Show HN：Faramesh – 適用於隨機自主 AI 代理的確定性閘門
本文介紹了 Faramesh，一個為自主 AI 代理提供確定性閘門的開源專案。它旨在為工具呼叫建立加密邊界，確保操作符合定義的策略，並透過正規化引擎解決 LLM 輸出不一致的挑戰。
I built Faramesh because I wanted a hard, cryptographic boundary between the agent's "brain" and my actual infrastructure. It intercepts tool-calls and forces them through a deterministic gate before any code runs. If the action isn't in your policy, it simply doesn't exist.
The biggest headache was canonicalization.py. LLMs are messy—one model sends a float as 1.0, another as 1.00, and it breaks the cryptographic hash every time. I wrote a normalization engine to ensure that identical intent produces the exact same byte-stream and hash.
It’s open source (Python/Node SDKs). I’m curious if people think this should live at the framework level or as a standalone proxy. Tear the code apart:
https://github.com/faramesh/faramesh-core
For theory lovers, I'd invite you to read a paper i published just recently titled "Faramesh: A Protocol-Agnostic Execution Control Plane for Autonomous Agent systems" (Link below)
https://doi.org/10.5281/zenodo.18296731
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