LLMs are stateless — without memory management, every message is a fresh start. This module covers the conversation memory layer: how to store messages as a linked graph, how to retrieve and search them, and how adding a message automatically seeds the long-term memory layer through entity extraction.
By the end of this module, you will:
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Explain why a linked-list graph structure is more useful for conversation history than a flat table
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Build a conversation memory layer using
add_session(),add_message(), andget_recent_messages() -
Search message history semantically using vector embeddings
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Understand how entity extraction automatically connects short-term and long-term memory