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Z-GRC:用於 LLM 治理的 Python 函式庫與控制面板,也適用於命令列工具(Claude Code 等):r/ClaudeCode

Z-GRC 是一款面向 LLM 應用程式與命令列工具的開源治理、風險與控制引擎。它包含一個攔截 LLM API 呼叫的 Python 套件、一個用於管理使用者、使用者群組、配額與 API 權杖的 Next.js 控制面板,以及代理伺服器模式。透過代理模式,Claude Code 等已經建置好的工具無需修改原始碼,就能把 LLM 流量導經它,實現即時成本控制與攔截。

已翻譯

關於這個 mod

這篇貼文宣布 Z-GRC(Governance, Risk, Control,治理、風險與控制),這是團隊的第一個開源版本。它的目的是解決 AI 代理、聊天機器人與內部工具專案中反覆出現的問題:意外的成本飆升、缺乏即時用量控制、共用的 LLM 憑證無法依使用者控管成本,以及無法涵蓋 DEV/STAGE 環境。

方案包含三個部分:一個 Python 套件(z-grc),作為攔截 LLM API 呼叫的執行階段;一個 Next.js 控制面板(z-grc-application),用來建立使用者、使用者群組、配額與 API 權杖,並將用量視覺化;以及以 z-grc 套件為基礎的代理伺服器模式,讓 Claude Code(Codex 仍在開發中)等已部署的應用程式,把 LLM 流量導經它。簡單來說,無需修改原始碼,就能控制 Claude Code 的成本。

認證權杖會攜帶經過壓縮並加入雜訊的承載資料,其中嵌入了使用者身分、設定、配額上限、攔截條件與遙測的目的地。控制面板負責核發這些權杖並保存設定。此套件可以在前景或背景以代理伺服器模式執行,外部命令列工具無需修改程式碼、無需等待,就能把 LLM 流量導向它;一旦超過目標成本,就會攔截。

連結:儲存庫 https://github.com/zeb-ai/z-grc,文件 https://zeb-ai.github.io/z-grc-application/

安裝

安裝方式請查看原始來源。

原文 / README

Title: Z-GRC a Python library & control panel for LLM governance & also applicable for CLIs (claude code, ) : r/ClaudeCode Skip to main contentZ-GRC a Python library & control panel for LLM governance & also applicable for CLIs (claude code, ) : r/ClaudeCode. Open menu Open navigationGo to Reddit Home. # Z-GRC a Python library & control panel for LLM governance & also applicable for CLIs (claude code, ). Hi, My team and I have been building Z-GRC (Governance, Risk, Control) and this is the first time we're sharing a project as open source. Why we built it ?, Across our projects like AI agents, LLM chatbots, internal tools kept facing into the same pain points everytime like, Unexpected cost spikes at unexpected times, with no idea how much had been used until the bill arrived. No way to control usage in real time applications, Shared LLM credentials floating around inside a project or across the whole org, with no per-user cost control and no coverage usage for DEV, STAGE environments. So we started designing what we wished existed, a governance engine you can drop into any application, whether it's actively in development or already shipped with a oneline line or top of the code file that's all we can can control of the cost consumption of that application. A Python package (z-grc):** the runtime that intercepts LLM API calls. A Next.js control panel (z-grc-application): where you create users, user-groups, quotas and API tokens and visualize everything. Proxy Server ( usingz-grc package): where we can control already build application like claude code, codex(WIP) with proxy server. in simple terms we can control cost in Claude code without touching the source code. It carries compressed payload data with noise added and it embeds everything the package needs which user is this, configuration, quota limits, when to block, where to send telemetry, allof it. The control panel (NextJS application) is what mints these tokens that's where the configuration actually lives and that's where the embedding happens. The package can run as a proxy server in foreground or background mode, so external CLI tools route their LLM traffic through it without code changes with no waiting time and blocks when target cost execeeded. - Repo : https://github.com/zeb-ai/z-grc. Z-GRC Application <> Control Panel:. - Docs: https://zeb-ai.github.io/z-grc-application/.

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