I wanted to know if the postgres chat memory is enough for the RAG agent to have historical context i.e. previous chats as contextual memory. For example if I give it an instruction in one of the prior chat - is this sufficient. And if not can somebody guide me on this?

Hi, Can anyone help in how postgress chat is used in AI Agent memory in n8n. I am using a webhook in the workflow so maybe that is the issue. I get the following error: "error in sub-node 'Postgres Chat Memory' - No session ID found"

Anyone here who has experience in selling workflows in n8n workflows that runs on your own account? Scenario: I sell a SoMe post generator where they can type in topic in Slack, it generates som examples and the client chooses example 3 to be posted on their LinkedIn profile. I don't want to client to get the automation, I just to let it run on my n8n instance. What is the easiest way to get it set up for the clients Slack and LinkedIn without too much technical stuff to happen in clients end?