Parsers for OpenAI functions output.
Exception that output parsers should raise to signify a parsing error.
This exists to differentiate parsing errors from other code or execution errors that also may arise inside the output parser.
OutputParserException will be available to catch and handle in ways to fix the
parsing error, while other errors will be raised.
Base class for an output parser that can handle streaming input.
Base class to parse the output of an LLM call.
A single chat generation output.
A subclass of Generation that represents the response from a chat model that
generates chat messages.
The message attribute is a structured representation of the chat message. Most of
the time, the message will be of type AIMessage.
Users working with chat models will usually access information via either
AIMessage (returned from runnable interfaces) or LLMResult (available via
callbacks).
A single text generation output.
Generation represents the response from an "old-fashioned" LLM (string-in, string-out) that generates regular text (not chat messages).
This model is used internally by chat model and will eventually be mapped to a more
general LLMResult object, and then projected into an AIMessage object.
LangChain users working with chat models will usually access information via
AIMessage (returned from runnable interfaces) or LLMResult (available via
callbacks). Please refer to AIMessage and LLMResult for more information.
Parse an output that is one of sets of values.
Parse an output as the JSON object.
Parse an output as the element of the JSON object.
Parse an output as a Pydantic object.
This parser is used to parse the output of a chat model that uses OpenAI function format to invoke functions.
The parser extracts the function call invocation and matches them to the Pydantic schema provided.
An exception will be raised if the function call does not match the provided schema.
Parse an output as an attribute of a Pydantic object.
