Schemas are the LangChain Base Classes and Interfaces.
Abstract base class for memory in Chains.
Memory refers to state in Chains. Memory can be used to store information about past executions of a Chain and inject that information into the inputs of future executions of the Chain. For example, for conversational Chains Memory can be used to store conversations and automatically add them to future model prompts so that the model has the necessary context to respond coherently to the latest input.
LangChain Runnable and the LangChain Expression Language (LCEL).
The LangChain Expression Language (LCEL) offers a declarative method to build production-grade programs that harness the power of LLMs.
Programs created using LCEL and LangChain Runnables inherently support synchronous, asynchronous, batch, and streaming operations.
Support for async allows servers hosting LCEL based programs to scale better for higher concurrent loads.
Streaming of intermediate outputs as they're being generated allows for creating more responsive UX.
This module contains schema and implementation of LangChain Runnables primitives.
