# 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.
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# Options:
#     uri     Filter to show a specific users twts.
#     offset  Start index for quey.
#     limit   Count of items to return (going back in time).
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# twt range = 1 1
# self = https://watcher.sour.is/conv/b6biefq
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構建 LLM 應用：評估（第八部分）**
作者：Vipra Singh 編譯：ronghuaiyang 導讀我們在上一篇博客中成功構建了多個 RAG 應用。現在，讓我們來看看評估這些應用的過程。我們在上一篇博客中成功構建了多個 RAG 應用。現在，讓我們來看看評估這些應用的過程。我們將探究從我們的大型語言模型生成的結果有多可靠。首先，讓我們通過下表來理解傳統機器學習、深度學習和 LLMs 之間的區別。大型語言模型（LLMs）的 ⌘ Read more