Conversational Memory in LangChain

This post details the integration of Milvus as a vector store for LangChain's conversational memory. It outlines the setup process involving LangChain libraries, OpenAI embeddings, and Milvus Lite. The core contribution is demonstrating how to use `VectorStoreRetrieverMemory` with Milvus to store and retrieve conversational context, enabling LLMs to maintain state and provide more coherent interactions. It provides code examples for initializing Milvus Lite, creating a retriever, saving conversation context, and querying the memory within a `ConversationChain`.