# 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/lxqv56a
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使用 Ollama 和 Go 基於文本嵌入模型實現文本向量化**
基於 RAG + 大模型的應用已經成爲當前 AI 應用領域的一個熱門方向。RAG(Retrieval-Augmented Generation) 將檢索和生成兩個步驟相結合，利用外部知識庫來增強生成模型的能力 (如下圖來自網絡)。在 RAG 賦能的大模型應用中，關鍵的一步是將文本數據向量化後存儲在向量數據庫中 (如上圖的紅框)，以實現快速的相似度搜索，從而檢索與輸入查詢相關的文本片段，再將檢索到的 ⌘ Read more