从你自己文档里作答的客服智能体

多数团队最先需要的那个智能体：它读你的帮助中心，凌晨三点也能回答客户，还不瞎编政策。

上传文档，把它们切成块，存嵌入，只用检索到的段落加一个来源链接来回答。什么都匹配不上时，智能体转给人工，而不是瞎猜。

Build a documentation support agent.

Data: a table "documents" (title, url, content) and a table "chunks" (document_id, content, embedding vector). A table "escalations" (question, email, created_at, status).

Server: one edge function that embeds the user question, retrieves the six closest chunks, and streams an answer that uses only those chunks. Every answer must end with the source links it used. If similarity is below the threshold, return a short "I do not have this in the docs" answer and insert a row into escalations.

UI: a chat page with streaming responses, message history in the browser, source links rendered as chips under each answer, and an escalation form that appears when the agent cannot answer.

Enable row level security on all tables, keep model calls on the server, and show a clear error state when the request fails.