9d5bfc127e
* config reference doc autogen * improvements * cleanup; still ugly but working * reformat * remove autogen config ref from git * factor out validations * rewrite * rewrite * cleanup * progress * progress * progress * lint and minifying somewhat * remove unneeded * coderabbit * coderabbit * update preview-docs workflow triggers * installing with deps * coderabbit * update refs * overwrote file accidentally
753 lines
29 KiB
Python
753 lines
29 KiB
Python
# type: ignore
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"""
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Quarto documentation generation from Pydantic models. Uses Pydantic model source code
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to automatically group fields, including inherited fields from parent classes.
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"""
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import ast
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import inspect
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import textwrap
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import types
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import typing
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from typing import Any, FrozenSet, Type, Union
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from pydantic import BaseModel
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from axolotl.utils.schemas.config import AxolotlInputConfig
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class QuartoGenerator:
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"""Generate Quarto documentation from Pydantic models."""
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def __init__(self):
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self._class_fields_cache = {}
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self._inheritance_map_cache = {}
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self._nested_models_cache = {}
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def _get_direct_fields(self, cls: Type[BaseModel]) -> FrozenSet[str]:
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"""Get fields defined directly in a single class (not inherited)."""
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if cls in self._class_fields_cache:
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return self._class_fields_cache[cls]
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fields = set()
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# Get annotated fields
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if hasattr(cls, "__annotations__"):
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fields.update(cls.__annotations__.keys())
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# Filter out private/special methods
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fields = {f for f in fields if not f.startswith("_")}
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result = frozenset(fields)
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self._class_fields_cache[cls] = result
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return result
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def _is_pydantic_model(self, type_obj) -> bool:
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"""Check if a type is a Pydantic BaseModel."""
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return inspect.isclass(type_obj) and issubclass(type_obj, BaseModel)
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# pylint: disable=too-many-return-statements
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def _extract_nested_type(self, field_type) -> Any:
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"""Extract the actual type from complex type annotations."""
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# Handle Annotated types (Python 3.9+)
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if hasattr(typing, "get_origin") and hasattr(typing, "get_args"):
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origin = typing.get_origin(field_type)
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args = typing.get_args(field_type)
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if origin is not None:
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# Handle Annotated[SomeType, ...] - extract the first argument
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if hasattr(typing, "Annotated") and origin is typing.Annotated:
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if args:
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return self._extract_nested_type(
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args[0]
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) # Recursively process the actual type
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# Handle list[SomeType], List[SomeType], etc.
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elif origin in (list, typing.List):
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if args:
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return self._extract_nested_type(
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args[0]
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) # Extract element type
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# Handle Union types (including | syntax)
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elif origin is typing.Union:
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# Get non-None types from the Union
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non_none_types = [arg for arg in args if arg is not type(None)]
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if len(non_none_types) >= 1:
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# Prioritize Pydantic models over primitive types
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pydantic_models = [
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arg
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for arg in non_none_types
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if self._is_pydantic_model(arg)
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]
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if pydantic_models:
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# Return the first Pydantic model found
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return self._extract_nested_type(pydantic_models[0])
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# No Pydantic models, return the first non-None type
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return self._extract_nested_type(non_none_types[0])
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# Handle new Python 3.10+ union syntax (PeftConfig | None)
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if hasattr(field_type, "__class__") and field_type.__class__ is types.UnionType:
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# Get non-None types from the Union
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non_none_types = [
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arg for arg in field_type.__args__ if arg is not type(None)
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]
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if len(non_none_types) >= 1:
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# Prioritize Pydantic models over primitive types
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pydantic_models = [
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arg for arg in non_none_types if self._is_pydantic_model(arg)
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]
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if pydantic_models:
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return self._extract_nested_type(pydantic_models[0])
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return self._extract_nested_type(non_none_types[0])
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# Handle old typing.Union syntax (fallback)
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if hasattr(field_type, "__origin__"):
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if field_type.__origin__ is Union:
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# Get non-None types from the Union
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non_none_types = [
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arg for arg in field_type.__args__ if arg is not type(None)
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]
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if len(non_none_types) >= 1:
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# Prioritize Pydantic models over primitive types
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pydantic_models = [
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arg for arg in non_none_types if self._is_pydantic_model(arg)
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]
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if pydantic_models:
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return self._extract_nested_type(pydantic_models[0])
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return self._extract_nested_type(non_none_types[0])
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# Handle other generic types like dict[str, Any], etc.
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elif hasattr(field_type, "__args__"):
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return field_type
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return field_type
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# pylint: disable=too-many-return-statements
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def _extract_all_pydantic_models_from_type(
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self, field_type
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) -> list[type[BaseModel]]:
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"""Extract all Pydantic models from a type annotation, including from Unions."""
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models = []
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if field_type is None:
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return models
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# Handle Annotated types
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if hasattr(typing, "get_origin") and hasattr(typing, "get_args"):
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origin = typing.get_origin(field_type)
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args = typing.get_args(field_type)
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if origin is not None:
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# Handle Annotated[SomeType, ...] - extract from the first argument
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if hasattr(typing, "Annotated") and origin is typing.Annotated:
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if args:
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models.extend(
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self._extract_all_pydantic_models_from_type(args[0])
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)
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return models
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# Handle list[SomeType], List[SomeType], etc.
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if origin in (list, typing.List):
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if args:
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models.extend(
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self._extract_all_pydantic_models_from_type(args[0])
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)
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return models
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# Handle Union types
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if origin is typing.Union:
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for arg in args:
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if arg is not type(None): # Skip None type
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models.extend(
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self._extract_all_pydantic_models_from_type(arg)
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)
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return models
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# Handle new Python 3.10+ union syntax
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if hasattr(field_type, "__class__") and field_type.__class__ is types.UnionType:
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for arg in field_type.__args__:
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if arg is not type(None): # Skip None type
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models.extend(self._extract_all_pydantic_models_from_type(arg))
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return models
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# Handle old typing.Union syntax (fallback)
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if hasattr(field_type, "__origin__") and field_type.__origin__ is Union:
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for arg in field_type.__args__:
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if arg is not type(None): # Skip None type
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models.extend(self._extract_all_pydantic_models_from_type(arg))
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return models
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# Check if this type itself is a Pydantic model
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if self._is_pydantic_model(field_type):
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models.append(field_type)
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return models
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def _get_nested_models(
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self, model_class: type[BaseModel], visited=None
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) -> dict[str, type[BaseModel]]:
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"""Get all nested Pydantic models from a model class."""
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if visited is None:
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visited = set()
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# Avoid infinite recursion
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if model_class in visited:
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return {}
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if model_class in self._nested_models_cache:
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return self._nested_models_cache[model_class]
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visited.add(model_class)
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nested_models = {}
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# Check all fields in the model
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for field_info in model_class.model_fields.values():
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field_type = self._extract_nested_type(field_info.annotation)
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if self._is_pydantic_model(field_type):
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nested_models[field_type.__name__] = field_type
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# Recursively get nested models from this nested model
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deeper_nested = self._get_nested_models(field_type, visited.copy())
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nested_models.update(deeper_nested)
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self._nested_models_cache[model_class] = nested_models
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return nested_models
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def _build_inheritance_map(self, child_class: Type[BaseModel]):
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"""Build inheritance map for a class and all its parents."""
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if child_class in self._inheritance_map_cache:
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return self._inheritance_map_cache[child_class]
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inheritance_map = {}
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# Get MRO and filter out BaseModel and object
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mro_classes = [
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cls
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for cls in child_class.__mro__
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if cls not in (BaseModel, object) and hasattr(cls, "__annotations__")
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]
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# Process each class in the MRO
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for cls in mro_classes:
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inheritance_map[cls] = self._get_direct_fields(cls)
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self._inheritance_map_cache[child_class] = inheritance_map
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return inheritance_map
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def _wrap_comment(self, text: str, width: int = 88) -> list[str]:
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"""Wrap a comment to specified width, accounting for '# ' prefix."""
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if not text.strip():
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return ["#"]
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# Account for "# " prefix (2 characters)
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content_width = width - 2
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wrapped_lines = textwrap.wrap(text, width=content_width)
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return [f"# {line}" for line in wrapped_lines]
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def _extract_type_from_source(
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self, model_class: type[BaseModel], field_name: str
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) -> str:
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"""Extract the actual type annotation text from source code, checking inheritance chain."""
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# Use inheritance map to check classes efficiently
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inheritance_map = self._build_inheritance_map(model_class)
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# Check classes in MRO order
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for cls in model_class.__mro__:
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if cls in inheritance_map and field_name in inheritance_map[cls]:
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type_annotation = self._get_type_from_class_source(cls, field_name)
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if type_annotation != "unknown":
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return type_annotation
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return "unknown"
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def _get_type_from_class_source(self, class_obj: type, field_name: str) -> str:
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"""Extract type annotation from a specific class's source code."""
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try:
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source = inspect.getsource(class_obj)
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tree = ast.parse(source)
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except (OSError, TypeError):
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return "unknown"
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# Find the class definition
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for node in tree.body:
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if isinstance(node, ast.ClassDef) and node.name == class_obj.__name__:
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# Find the field assignment
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for body_node in node.body:
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if isinstance(body_node, ast.AnnAssign) and isinstance(
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body_node.target, ast.Name
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):
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if body_node.target.id == field_name and body_node.annotation:
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return ast.unparse(body_node.annotation)
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break
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return "unknown"
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def _extract_field_groups_from_all_classes(
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self, model_class: type[BaseModel]
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) -> list[dict]:
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"""Extract field groups from all classes in the inheritance hierarchy."""
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all_groups = []
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inheritance_map = self._build_inheritance_map(model_class)
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# Get all Pydantic base classes in MRO order (most specific first)
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# This puts AxolotlInputConfig fields first, then parent class fields
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pydantic_classes = [
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cls
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for cls in model_class.__mro__
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if cls in inheritance_map and inheritance_map[cls]
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]
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# Extract groups from each class
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for cls in pydantic_classes:
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class_groups = self._extract_field_groups_from_source(cls)
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for group in class_groups:
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all_groups.append(group)
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# If no groups found, create a default grouping by class
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if not all_groups:
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for cls in pydantic_classes:
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fields_in_class = inheritance_map[cls]
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if fields_in_class:
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all_groups.append(
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{
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"fields": list(fields_in_class),
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}
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)
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return all_groups
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# pylint: disable=too-many-return-statements
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def _extract_field_groups_from_source(
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self, model_class: type[BaseModel]
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) -> list[dict]:
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"""Extract field groups from source code based on blank lines and comments."""
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try:
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source = inspect.getsource(model_class)
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tree = ast.parse(source)
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except (OSError, TypeError):
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# Fallback if we can't get source code
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fields_in_class = self._get_direct_fields(model_class)
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if fields_in_class:
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return [
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{
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"fields": list(fields_in_class),
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}
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]
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return []
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groups = []
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current_group_fields = []
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current_group_comment = None
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# Find the class definition
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class_node = None
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for node in ast.walk(tree):
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if isinstance(node, ast.ClassDef) and node.name == model_class.__name__:
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class_node = node
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break
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if not class_node:
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fields_in_class = self._get_direct_fields(model_class)
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if fields_in_class:
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return [
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{
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"fields": list(fields_in_class),
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}
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]
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return []
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# Parse the source lines to detect groupings
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source_lines = source.split("\n")
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# Get fields that are actually defined in this specific class
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fields_in_class = self._get_direct_fields(model_class)
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# Find assignments that correspond to model fields for THIS class only
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field_assignments = []
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for node in class_node.body:
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if isinstance(node, ast.AnnAssign) and isinstance(node.target, ast.Name):
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field_name = node.target.id
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if field_name in fields_in_class:
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field_assignments.append(
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{
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"name": field_name,
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"lineno": node.lineno,
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"end_lineno": getattr(node, "end_lineno", node.lineno),
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}
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)
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if not field_assignments:
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if fields_in_class:
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return [
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{
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"fields": list(fields_in_class),
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}
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]
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return []
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# Sort by line number
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field_assignments.sort(key=lambda x: x["lineno"])
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# Group fields based on blank lines and comments
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for i, field_info in enumerate(field_assignments):
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field_name = field_info["name"]
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current_line = field_info["lineno"]
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# Check if this starts a new group (blank line before or significant gap)
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is_new_group = False
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if i == 0:
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is_new_group = True
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else:
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prev_end_line = field_assignments[i - 1]["end_lineno"]
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# Check for blank lines or comments between fields
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lines_between = source_lines[prev_end_line : current_line - 1]
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has_blank_line = any(line.strip() == "" for line in lines_between)
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has_comment = any(
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line.strip().startswith("#") for line in lines_between
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)
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# Start new group if there's a blank line or comment, or significant gap
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if has_blank_line or has_comment or (current_line - prev_end_line > 3):
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is_new_group = True
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if is_new_group and current_group_fields:
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# Save the previous group
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groups.append(
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{
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"fields": current_group_fields.copy(),
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"description": current_group_comment,
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}
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)
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current_group_fields = []
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current_group_comment = None
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current_group_fields.append(field_name)
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# Add the final group
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if current_group_fields:
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groups.append(
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{
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"fields": current_group_fields,
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"description": current_group_comment,
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}
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)
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return groups
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def _generate_field_documentation(
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self,
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model_class: type[BaseModel],
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field_name: str,
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field_info: dict,
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field_type_str: str,
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is_required: bool,
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indent_level: int = 0,
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visited_models: set = None,
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) -> list[str]:
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"""Generate documentation for a single field, expanding nested models inline."""
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if visited_models is None:
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visited_models = set()
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lines = []
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indent = " " * indent_level
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# Get the actual field type for nested model detection
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if field_name in model_class.model_fields:
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pydantic_field_info = model_class.model_fields[field_name]
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actual_field_type = pydantic_field_info.annotation
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else:
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actual_field_type = None
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# Add description comment if available
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description = field_info.get("description", "")
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if description:
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wrapped_lines = self._wrap_comment(description, width=88 - len(indent))
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for line in wrapped_lines:
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lines.append(f"{indent}{line}")
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# Extract nested Pydantic models from the type annotation
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nested_models = self._extract_all_pydantic_models_from_type(actual_field_type)
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# Filter out already visited models to prevent infinite recursion
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expandable_models = [
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model for model in nested_models if model not in visited_models
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]
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if expandable_models:
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# This field contains Pydantic models that can be expanded
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# Show the field with its full type annotation
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field_line = f"{indent}{field_name}: {field_type_str}"
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if field_info.get("default") is not None:
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field_line += f" = {field_info['default']}"
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if is_required:
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field_line += " (required)"
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lines.append(field_line)
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# Add to visited to prevent infinite recursion
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new_visited = visited_models.copy()
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new_visited.update(expandable_models)
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# Expand each nested Pydantic model
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for i, nested_model in enumerate(expandable_models):
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if i > 0:
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lines.append("\n")
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lines.append(f"{indent} # For {nested_model.__name__}:")
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# Get nested model schema
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try:
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nested_schema = nested_model.model_json_schema()
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nested_properties = nested_schema.get("properties", {})
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nested_required = nested_schema.get("required", [])
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except Exception: # pylint: disable=broad-exception-caught
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# Fallback: use model fields directly
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nested_properties = {}
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nested_required = []
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for (
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nested_field_name,
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nested_field_info,
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) in nested_model.model_fields.items():
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nested_description = ""
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if (
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hasattr(nested_field_info, "json_schema_extra")
|
|
and nested_field_info.json_schema_extra
|
|
):
|
|
nested_description = (
|
|
nested_field_info.json_schema_extra.get(
|
|
"description", ""
|
|
)
|
|
)
|
|
elif (
|
|
hasattr(nested_field_info, "description")
|
|
and nested_field_info.description
|
|
):
|
|
nested_description = nested_field_info.description
|
|
|
|
nested_default_val = None
|
|
if (
|
|
hasattr(nested_field_info, "default")
|
|
and nested_field_info.default is not None
|
|
):
|
|
if str(nested_field_info.default) != "PydanticUndefined":
|
|
nested_default_val = nested_field_info.default
|
|
|
|
nested_properties[nested_field_name] = {
|
|
"type": "unknown",
|
|
"description": nested_description,
|
|
"default": nested_default_val,
|
|
}
|
|
|
|
if nested_field_info.is_required():
|
|
nested_required.append(nested_field_name)
|
|
|
|
# Get field groups for the nested model
|
|
nested_field_groups = self._extract_field_groups_from_all_classes(
|
|
nested_model
|
|
)
|
|
|
|
# Generate nested fields with increased indentation
|
|
for i, group in enumerate(nested_field_groups):
|
|
if not group["fields"]:
|
|
continue
|
|
|
|
# Add blank line between groups (except before first group)
|
|
if i > 0:
|
|
lines.append("")
|
|
|
|
# Process nested fields
|
|
for nested_field_name in group["fields"]:
|
|
if nested_field_name not in nested_properties:
|
|
continue
|
|
|
|
nested_field_info = nested_properties[nested_field_name]
|
|
nested_field_type = self._extract_type_from_source(
|
|
nested_model, nested_field_name
|
|
)
|
|
nested_is_required = nested_field_name in nested_required
|
|
|
|
# Recursively generate documentation for nested field
|
|
nested_lines = self._generate_field_documentation(
|
|
nested_model,
|
|
nested_field_name,
|
|
nested_field_info,
|
|
nested_field_type,
|
|
nested_is_required,
|
|
indent_level + 1,
|
|
new_visited,
|
|
)
|
|
lines.extend(nested_lines)
|
|
else:
|
|
# Regular field (no expandable nested models)
|
|
field_line = f"{indent}{field_name}: {field_type_str}"
|
|
if field_info.get("default") is not None:
|
|
field_line += f" = {field_info['default']}"
|
|
if is_required:
|
|
field_line += " (required)"
|
|
lines.append(field_line)
|
|
|
|
return lines
|
|
|
|
def generate_qmd(
|
|
self,
|
|
model_class: type[BaseModel],
|
|
title: str | None = None,
|
|
expand_nested: bool = True,
|
|
) -> str:
|
|
"""Auto-generate config reference documentation including inherited fields."""
|
|
|
|
if title is None:
|
|
title = f"{model_class.__name__} Reference"
|
|
|
|
# Try to get JSON schema, with fallback for serialization issues
|
|
try:
|
|
schema = model_class.model_json_schema()
|
|
properties = schema.get("properties", {})
|
|
required = schema.get("required", [])
|
|
except Exception as e: # pylint: disable=broad-exception-caught
|
|
print(
|
|
f"Warning: Could not generate JSON schema ({e}). Using model fields instead."
|
|
)
|
|
# Fallback: use model fields directly
|
|
properties = {}
|
|
required = []
|
|
for field_name, field_info in model_class.model_fields.items():
|
|
# Extract description from json_schema_extra or field info
|
|
description = ""
|
|
if (
|
|
hasattr(field_info, "json_schema_extra")
|
|
and field_info.json_schema_extra
|
|
):
|
|
description = field_info.json_schema_extra.get("description", "")
|
|
elif hasattr(field_info, "description") and field_info.description:
|
|
description = field_info.description
|
|
|
|
# Get default value
|
|
default_val = None
|
|
if hasattr(field_info, "default") and field_info.default is not None:
|
|
# Handle special Pydantic default markers
|
|
if str(field_info.default) != "PydanticUndefined":
|
|
default_val = field_info.default
|
|
|
|
properties[field_name] = {
|
|
"type": "unknown",
|
|
"description": description,
|
|
"default": default_val,
|
|
}
|
|
|
|
if field_info.is_required():
|
|
required.append(field_name)
|
|
|
|
# Extract field groups from all classes in inheritance hierarchy
|
|
field_groups = self._extract_field_groups_from_all_classes(model_class)
|
|
|
|
# Start building QMD content
|
|
qmd_lines = [
|
|
"---",
|
|
f"title: {title}",
|
|
"description: A complete list of all configuration options.",
|
|
"---",
|
|
"",
|
|
]
|
|
|
|
# Generate one big code block with all fields (inline nested expansion)
|
|
qmd_lines.append("```yaml")
|
|
|
|
for i, group in enumerate(field_groups):
|
|
if not group["fields"]:
|
|
continue
|
|
|
|
# Add blank line between groups (except before first group)
|
|
if i > 0:
|
|
qmd_lines.append("")
|
|
|
|
# Process fields in the order they appear in source
|
|
for field_name in group["fields"]:
|
|
if field_name not in properties:
|
|
continue
|
|
|
|
field_info = properties[field_name]
|
|
field_type = self._extract_type_from_source(model_class, field_name)
|
|
is_required = field_name in required
|
|
|
|
if expand_nested:
|
|
# Check if this field has nested models
|
|
if field_name in model_class.model_fields:
|
|
pydantic_field_info = model_class.model_fields[field_name]
|
|
nested_models = self._extract_all_pydantic_models_from_type(
|
|
pydantic_field_info.annotation
|
|
)
|
|
has_nested = bool(nested_models)
|
|
else:
|
|
has_nested = False
|
|
|
|
# Add blank line before nested config
|
|
if has_nested:
|
|
qmd_lines.append("")
|
|
|
|
# Use the new inline generation method
|
|
field_lines = self._generate_field_documentation(
|
|
model_class,
|
|
field_name,
|
|
field_info,
|
|
field_type,
|
|
is_required,
|
|
indent_level=0,
|
|
visited_models=set(),
|
|
)
|
|
qmd_lines.extend(field_lines)
|
|
|
|
# Add blank line after nested config
|
|
if has_nested:
|
|
qmd_lines.append("")
|
|
else:
|
|
# Original simple approach
|
|
description = field_info.get("description", "")
|
|
default = field_info.get("default")
|
|
|
|
# Add wrapped comment for description
|
|
if description:
|
|
wrapped_lines = self._wrap_comment(description)
|
|
qmd_lines.extend(wrapped_lines)
|
|
|
|
line = f"{field_name}: {field_type}"
|
|
if default is not None:
|
|
line += f" = {default}"
|
|
if is_required:
|
|
line += " (required)"
|
|
qmd_lines.append(line)
|
|
|
|
qmd_lines.append("```")
|
|
|
|
# Join all lines and clean up any double newlines
|
|
content = "\n".join(qmd_lines)
|
|
|
|
# Replace multiple consecutive newlines with just two newlines (one blank line)
|
|
import re
|
|
|
|
content = re.sub(r"\n{3,}", "\n\n", content)
|
|
|
|
# Ensure single newline at the very end
|
|
content = content.rstrip("\n") + "\n"
|
|
|
|
return content
|
|
|
|
|
|
def main():
|
|
generator = QuartoGenerator()
|
|
|
|
print("Generating config reference content...")
|
|
qmd_content = generator.generate_qmd(AxolotlInputConfig, "Config Reference", True)
|
|
|
|
print("Writing to file...")
|
|
with open("docs/config-reference.qmd", "w", encoding="utf-8") as f:
|
|
f.write(qmd_content)
|
|
print("Done!")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|