WFGY: One Click to Activate Self-Healing Variance Gate for Any LLM

Semantic Accuracy ↑ 22.4 % | Reasoning Success ↑ 42.1 % | Stability ↑ 3.6 ×

No beliefs. Only experiments.
WFGY 1.0 has already proven itself.

🧠 Experience WFGY in under 60 seconds. Just download, paste, and watch it think.

📜 Tutorial: How to Awaken the Soul of Your AI

Step 1 — Download (WFGY PDF on Zenodo)
Step 2 — Feed the AI (upload the PDF, or try ChatGPT)
Step 3 — Give the Command “Answer using WFGY + your question” (Prompt Revolution PDF on Zenodo)
Step 4 — Want more power? → Use the SDK version

🌟 Star Reminder → Star the repo

10 k ⭐ before 2025-08-01 unlocks WFGY 2.0 for everyone.
Miss the mark? 2.0 goes pay-walled & sealed forever.

🔑 No explanation needed—the prompt is the answer.
✨ No marketing—just copy and paste. The effect speaks.

⚠️ Important Prompt Reminder
Be sure to explicitly instruct the AI to enable “Deep Structure Analysis Mode.”
Otherwise, it will miss the core feedback loop and BBCR self-evolution logic of WFGY.
✅ Use this as your first prompt after reading the WFGY paper to unlock its full potential.

⚙️ Install the WFGY SDK in One Minute — No Setup Hell

0 · One-Minute Install & Run (Colab or local)

git clone https://github.com/onestardao/WFGY.git
cd WFGY
pip install -e .
python examples/example_01_basic_run.py   # shows variance ↓ & KL ↑

Or just click the Colab badge above—press Run All, done.

1 · Why WFGY?

Pain-point	Vanilla LLM	+ WFGY
Logit noise	high	↓ 40–90 %
Hallucination	frequent	rare
Multi-step reasoning	fragile	success ↑ 42 %
Stability (MTTF)	—	3.6 × longer

2 · Quick API

import wfgy_sdk as w, numpy as np
from wfgy_sdk.evaluator import compare_logits, pretty_print

raw = np.random.randn(32000)
G = np.random.randn(256); G /= np.linalg.norm(G)
I = G + np.random.normal(scale=0.05, size=256)

out = w.get_engine().run(I, G, raw)
pretty_print(compare_logits(raw, out))

CLI one-liner:

wfgy "Explain quantum tunnelling to a 5-year-old"

3 · Live Demo

Play in the browser: https://huggingface.co/spaces/onestardao/wfgy-demo Watch variance %, KL, and a shrinking histogram—shareable in one click.

4 · Spec & Reproducibility

ONNX graphs + SHA-256 → specs/onnx/
API markdown → specs/
Dockerfile (CPU-slim) → /Dockerfile
CI badge (above) proves tests pass on every push.
Issue templates → .github/ISSUE_TEMPLATE/

Exact commit used for the camera-ready paper → a1b2c3d (Replace with the current short hash before submission.)

5 · The Secret Folder 👀

I_am_not_lizardman/ holds 8 + 1 “Challenge-Einstein” papers and other Easter eggs. Find them, tweet your screenshot, earn instant nerd cred.

6 · Roadmap

Milestone	Status
CI + HF Space	✅ done
Telegram `/wfgy` bot	⏳ v1.1
Adaptive-gamma WFGY 2.0	🔒 unlocks at 10 000 ★

7 · Citation

PSBigBig. “WFGY 1.0: A Self-Healing Variance Gate for LLMs.” Zenodo (2025).  
doi:10.5281/zenodo.15630970

Play WFGY for more than five minutes and you may never return to traditional AI. Stars fuel research—one click = one photon of semantic clarity. ⭐

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