langchain.tools.bing_search.tool.BingSearchResults

class langchain.tools.bing_search.tool.BingSearchResults(*, name: str = 'Bing Search Results JSON', description: str = 'A wrapper around Bing Search. Useful for when you need to answer questions about current events. Input should be a search query. Output is a JSON array of the query results', args_schema: Optional[Type[BaseModel]] = None, return_direct: bool = False, verbose: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False, num_results: int = 4, api_wrapper: BingSearchAPIWrapper)

Bases: BaseTool

Tool that queries the Bing Search API and gets back json.

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 api_wrapper: langchain.utilities.bing_search.BingSearchAPIWrapper [Required]

param args_schema: Optional[Type[BaseModel]] = None

Pydantic model class to validate and parse the tool’s input arguments.

param callback_manager: Optional[BaseCallbackManager] = None

Deprecated. Please use callbacks instead.

param callbacks: Callbacks = None

Callbacks to be called during tool execution.

param description: str = 'A wrapper around Bing Search. Useful for when you need to answer questions about current events. Input should be a search query. Output is a JSON array of the query results'

Used to tell the model how/when/why to use the tool.

You can provide few-shot examples as a part of the description.

param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False

Handle the content of the ToolException thrown.

param metadata: Optional[Dict[str, Any]] = None

Optional metadata associated with the tool. Defaults to None This metadata will be associated with each call to this tool, and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a tool with its use case.

param name: str = 'Bing Search Results JSON'

The unique name of the tool that clearly communicates its purpose.

param num_results: int = 4

param return_direct: bool = False

Whether to return the tool’s output directly. Setting this to True means

that after the tool is called, the AgentExecutor will stop looping.

param tags: Optional[List[str]] = None

Optional list of tags associated with the tool. Defaults to None These tags will be associated with each call to this tool, and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a tool with its use case.

param verbose: bool = False

Whether to log the tool’s progress.

__call__(tool_input: str, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → str

Make tool callable.

async ainvoke(input: Union[str, Dict], config: Optional[RunnableConfig] = None, **kwargs: Any) → Any

async arun(tool_input: Union[str, Dict], verbose: Optional[bool] = None, start_color: Optional[str] = 'green', color: Optional[str] = 'green', callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any

Run the tool asynchronously.

invoke(input: Union[str, Dict], config: Optional[RunnableConfig] = None, **kwargs: Any) → Any

validator raise_deprecation  »  all fields

Raise deprecation warning if callback_manager is used.

run(tool_input: Union[str, Dict], verbose: Optional[bool] = None, start_color: Optional[str] = 'green', color: Optional[str] = 'green', callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any

Run the tool.

property args: dict

property is_single_input: bool

Whether the tool only accepts a single input.

model Config

Bases: object

Configuration for this pydantic object.

arbitrary_types_allowed = True

extra = 'forbid'