# I am the Watcher. I am your guide through this vast new twtiverse.
# 
# Usage:
#     https://watcher.sour.is/api/plain/users              View list of users and latest twt date.
#     https://watcher.sour.is/api/plain/twt                View all twts.
#     https://watcher.sour.is/api/plain/mentions?uri=:uri  View all mentions for uri.
#     https://watcher.sour.is/api/plain/conv/:hash         View all twts for a conversation subject.
# 
# Options:
#     uri     Filter to show a specific users twts.
#     offset  Start index for quey.
#     limit   Count of items to return (going back in time).
# 
# twt range = 1 1
# self = https://watcher.sour.is/conv/ikr6vmq
構建 LLM 應用:向量數據庫(第四部分)**
作者:Vipra Singh 編譯:ronghuaiyang 導讀在系列博客中,我們通過檢索增強生成(RAG)應用的視角來學習大規模語言模型(LLM)。引言在之前的博文中,我們已經討論到將原始數據嵌入爲向量的內容。爲了重複利用嵌入的信息,我們需要存儲這些嵌入,以便按需訪問。爲此,我們使用一種特殊的數據庫,即向量數據庫。對於使用檢索增強生成(RAG)的大規模應用來說,高效存儲和檢索向量的 ⌘ Read more