hayko1984/aethon-oss

★ 14PythonAudience · developerComplexity · 3/5LicenseSetup · moderate

Mindmap

mindmap
  root((aethon-oss))
    What It Does
      Local AI assistant
      Markdown memory
      No cloud needed
    Tech Stack
      Python
      Ollama
    Use Cases
      Personal knowledge base
      Agent memory layer
      Privacy-first workflows
    Audience
      Developers
      Researchers
      Tool builders
    Setup
      Clone repo
      Python venv
      Scan example files

mindmap root((aethon-oss)) What It Does Local AI assistant Markdown memory No cloud needed Tech Stack Python Ollama Use Cases Personal knowledge base Agent memory layer Privacy-first workflows Audience Developers Researchers Tool builders Setup Clone repo Python venv Scan example files

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Things people build with this

USE CASE 1

Build a personal AI assistant that remembers past conversations as plain Markdown files you can read and edit directly.

USE CASE 2

Set up a local knowledge base that links daily notes chronologically, similar to Obsidian but driven by a local AI model.

USE CASE 3

Create a privacy-first agent memory system that runs entirely on your own hardware with no API calls to external services.

Tech stack

PythonOllama

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Ollama installed and a compatible AI model downloaded locally before the assistant can respond.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

In plain English

AETHON OSS is an open-source reference implementation of a local AI assistant workspace. The core idea is that the AI keeps its memory as plain Markdown files on your own machine rather than storing anything in the cloud, and it uses AI models that run locally through software compatible with Ollama (a tool for running AI models on personal hardware) rather than sending requests to external services. The project positions itself against the typical AI assistant demo, which tends to be stateless (no memory between sessions) and dependent on cloud APIs. AETHON instead keeps daily logs that link chronologically, similar to how tools like Obsidian connect personal notes. The memory accumulates as readable Markdown so the user can inspect what the assistant knows and how it is organized. The repository includes a small Python package for indexing that memory and doing basic local retrieval, a script for linking daily note files in chronological order, a standalone web page for visualizing how memory entries connect to each other, and example memory files with personal details removed. The maintainer's actual working AETHON setup contains private notes, browser profiles, API keys, and social account automation that are intentionally excluded from this public version. What is shared here is the structural and tooling layer that could be reused by others who want to build a similar local-first assistant workflow. The stated goal is to evolve this public extraction into a reusable framework for maintainers, researchers, and tool builders who want durable, inspectable agent memory without relying on cloud services. The project is described as an early extraction, meaning it reflects a working private system but has not yet been polished into a finished, general-purpose tool. The license is MIT, and setup involves cloning the repository, creating a Python virtual environment, installing the package, and running a command-line scan against the included example memory files.

Copy-paste prompts

Prompt 1

Using the aethon-oss Python package, show me how to index a folder of Markdown memory files and retrieve the most relevant entries for a given query.

Prompt 2

I want to build a local AI assistant using Ollama that keeps memory in Markdown files like aethon-oss. Write a Python script that reads a memory file, appends a new dated entry, and links it to the previous day's file.

Prompt 3

Show me how to launch the aethon-oss memory visualization web page to display connections between Markdown memory entries in a local browser.

Prompt 4

I want to adapt aethon-oss for a team wiki where multiple people contribute Markdown notes. What changes would I need to make to the indexing and linking scripts?

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