langchain.agents.output_parsers.tools.ToolAgentAction

class langchain.agents.output_parsers.tools.ToolAgentAction[source]

Bases: AgentActionMessageLog

覆盖init以支持通过位置进行实例化，以实现向后兼容。

param log: str [Required]

关于该操作的额外日志信息。 这个日志可以用几种方式。首先，它可以用于审计LLM预测导致这个（工具，工具输入）的确切情况。其次，它可以在未来的迭代中显示LLM之前的想法。当（工具，工具输入）不包含关于LLM预测的完整信息时，这是有用的（例如，在工具/工具输入之前的任何“想法”）。

param message_log: Sequence[BaseMessage] [Required]

类似于日志，这可以用来传递关于LLM预测的确切消息的额外信息，在解析出(tool, tool_input)之前。如果(tool, tool_input)不能完全重现LLM预测，并且您需要该LLM预测（用于未来的代理迭代），则这是非常有用的。与`log`相比，当基础LLM是ChatModel（因此返回消息而不是字符串）时，这是有用的。

param tool: str [Required]

要执行的工具的名称。

param tool_call_id: str [Required]

工具调用，这条消息是在回应什么。

param tool_input: Union[str, dict] [Required]

工具的输入。

param type: Literal['AgentActionMessageLog'] = 'AgentActionMessageLog'
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Parameters

  • _fields_set (Optional[SetStr]) –

  • values (Any) –

Return type

Model

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include

  • update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep (bool) – set to True to make a deep copy of the model

  • self (Model) –

Returns

new model instance

Return type

Model

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • by_alias (bool) –

  • skip_defaults (Optional[bool]) –

  • exclude_unset (bool) –

  • exclude_defaults (bool) –

  • exclude_none (bool) –

Return type

DictStrAny

classmethod from_orm(obj: Any) → Model
Parameters

obj (Any) –

Return type

Model

classmethod get_lc_namespace() → List[str]

获取langchain对象的命名空间。

Return type

List[str]

classmethod is_lc_serializable() → bool

返回类是否可序列化。

Return type

bool

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

Parameters

  • include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –

  • by_alias (bool) –

  • skip_defaults (Optional[bool]) –

  • exclude_unset (bool) –

  • exclude_defaults (bool) –

  • exclude_none (bool) –

  • encoder (Optional[Callable[[Any], Any]]) –

  • models_as_dict (bool) –

  • dumps_kwargs (Any) –

Return type

unicode

classmethod lc_id() → List[str]

用于序列化目的的此类的唯一标识符。

唯一标识符是一个描述对象路径的字符串列表。

Return type

List[str]

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
Parameters

  • path (Union[str, Path]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

Model

classmethod parse_obj(obj: Any) → Model
Parameters

obj (Any) –

Return type

Model

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
Parameters

  • b (Union[str, bytes]) –

  • content_type (unicode) –

  • encoding (unicode) –

  • proto (Protocol) –

  • allow_pickle (bool) –

Return type

Model

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny
Parameters

  • by_alias (bool) –

  • ref_template (unicode) –

Return type

DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode
Parameters

  • by_alias (bool) –

  • ref_template (unicode) –

  • dumps_kwargs (Any) –

Return type

unicode

to_json() → Union[SerializedConstructor, SerializedNotImplemented]
Return type

Union[SerializedConstructor, SerializedNotImplemented]

to_json_not_implemented() → SerializedNotImplemented
Return type

SerializedNotImplemented

classmethod update_forward_refs(**localns: Any) → None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

Parameters

localns (Any) –

Return type

None

classmethod validate(value: Any) → Model
Parameters

value (Any) –

Return type

Model

property lc_attributes: Dict

需要包含在序列化kwargs中的属性名称列表。

这些属性必须被构造函数接受。

property lc_secrets: Dict[str, str]

构造函数参数名称到秘钥ID的映射。

例如，

{“openai_api_key”: “OPENAI_API_KEY”}

property messages: Sequence[langchain_core.messages.base.BaseMessage]

返回与此操作对应的消息。