开源多模态语义搜索
我开发了一个多模态语义搜索框架（RAG），它协调了MongoDB、Pinecone、S3存储桶、LLM API等组件。
如果您对“语义搜索”不太熟悉，可以将其视为RAG。
为了实现文本、图像等的语义搜索，我们需要在将数据发送到数据库之前对其进行预处理。
我的框架充当您的应用程序与现有数据库之间的中间层，所有处理都在这里进行。
其主要区别在于它与MongoDB兼容的NoSQL接口：您与这个RAG引擎的交互方式与MongoDB完全相同，同时享受强大的向量搜索和文档增强功能。
它是开源的： https://github.com/onenodehq/onenode
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I've developed a framework for multimodal semantic search (RAG), which orchestrates MongoDB, Pinecone, S3 bucket, LLM API, etc.<p>If you are not too familiar with "semantic search," think of it as RAG.<p>To enable semantic search for text, image, etc, we need to pre-process our data before sending it to the database.<p>My framework works as a middle layer between your app and existing databases, where all the processings happen.<p>The key differentiator is its MongoDB-compatible NoSQL interface: you interact with this RAG engine exactly as you would with MongoDB, while benefiting from powerful vector search and document-augmentation capabilities.<p>It's open source: https://github.com/onenodehq/onenode