Give a local AI chatbot memory of past conversations across sessions.
Build a custom AI pipeline that needs structured, queryable memory it fully controls.
Run a fully offline AI assistant with Ollama and no data leaving your machine.
| zaydmulani09/mnemo | manyougz/velotype | evokoa/pggraph | |
|---|---|---|---|
| Stars | 193 | 191 | 210 |
| Language | Rust | Rust | Rust |
| Setup difficulty | moderate | easy | moderate |
| Complexity | 3/5 | 2/5 | 4/5 |
| Audience | developer | writer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires either Docker with Ollama or the compiled Rust binary plus an AI provider API key.
Mnemo is a memory layer for AI language model applications, written in Rust. It solves a specific problem: AI chat sessions normally forget everything when they end. Mnemo runs as a background service alongside your application, listens for text you feed it, and builds a persistent record of entities and their relationships so that future conversations can reference things learned in earlier ones. Here is how it works in practice. Your application sends text to mnemo's ingest endpoint, such as a message from a chat session or a document. Mnemo sends that text to a language model of your choice, which extracts named entities (people, tools, places, concepts) and the connections between them. Those entities are stored in a local SQLite database along with a graph structure that tracks relationships. When your application needs context for a new prompt, it calls mnemo's retrieve endpoint with a query. Mnemo searches the stored text, finds matching entities, traverses the relationship graph to pull in related information, ranks everything by relevance, and returns a ready-to-use context string you can paste into your model's system prompt. Mnemo works with Ollama (a tool for running AI models entirely on your own computer, at no cost), OpenAI, Anthropic, or any API that follows the OpenAI format. No data ever leaves your machine unless you connect it to a cloud API yourself. The whole service ships as a single compiled binary with no Python or external runtime required, and it is designed to respond in under 50 milliseconds. Three ways to use it are provided: Docker with Ollama for a fully local, free setup, installing the Rust binary directly and pointing it at whichever AI service you already use, and a Python SDK for developers who want to call mnemo from Python code without managing HTTP requests manually. A command-line tool is also included for storing and searching memories, listing entities, and inspecting the knowledge graph from a terminal. Mnemo is aimed at developers building custom AI pipelines who need persistent, structured, local memory they control completely. It is not designed for use with managed AI platforms that already handle memory for you. The project is MIT-licensed. The full README is longer than what was shown.
A local Rust service that gives AI chat apps persistent memory by extracting entities and relationships from conversations and returning relevant context on demand.
Mainly Rust. The stack also includes Rust, SQLite, Docker.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.