节点与集成
Postgres Chat Memory
Use the Postgres Chat Memory node to use Postgres as a memory1 server for storing chat history.
On this page, you'll find a list of operations the Postgres Chat Memory node supports, and links to more resources.
Node parameters
- Session Key: Enter the key to use to store the memory in the workflow data.
- Table Name: Enter the name of the table to store the chat history in. The system will create the table if doesn't exist.
- Context Window Length: Enter the number of previous interactions to consider for context.
Related resources
Refer to LangChain's Postgres Chat Message History documentation for more information about the service.
View n8n's Advanced AI documentation.
Single memory instance
If you add more than one Postgres Chat Memory node to your workflow, all nodes access the same memory instance by default. Be careful when doing destructive actions that override existing memory contents, such as the override all messages operation in the Chat Memory Manager node. If you want more than one memory instance in your workflow, set different session IDs in different memory nodes.
Footnotes
- Back
In an AI context, memory allows AI tools to persist message context across interactions. This allows you to have a continuing conversations with AI agents, for example, without submitting ongoing context with each message. In n8n, AI agent nodes can use memory, but AI chains can't.
官方原文和授权
本页来自 N8N 英文官方网站固定快照，并转换成 xueai 静态页面。内容以 N8N 持续更新的官方页面为准。