winstonkoh87AI apps
Athena Public
Athena-Public
A generic LLM is a brilliant amnesiac. Athena is the hippocampus — the memory that makes intelligence useful.
- Windows
- macOS
- Linux
- Runs locally
- Needs API key
- Popularity
- 583 Stars
- GitHub stars
- Recent activity
- 8/25/2026
- Updated in the last 30 days
- License
- MIT
- Permissive
Why it matters
We look beyond stars: what problem it solves, whether it creates real utility, and what makes its approach worth noticing.
Community activity
In the last 90 days there were 1 new issues and 12 pull requests; the bounded issue/PR samples include 1 issue authors and 2 PR contributors, with 6 releases.
Maintainer responsiveness
The 1-issue window sample had a 100% close rate, and the 12-pull-request sample had a 75% merge rate. Maintainer-comment observations covered only 100% of that issue sample, so response rate and first-response speed are not reported.
Key highlights
- 🧠 Your Memory, Your Machine — Files on your disk, not in OpenAI's cloud. Read them, edit them, git-version them.
- 🔌 Switch Models Freely — Claude today, Gemini tomorrow, GPT next week. The memory stays. The model is just whoever'
- 📈 It Compounds — Session 500 recalls patterns from session 5. The durable asset isn't the code — it's your data: an
Quick start
How it is installed, how hard it is, and where to start.
Best for
- Developers who want to try it on their machine
Watch outs
- 5 inferred from materials — review under Sources below
Sources
Each field shows its status and source — expand to review.
7 · Expand
Sources
Each field shows its status and source — expand to review.
Latest release
Verifiedv9.9.8
Source: GitHub API · latest_release=v9.9.8 · 8/25/2026
License
VerifiedMIT
Source: GitHub API · license.spdx_id=MIT · 8/25/2026
needs api key
Inferred from materialsYes
Source: Project README · matched api key keywords · 8/16/2026
One-liner
Verified{"en":"A generic LLM is a brilliant amnesiac. Athena is the hippocampus — the memory that makes intelligence useful.","zh":"Athena 解决了当前 AI 助手普遍存在的“记忆碎片化”和“平台锁定”问题。它通过本地优先的 Markdown 架构,将个人上下文与模型解耦,实现了跨模型的知识持久化。"}
Source: heuristic_batch_publish · batch-publish-tools heuristic write · 8/24/2026
Platforms
Inferred from materialswindows, macos, linux
Source: Project README · windows,macos,linux · 8/16/2026
Category hint
Inferred from materialsai-apps
Source: Project README · hint=ai-apps · 8/16/2026
supports local
Inferred from materialsYes
Source: Project README · matched local keywords · 8/16/2026
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