About the project

About Mneme

Named after Mnemosyne, Mneme is a local-document Retrieval-Augmented Generation system for developers who want useful answers without giving up the trail back to their files.

The thesis

Mneme treats documents as a memory you should be able to inspect. It indexes local files, retrieves across them, and uses an OpenAI-compatible endpoint only for the LLM-backed parts you choose to enable.

Your documents. A memory you can verify.

What is in the repository

SurfacePurpose
src/Standard RAG, Graph RAG, query decomposition, citations, queueing, metrics, quality, and security.
tui/Streaming chat, slash commands, settings, file management, and directory watching.
tests/Offline-safe unit, integration, and regression coverage.
benchmarks/Retrieval quality data and evaluation surfaces.

What the interface should make visible

  • Local ownership of files, parsing, indexing, and retrieval.
  • Source-linked answers with enough location information to inspect.
  • Explicit endpoint and context boundaries when an LLM-backed feature is used.
  • A developer workflow that starts with the CLI or terminal UI, not a cloud dashboard.
Open source

Mneme is released under the MIT License. Read the code, run the tests, or start with the GitHub repository ↗.

Search Mneme documentation