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Holographic Memory

Holographic Memory System is a Rust-backed library for Rust and Node.js applications that provides document search, associative memory and analogical reasoning using vector-symbolic architectures.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Holographic Memory — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use HMS when implementing document retrieval or associative memory inside a Rust or Node.js application and you want the store and model stages to run locally. Choose the local-model option when you have compatible model files available in local directories.

Who it is for

  • Developers building Rust or Node.js applications with local document retrieval.
  • Developers adding associative memory, relational knowledge representation or analogical reasoning to an application.

Documented uses

  • Index documents and search them by meaning alongside BM25 ranking.
  • Retrieve matching documents with source details and metadata filters.
  • Add vector-symbolic associative memory and analogical reasoning to an application.
  • Use local embedding and reranking models without having the library download model weights.
Before you choose

Requirements & limits

The repository is public and lists the AGPL-3.0 license. Core installation instructions are provided for Rust and Node.js.

  • HMS is a software library, so using it requires application integration rather than an end-user interface.
  • Document search combines BM25 with exact cosine over embeddings the application supplies; local embedding and reranking are additional options.
  • The optional local-model stages require locally available model weights and do not download them.
  • The experimental Python SDK is an HTTP client and requires an HMS-backed service supplied separately.
  • Existing stores with the older embedding schema need re-encoding from original sources.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Add and query a document with the Node.js library

Store one document and retrieve a relevant match with a metadata filter.

Before you start

  • Node.js application
  • The holographic-memory package
  • A local directory for the HMS store

Steps

  1. Create a HolographicMemorySystem with a vector dimension and local storage path.

  2. Wrap it in DocumentMemory.

  3. Call memorize with a document ID, text, source URI and metadata.

  4. Call search with a query and metadata filter, then read the returned document ID, source URI and text.

  5. Call flush to flush the store.

Expected outcome

The application can retrieve a matching document and its source details from its local HMS store.

Guide limitations

  • The example supplies no embedding model; local embeddings and reranking are a separate setup.
  • Existing stores using an older embedding schema require re-encoding from original sources.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
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Sources checked
14 October 2026
Original website title
writerslogic/holographic-memory · Official homepage title · retained in its source language
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