Tool that takes in function or coroutine directly.
The name of the function.
The input arguments' schema.
Whether to return the tool's output directly.
Whether to log the tool's progress.
Callbacks for this call and any sub-calls (e.g. a Chain calling an LLM).
Optional list of tags associated with the retriever.
Optional metadata associated with the retriever.
Handle the content of the ToolException thrown.
Handle the content of the ValidationError thrown.
The tool response format.
Provider-specific metadata.
Check if the tool accepts only a single input argument.
Get the schema for tool calls, excluding injected arguments.
Return True as this class is serializable.
Get the namespace of the LangChain object.
Return a unique identifier for this class for serialization purposes.
Convert the graph to a JSON-serializable format.
Serialize a "not implemented" object.
Get a JSON schema that represents the input to the Runnable.
Get a JSON schema that represents the output of the Runnable.
The type of config this Runnable accepts specified as a Pydantic model.
Get a JSON schema that represents the config of the Runnable.
Return a list of prompts used by this Runnable.
Pipe Runnable objects.
Pick keys from the output dict of this Runnable.
Merge the Dict input with the output produced by the mapping argument.
Invoke the retriever to get relevant documents.
Run invoke in parallel on a list of inputs.
Run ainvoke in parallel on a list of inputs.
Stream all output from a Runnable, as reported to the callback system.
Generate a stream of events.
Bind arguments to a Runnable, returning a new Runnable.
Bind lifecycle listeners to a Runnable, returning a new Runnable.
Bind async lifecycle listeners to a Runnable.
Bind input and output types to a Runnable, returning a new Runnable.
Create a new Runnable that retries the original Runnable on exceptions.
Map a function to multiple iterables.
Add fallbacks to a Runnable, returning a new Runnable.
Create a BaseTool from a Runnable.
