LlamaIndex Chat_Store Integration: Tablestore Chat Store
Using TablestoreChatStore, you can store your chat history remotely, without having to worry about manually persisting and loading the chat history.
Installation
pip install llama-index-storage-chat-store-tablestore
Usage
from llama_index.storage.chat_store.tablestore import TablestoreChatStore
from llama_index.core.memory import ChatMemoryBuffer
# 1. create tablestore vector store
chat_store = TablestoreChatStore(
endpoint="<end_point>",
instance_name="<instance_name>",
access_key_id="<access_key_id>",
access_key_secret="<access_key_secret>",
)
# You need to create a table for the first use
chat_store.create_table_if_not_exist()
chat_memory = ChatMemoryBuffer.from_defaults(
token_limit=3000,
chat_store=chat_store,
chat_store_key="user1",
)
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