Auto-indexing key-value store

In plain words

This is a development tool that provides full-text search functionality through a 16-bit vector space index accessible via HTTP API. It's designed for developers who need to integrate search capabilities into their applications. The tool uses vector space indexing to handle search queries, allowing for efficient retrieval of relevant results from text data.

written from the facts on this page · September 2026

From the sources

This is a reboot of the old Resin search engine/machine learning project . Resin is a vector space search engine, a vector database and an anything key/value store. It powers efficient string processing, vector operations, and custom storage primitives designed for speed and simplicity. It can produce large language models out of strings and large anything models out of byte arrays. Contributions are welcome! Please open an issue or pull request with clear motivation, tests when applicable, and concise changes. Language model search engine built on a vector database and an anything key/valuefrom github.com

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  PageIndex – Vectorless RAG2025 · github.com · ▲192

  Not all improvements come from adding complexity — sometimes it's about removing it. PageIndex takes a different approach to RAG. Instead of relying on vector databases or artificial chunking, it builds a hierarchical tree structure from documents and uses reasoning-based tree search to locate the most relevant sections. This mirrors how humans approach reading: navigating through sections and context rather than matching embeddings. As a result, the retrieval feels transparent, structured, and explainable. It moves RAG away from approximate "semantic vibes" and toward explicit reasoning…

• IM
  I made a website to semantically search ArXiv papers2024 · papermatch.mitanshu.tech · ▲324

  As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…

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  Pluggable vector space models2019 · github.com · ▲12

  Language model search engine built on a vector database and an anything key/value store. - Release v.0.31 · kreeben/resin

• AS
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  I've been building a tool that changes how LLM coding agents explore codebases, and I wanted to share it along with some early observations. Typically claude code globs directories, greps for patterns, and reads files with minimal guidance. It works in kind of the same way you'd learn to navigate a city by walking every street. You'll eventually build a mental map, but claude never does - at least not any that persists across different contexts. The Recursive Language Models paper from Zhang, Kraska, and Khattab at MIT CSAIL introduced a cleaner framing. Instead of cramming everything into…

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