text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryCassandra Chat Message HistoryDynamodb Chat Message HistoryEntity Memory with SQLite storageMomento Chat Message HistoryMongodb Chat Message HistoryMotÃ¶rhead MemoryMotÃ¶rhead Memory (Managed)Postgres Chat Message HistoryRedis Chat Message HistoryZep MemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsMemoryEntity Memory with SQLite storageEntity Memory with SQLite storageIn this walkthrough we'll create a simple conversation chain which uses ConversationEntityMemory backed by a SqliteEntityStore.from langchain.chains import ConversationChainfrom langchain.llms import OpenAIfrom langchain.memory import ConversationEntityMemoryfrom langchain.memory.entity import SQLiteEntityStorefrom langchain.memory.prompt import ENTITY_MEMORY_CONVERSATION_TEMPLATEentity_store = SQLiteEntityStore()llm = OpenAI(temperature=0)memory = ConversationEntityMemory(llm=llm, entity_store=entity_store)conversation = ConversationChain(    llm=llm,    prompt=ENTITY_MEMORY_CONVERSATION_TEMPLATE,    memory=memory,    verbose=True,)Notice the usage of EntitySqliteStore as parameter to entity_store on the memory property.conversation.run("Deven & Sam are working on a hackathon project")            > Entering new ConversationChain chain...    Prompt after formatting:    You are an assistant to a human, powered by a large language model trained by OpenAI.        You are designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, you are able