LibreAI / Local LLM / waku-agent
// local-llm ยท ShenSeanChen/waku-agent

waku-agent

Local-first agent harness with loop, memory, and evals in readable code.

๐Ÿ’Ž Hidden gemโ˜… 1.9k starsโ‘‚ 384 forksMITupdated 2026-10
โ–ฆ visual โ€” this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

waku-agent is an open-source local llm project by ShenSeanChen (ShenSeanChen/waku-agent on GitHub). It has 1,900 GitHub stars and 384 forks, is released under the MIT license, and was last updated on GitHub on 4 October 2026.

GitHub stars
1,900
Forks
384
License
MIT
Last updated on GitHub
4 October 2026
Category
Local LLM
Listing
Hidden gem โ€” a shorter page for a lesser-known project
Official site
Official site
// how it works

How it works

  1. Clone the harness

    Get the readable codebase.

  2. Configure the loop

    Set up the agent loop for your task.

  3. Add memory

    Wire in memory that persists across runs.

  4. Evaluate

    Use the built-in evals to measure quality.

// features

Why people love it

Local-first

Runs on your machine by design.

Readable code

The whole harness stays legible.

Agent loop

Core loop included, not hidden.

Memory

Persistent memory built in.

Evals

Measure your agent as you build.

Yours to own

Fork and extend freely under MIT.

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// run it

Run it yourself

  1. Step 1 โ€” Clone the repo

    Download the source and move into the project folder.

    git clone https://github.com/ShenSeanChen/waku-agent.git
    cd waku-agent
  2. Step 2 โ€” Check the README

    Every project documents its own setup; start with install requirements.

    cat README.md | head -60
  3. Step 3 โ€” Run it

    Follow the project's launch command โ€” Docker, pip, npm, or a binary release.

    # see README for the exact launch command
// use cases

What you can build

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// faq

Questions, answered

Is this a framework or an app?

A harness: code you own and extend, not a black-box app.

Is waku-agent free for commercial use?

MIT licensed โ€” commercial use allowed.

Which models does it use?

Local-first with configurable providers; check the docs.

Do I need to be a Python dev?

Yes, the harness is Python and meant to be read and modified.

How is it different from LangChain?

It is deliberately minimal and legible rather than feature-maximal.

// keep exploring

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// alternatives

Alternatives in Local LLM

The most-starred other Local LLM projects in the LibreAI catalogue โ€” the realistic shortlist if waku-agent is not the right fit.

Get waku-agent

Free and open โ€” grab the source, star the repo, and start creating.