ComponentsMemoryRocksetOn this pageRocksetRockset is a real-time analytics database service for serving low latency, high concurrency analytical queries at scale. It builds a Converged Index™ on structured and semi-structured data with an efficient store for vector embeddings. Its support for running SQL on schemaless data makes it a perfect choice for running vector search with metadata filters. This notebook goes over how to use Rockset to store chat message history. Setting up​pip install rocksetTo begin, with get your API key from the Rockset console. Find your API region for the Rockset API reference.Example​from langchain.memory.chat_message_histories import RocksetChatMessageHistoryfrom rockset import RocksetClient, Regionshistory = RocksetChatMessageHistory(    session_id="MySession",    client=RocksetClient(        api_key="YOUR API KEY",         host=Regions.usw2a1 # us-west-2 Oregon    ),    collection="langchain_demo",    sync=True)history.add_user_message("hi!")history.add_ai_message("whats up?")print(history.messages)The output should be something like:[    HumanMessage(content='hi!', additional_kwargs={'id': '2e62f1c2-e9f7-465e-b551-49bae07fe9f0'}, example=False),     AIMessage(content='whats up?', additional_kwargs={'id': 'b9be8eda-4c18-4cf8-81c3-e91e876927d0'}, example=False)]PreviousRemembrallNextSQL (SQLAlchemy)Setting upExample