refactor: migrate config system to Pydantic dataclasses
- Replace hand-rolled BaseConfig (from_dict/to_dict/_coerce/_unwrap_optional) with pydantic.dataclasses
- from_dict now uses cls(**d), to_dict uses dataclasses.asdict + json.dumps filter
- TrainConfig: required fields are now truly required (no default=None), delete manual validate()/__post_init__
- Remove dead required() helper and metadata={'help': ...} annotations
- Fix gradient_checkpointing_modules type from List[str] to List[type]
- Add pydantic>=2.0 as direct dependency in pyproject.toml
- Add numpy-style Parameters docstrings to all config classes
- Enable use_attribute_docstrings in BaseConfig for schema generation
- LoRAConfig also migrated to pydantic dataclass
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@@ -22,13 +22,10 @@ class BaseToolParser(ABC):
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Maintains streaming state internally so that each call to :meth:`feed`
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can diff against previously emitted content.
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Parameters
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----------
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tools : list of dict, optional
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Tool definitions from the request.
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tool_choice : str
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``"auto"`` / ``"required"`` / ``"none"`` or a named tool choice
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dict.
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Args:
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tools (list of dict, optional): Tool definitions from the request.
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tool_choice (str): ``"auto"`` / ``"required"`` / ``"none"`` or a named
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tool choice dict.
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"""
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def __init__(self, tools: Optional[List[Dict]] = None, tool_choice: str = "auto"):
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@@ -51,14 +48,12 @@ class BaseToolParser(ABC):
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Returns an empty list when nothing new should be emitted.
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Parameters
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----------
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body : str
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The complete accumulated generated text so far.
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current_token_ids : list of int, optional
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All token IDs decoded into *body* (cumulative).
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delta_token_ids : list of int, optional
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Only the token IDs for this chunk.
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Args:
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body (str): The complete accumulated generated text so far.
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current_token_ids (list of int, optional): All token IDs decoded
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into *body* (cumulative).
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delta_token_ids (list of int, optional): Only the token IDs for
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this chunk.
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"""
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@abstractmethod
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