📄 中文摘要
在语义搜索的实现中，嵌入层往往被简化为一行代码的调用。然而，实际操作中，这一层是系统中最容易出现微妙错误的地方。这些错误不会导致应用崩溃，但会导致相似度评分、排名不准确，搜索结果看似正确却不尽如人意。构建服务时，开发者发现数据库架构和搜索查询并不是最困难的部分，反而是嵌入层耗费了最多的时间。嵌入层的复杂性主要体现在三个方面：首先，外部 API 调用可能因网络问题而失败；其次，嵌入向量的处理和存储需要精确；最后，如何在不同环境中保持一致性也是一大挑战。
使用 Spring Boot 和 pgvector 构建语义搜索 API 的第三部分：嵌入层
📄 English Summary
Building a Semantic Search API with Spring Boot and pgvector - Part 3: The Embedding Layer.
The implementation of semantic search often simplifies the embedding layer to a single line of code. However, in practice, this layer is where subtle bugs are most likely to occur. These bugs do not crash the application but lead to inaccurate similarity scores, incorrect rankings, and search results that seem correct but feel off. When building the service, developers found that the database schema and search query were not the most challenging parts; instead, the embedding layer consumed the most time. The complexity of the embedding layer arises from three main factors: first, external API calls can fail due to network issues; second, the processing and storage of embedding vectors require precision; and third, maintaining consistency across different environments poses a significant challenge.