Async transform the input into the output format.
Parse a list of candidate model Generation objects into a specific format.
Async parse a single string model output into some structure.
Parse the output of an LLM call with the input prompt for context.
Return dictionary representation of output parser.
The name of the Runnable. Used for debugging and tracing.
Input type.
Output Type.
The type of input this Runnable accepts specified as a Pydantic model.
Output schema.
List configurable fields for this Runnable.
Get the name of the Runnable.
Get a Pydantic model that can be used to validate input to the Runnable.
Get a JSON schema that represents the input to the Runnable.
Get a Pydantic model that can be used to validate output to the Runnable.
Parse the output of an LLM call to a JSON object.
Probably the most reliable output parser for getting structured data that does not use function calling.
When used in streaming mode, it will yield partial JSON objects containing all the keys that have been returned so far.
In streaming, if diff is set to True, yields JSONPatch operations describing
the difference between the previous and the current object.
Get a JSON schema that represents the output of the Runnable.