# 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/hwx56fa
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構建 LLM 應用：介紹（第一部分）**
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）。即使是一個簡單的檢索增強生成（RAG）應用也涉及到調整衆多不同的參數、組件和模型在我最近對語言模型（LLM）應用的探索中，我被檢索增強生成（RAG）所扮演的重要角色深深吸引。從概念構想到雲上部署，全面理解端到端的 RAG 架構是一項相當 ⌘ Read more