PageIndex seems to be able to become an industry standard index method in the AI era, which is similar position as B-tree earned in the RDBMS era.
Standing on the shoulders of giants is the right way to build something new.
📢 New feature in PageIndex Chat: Team Spaces
👥 Create a shared workspace where your team can sync documents, chat with the same knowledge base, and manage access in one place.
#PageIndex#NewFeature#RAG
@AI_WithExpert You can also check out OpenKB: Open LLM Knowledge Base. It lets your sources accumulate and cross-link across sessions, instead of getting re-pasted into a new notebook each time. github.com/VectifyAI/Open…
Cool workflow, but it's still one-shot per session. The next missing piece is persistence — the sources you upload today don't make tomorrow's query smarter. Stacks that actually compound (a Markdown vault that updates itself) feel like the next step beyond NotebookLM-style one-offs. github.com/VectifyAI/Open…
@claudeai Linear context doesn't scale. Hierarchical context does.
Dynamic workflows are proving this for agents; while PageIndex is proving it for retrieval.
The future isn't infinite context. It's agentic, adaptive context trees.
github.com/VectifyAI/Page…
@_catwu Linear context doesn’t scale. Hierarchical context does.
Dynamic workflows are showing the way for agents. PageIndex is proving the same for retrieval.
The future isn’t infinite context. It’s agentic, adaptive context trees.
github.com/VectifyAI/Page…
@bcherny Linear context doesn't scale. Hierarchical context does.
Dynamic workflows are showing it for agents, while PageIndex is proving it for retrieval.
The future isn't infinite context. It's agentic, adaptive context trees.
github.com/VectifyAI/Page…
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