Pinecone 集成 Gemini Embedding 2,混合搜索免建第二索引
Pinecone 把 Google 的 Gemini Embedding 2 直接做进了索引,发纯文本就能自动向量化,全文搜索和向量搜索共用一个字段。做 RAG 或混合搜索的朋友可以少维护一套嵌入管线,部署成本明显下降,值得上手试试。
Pinecone 宣布其集成嵌入功能新增支持 Google 的 Gemini Embedding 2 模型,开发者只需将 gemini-embedding-2 设置在文本字段上,即可直接发送原始文本,无需自行调用嵌入 API 和维护嵌入流水线。
该字段同时支持全文检索,意味着混合搜索(向量检索 + 关键词检索)不再需要单独的索引或独立的嵌入流程,一个字段即可同时承担语义搜索与全文搜索两类任务。
对使用 RAG 或企业检索的开发者而言,这一集成减少了嵌入管线与基础设施的运维成本,也降低了混合搜索架构的搭建门槛。
You can now use Google's Gemini Embedding 2 with Pinecone integrated embedding.
Set gemini-embedding-2 on a text field and send plain text. That field can serve full-text search too, so hybrid search doesn't need a second index or embedding pipeline.
🔗 https://t.co/nEtVDP9CpH https://t.co/aHvj5bgzDt
This report is categorized under AITOP's "Products" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include Gemini Embedding 2, Pinecone, RAG, 向量数据库.
Source attribution: curated from Pinecone (@pinecone).