<ul data-eligibleForWebStory="false"><li>In the world of AI-powered document chat systems, a proposal suggests storing session knowledge vectors in the browser using IndexedDB for session-level document-based AI chat, instead of relying on server-side vector databases.</li><li>The article examines the performance implications of server-side vector storage which can introduce latency and scalability issues, especially with increasing concurrent users competing for shared infrastructure resources.</li><li>The proposal leverages modern browser capabilities like IndexedDB, highlighting the performance advantages such as handling individual users’ document processing needs effectively.</li><li>The browser-based RAG approach is seen as a compelling alternative for session-level document chat applications, with the feasibility demonstrated through a working implementation called Smart Document Workspace.</li></ul>

Proposing Browser-Based RAG for Session-Level Knowledge: A Case for IndexedDB Vector Storage

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