langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent

class langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent

Bases: BaseSingleActionAgent

[Deprecated] 由OpenAI的功能驱动API的代理。

参数：

llm：这应该是ChatOpenAI的一个实例，具体来说是支持使用`functions`的模型。 tools：此代理可以访问的工具。 prompt：此代理的提示，应支持agent_scratchpad作为其中一个变量。要构建此提示的简便方法，请使用`OpenAIFunctionsAgent.create_prompt(…)`。

Notes

Deprecated since version 0.1.0: Use create_openai_functions_agent instead.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param llm: langchain_core.language_models.base.BaseLanguageModel [Required]

param output_parser: Type[langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser] = <class 'langchain.agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser'>

param prompt: langchain_core.prompts.base.BasePromptTemplate [Required]

param tools: Sequence[langchain_core.tools.BaseTool] [Required]

async aplan(intermediate_steps: List[Tuple[AgentAction, str]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Union[AgentAction, AgentFinish]

给定输入，决定要做什么。

参数：

intermediate_steps：LLM迄今为止所采取的步骤，

以及观察结果

**kwargs：用户输入。

返回：

指定要使用的工具的操作。

Parameters

• intermediate_steps (List[Tuple[AgentAction, str]]) –

• callbacks (Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]) –

• kwargs (Any) –

Return type

Union[AgentAction, AgentFinish]

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

classmethod create_prompt(system_message: Optional[SystemMessage] = SystemMessage(content='You are a helpful AI assistant.'), extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None) → ChatPromptTemplate

为这个代理创建提示。

参数：

system_message：用作系统消息的消息，将作为提示中的第一条消息。 extra_prompt_messages：将放置在系统消息和新的人类输入之间的提示消息。

返回：

一个传递给该代理的提示模板。

Parameters

• system_message (Optional[SystemMessage]) –

• extra_prompt_messages (Optional[List[BaseMessagePromptTemplate]]) –

Return type

ChatPromptTemplate

dict(**kwargs: Any) → Dict

返回代理的字典表示。

Parameters

kwargs (Any) –

Return type

Dict

classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None, system_message: Optional[SystemMessage] = SystemMessage(content='You are a helpful AI assistant.'), **kwargs: Any) → BaseSingleActionAgent

从LLM和工具构建一个代理。

Parameters

• llm (BaseLanguageModel) –

• tools (Sequence[BaseTool]) –

• callback_manager (Optional[BaseCallbackManager]) –

• extra_prompt_messages (Optional[List[BaseMessagePromptTemplate]]) –

• system_message (Optional[SystemMessage]) –

• kwargs (Any) –

Return type

BaseSingleActionAgent

classmethod from_orm(obj: Any) → Model

Parameters

obj (Any) –

Return type

Model

get_allowed_tools() → List[str]

获取允许的工具。

Return type

List[str]

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 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

plan(intermediate_steps: List[Tuple[AgentAction, str]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, with_functions: bool = True, **kwargs: Any) → Union[AgentAction, AgentFinish]

给定输入，决定要做什么。

参数：

intermediate_steps：LLM迄今为止所采取的步骤，以及观察结果 **kwargs：用户输入。

返回：

指定要使用的工具的操作。

Parameters

• intermediate_steps (List[Tuple[AgentAction, str]]) –

• callbacks (Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]) –

• with_functions (bool) –

• kwargs (Any) –

Return type

Union[AgentAction, AgentFinish]

return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → AgentFinish

当代理由于达到最大迭代次数而停止时返回响应。

Parameters

• early_stopping_method (str) –

• intermediate_steps (List[Tuple[AgentAction, str]]) –

• kwargs (Any) –

Return type

AgentFinish

save(file_path: Union[Path, str]) → None

保存代理。

参数：

file_path：保存代理的文件路径。

示例： .. code-block:: python

# 如果使用代理执行器 agent.agent.save(file_path=”path/agent.yaml”)

Parameters

file_path (Union[Path, str]) –

Return type

None

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

tool_run_logging_kwargs() → Dict

Return type

Dict

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 functions: List[dict]

property input_keys: List[str]

获取输入键。这里的输入指用户输入。

property return_values: List[str]

代理的返回值。

Examples using OpenAIFunctionsAgent

• Install package

• LLMonitor

• and some deps for this notebook