engine (.cursor/rules/general.mdc)

All public APIs must have Python 3.11+ type hints on parameters and return values; prefer typing/collections.abc abstractions; use typing.Annotated when useful

Files:

• packages/nvidia_nat_adk/src/nat/plugins/adk/llm.py
• src/nat/llm/register.py
• src/nat/llm/litellm_llm.py

⚙️ CodeRabbit configuration file

**/*: # Code Review Instructions

• Ensure the code follows best practices and coding standards. - For Python code, follow
  PEP 20 and
  PEP 8 for style guidelines.
• Check for security vulnerabilities and potential issues. - Python methods should use type hints for all parameters and return values.
  Example:

  def my_function(param1: int, param2: str) -> bool:
      pass

• For Python exception handling, ensure proper stack trace preservation:
  • When re-raising exceptions: use bare raise statements to maintain the original stack trace,
    and use logger.error() (not logger.exception()) to avoid duplicate stack trace output.
  • When catching and logging exceptions without re-raising: always use logger.exception()
    to capture the full stack trace information.

Documentation Review Instructions - Verify that documentation and comments are clear and comprehensive. - Verify that the documentation doesn't contain any TODOs, FIXMEs or placeholder text like "lorem ipsum". - Verify that the documentation doesn't contain any offensive or outdated terms. - Verify that documentation and comments are free of spelling mistakes, ensure the documentation doesn't contain any

words listed in the ci/vale/styles/config/vocabularies/nat/reject.txt file, words that might appear to be
spelling mistakes but are listed in the ci/vale/styles/config/vocabularies/nat/accept.txt file are OK.

Misc. - All code (except .mdc files that contain Cursor rules) should be licensed under the Apache License 2.0,

and should contain an Apache License 2.0 header comment at the top of each file.

• Confirm that copyright years are up-to date whenever a file is changed.

Files:

• packages/nvidia_nat_adk/src/nat/plugins/adk/llm.py
• src/nat/llm/register.py
• src/nat/llm/litellm_llm.py

⚙️ CodeRabbit configuration file

packages/**/*: - This directory contains optional plugin packages for the toolkit, each should contain a pyproject.toml file. - The pyproject.toml file should declare a dependency on nvidia-nat or another package with a name starting
with nvidia-nat-. This dependency should be declared using ~=<version>, and the version should be a two
digit version (ex: ~=1.0).

• Not all packages contain Python code, if they do they should also contain their own set of tests, in a
  tests/ directory at the same level as the pyproject.toml file.

Files:

• packages/nvidia_nat_adk/src/nat/plugins/adk/llm.py

📄 CodeRabbit inference engine (.cursor/rules/general.mdc)

All importable Python code must live under src/ (or packages//src/)

Files:

• src/nat/llm/register.py
• src/nat/llm/litellm_llm.py

📄 CodeRabbit inference engine (.cursor/rules/general.mdc)

Changes in src/nat should prioritize backward compatibility

Files:

• src/nat/llm/register.py
• src/nat/llm/litellm_llm.py

⚙️ CodeRabbit configuration file

This directory contains the core functionality of the toolkit. Changes should prioritize backward compatibility.

Files:

• src/nat/llm/register.py
• src/nat/llm/litellm_llm.py

src/nat/llm/litellm_llm.py (1)

• LiteLlmModelConfig (32-52)

src/nat/builder/framework_enum.py (1)

• LLMFrameworkEnum (19-25)

src/nat/builder/builder.py (1)

• Builder (68-290)

src/nat/builder/builder.py (1)

• Builder (68-290)

src/nat/data_models/temperature_mixin.py (1)

• TemperatureMixin (25-44)

src/nat/data_models/thinking_mixin.py (1)

• ThinkingMixin (29-86)

src/nat/data_models/top_p_mixin.py (1)

• TopPMixin (25-44)