factcircuit
FactCircuit는 불변 출처와 단계별 검증, 제한된 검색, 재현 가능한 평가를 제공하는 감사 가능한 주장·증거 검증 루프입니다
개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
로그인한 뒤 확인 파일을 만들어 이 저장소의 기본 브랜치에 30분 안에 커밋해 주세요. 다른 브랜치나 포크의 파일은 인정하지 않습니다. 파일을 올린 뒤 아래에서 확인하면 관리자 승인 없이 관리할 수 있습니다. 자격을 유지하려면 파일을 남겨 두세요.
로그인이 필요하면 로그인 화면으로 이동합니다. 로그인 후 이곳으로 돌아와 원하는 확인 버튼을 다시 눌러 주세요.
프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
NEBULA3D — *Neutron Elastic Background Utility for Local Analysis and 3D-ΔPDF* — is a Python toolkit (the nebula3d package) for cleaning 3D reciprocal-space neutron diffuse scattering volumes and preparing them for 3D-ΔPDF analysis.README 전문 보기 ↗
NEBULA3D (Neutron Elastic Background Utility for Local Analysis and 3D-ΔPDF) is a Python package and browser console that cleans 3D reciprocal-space diffuse-scattering volumes, neutron or X-ray, into real-space 3D-ΔPDF maps, with an AI agent that assesses and tunes the reduction with you.
Try it in the browser: https://drthyang.github.io/nebula3d/ runs the whole pipeline client-side; nothing is uploaded.
NEBULA Pilot on the built-in synthetic demo volume (simulated data, not measured), with a local model. A time-lapse: the waits for the model are sped up.
flatten stage), the
3D-ΔPDF transform and a back-FFT consistency check
(the pipeline).nebula3d-web serves the same console natively, with no size limit.LoadMD opens.Open https://drthyang.github.io/nebula3d/, load the built-in demo volume
(Use demo) or your own .nxs/.h5, and press Run pipeline.
To run it natively, from a clone (Python 3.10+ and Node.js):
pip install -e ".[web]"
make web-install && make ui # build the console once
nebula3d-web # serves http://127.0.0.1:8000
More, including the batch scripts: QUICKSTART.md.
An agent docked beside every page. Connect a local model (Ollama, LM Studio) or a cloud one (OpenAI, Gemini, Anthropic): it measures cuts, judges each stage, runs and tunes the pipeline, and shows you the figures it reads. Every number comes from deterministic metrics, and each answer is checked against the tools' results before you read it. Its tools, guardrails and evals: docs/pilot.md.
Beta: the latest release is 0.3.0, and main carries the 0.4.0 work
(CHANGELOG.md). CI runs the Python tests on 3.10–3.13 with
ruff and mypy, and the console's tests and builds, including replays of the
agent's evals (docs/development.md).
Copyright (C) 2026 Tsung-han Yang.
This project is licensed under the GNU Affero General Public License v3.0 or later.
This is an independent personal software project. It is not affiliated with, sponsored by, endorsed by, funded by, developed for, or owned by any employer, institution, laboratory, university, government agency, funding organization, facility, or other organization.
Commercial, closed-source, proprietary, or alternative licensing may be available only by separate written permission from the copyright holder.
See PROVENANCE.md for the project provenance statement.