transform

Run a function in an executor.

Base abstract message class.

Messages are the inputs and outputs of a chat model.

Examples include HumanMessage, AIMessage, and SystemMessage.

Message chunk, which can be concatenated with other Message chunks.

Base class to parse the output of an LLM call.

Output parsers help structure language model responses.

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).

ChatGeneration chunk.

ChatGeneration chunks can be concatenated with other ChatGeneration chunks.

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.

GenerationChunk, which can be concatenated with other Generation chunks.

Base class for an output parser that can handle streaming input.

Base class for an output parser that can handle streaming input.

Configuration for a Runnable.

# Parent sets tags
chain.invoke(input, config={"tags": ["parent"]})
# Child automatically inherits and can add:
# ensure_config({"tags": ["child"]}) -> {"tags": ["parent", "child"]}