Part 3/9:
Chains: At the core of Lang Chain are chains, which allow developers to connect multiple tasks, such as calling an LLM or retrieving data, in a seamless workflow.
Indexes: The framework enables the use of indexes, document loaders, and vector databases, thus enriching the data available to models beyond their initial training.
Memory: One of Lang Chain's most advantageous features is its ability to maintain long-term memory of past interactions, which can be crucial for applications that evolve over time.
Agents: These are components that leverage the LLM as a reasoning engine to determine subsequent actions, creating a more dynamic user experience.