feat: 完成 issue #6 LLM 网关 + RAG 模板化(混合网关主编排)
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# -*- coding: utf-8 -*-
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"""iAOP-Core · LLM 网关(LLM Gateway)—— 混合 LLM 的安全出站防线。
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"""iAOP-Core · LLM 网关(LLM Gateway)—— 混合 LLM 的安全出站防线与编排。
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对应 PRD 5.4「④ LLM 网关 + RAG」与 EPIC #6:
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本地 70B(敏感/核心)+ 云端 API(脱敏/通用)混合,敏感数据**本地闭环**。
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当前子模块(Issue #48):
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- dlp DLP 敏感数据拦截引擎:出站内容(query / RAG context / 模型输出)
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发往云端前做敏感规则检查,命中即拦截(目标 100% 拦截),全量审计。
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后续子任务(EPIC #6 拆分,将在本包扩展):
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- 敏感度路由(router)、Prompt 版本管理与幻觉校验中间件、路由准确率评估。
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模块组成:
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- dlp DLP 敏感数据拦截引擎(Issue #48):出站内容(query / RAG context /
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模型输出)发往云端前做敏感规则检查,命中即拦截(目标 100% 拦截),
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全量审计。
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- router 敏感度路由规则引擎(Issue #43 雏形):敏感度分级路由(local/cloud/
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block),模板配置驱动,DLP 拦截即 fail-closed 转 block。
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- prompts Prompt 版本管理(Issue #47 雏形):semver 版本库、运行时绑定、
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一键回滚、变更审计。
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- hallucination 幻觉/事实性校验中间件(Issue #47 雏形):引用溯源 +
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高利害信度阈值 → 人工确认。
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- gateway 混合网关主编排(EPIC #6 主体):路由 → 生成 → 溯源校验 →
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DLP 出站防线,端到端闭环。
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测试:`python -m unittest discover -s tests -v`(在 core/llm-gateway 目录下执行)。
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"""
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__version__ = "0.1.0"
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__version__ = "0.2.0"
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from .dlp import (
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DLP_DEFAULT_RULES,
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@@ -23,12 +29,40 @@ from .dlp import (
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DlpRule,
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DlpRuleKind,
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)
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from .router import (
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RouteDecision,
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RouteTarget,
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RouterRule,
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SensitivityRouter,
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)
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from .prompts import (
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PromptChange,
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PromptRegistry,
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PromptVersion,
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validate_semver,
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)
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from .hallucination import (
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GuardVerdict,
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HallucinationGuard,
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)
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from .gateway import (
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CloudBackend,
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GatewayResult,
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InferenceBackend,
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LLMGateway,
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LocalBackend,
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)
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__all__ = [
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"DlpRuleKind",
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"DlpRule",
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"DlpHit",
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"DlpResult",
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"DlpEngine",
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"DLP_DEFAULT_RULES",
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# dlp
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"DlpRuleKind", "DlpRule", "DlpHit", "DlpResult", "DlpEngine", "DLP_DEFAULT_RULES",
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# router
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"RouteTarget", "RouterRule", "RouteDecision", "SensitivityRouter",
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# prompts
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"PromptVersion", "PromptChange", "PromptRegistry", "validate_semver",
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# hallucination
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"GuardVerdict", "HallucinationGuard",
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# gateway
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"InferenceBackend", "LocalBackend", "CloudBackend",
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"GatewayResult", "LLMGateway",
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]
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