agent-seal-lite

agent-seal / AI Agent 审计追踪

Tamper-proof audit trail for AI agents / 防篡改的 AI Agent 审计追踪 — three-line integration (zero-code hook, @observe decorator, or framework callback). EU AI Act Article 12 ready. / 三行代码即可集成（零代码 Hook、@observe 装饰器或框架回调）。已为 EU AI Act 第 12 条做好准备。

English | 中文

agent-seal records every decision, tool call, and model request an AI agent makes into an immutable, SHA-256 hash-chained log. Each event is cryptographically linked to the previous one — tamper with a single byte and the entire chain breaks, detected instantly on verification. Designed for EU AI Act Article 12 (record-keeping, effective August 2026), SOC 2, and HIPAA audit requirements.

agent-seal 将 AI Agent 的每一次决策、工具调用和模型请求记录到一个不可篡改的、由 SHA-256 哈希链串联的日志中。每个事件都通过密码学方式与前一个事件链接——篡改任意一个字节，整条链就会断裂，验证时即刻被发现。专为 EU AI Act 第 12 条（记录保存，2026 年 8 月生效）、SOC 2 和 HIPAA 审计要求而设计。

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Integration Methods / 集成方式 🆕

agent-seal v1.1 offers three integration paths — from zero-code to deep framework hooks. Pick the one that fits your stack.

agent-seal v1.1 提供三种集成方式——从零代码到深度框架钩子。选择适合你技术栈的方式。

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Quick Start / 快速开始

1. Zero-Code (Global Hook) / 零代码（全局 Hook） 🆕

Install agent-seal and start the server. Every Python process on the machine is automatically traced — no code changes.

安装 agent-seal 并启动服务。机器上的每个 Python 进程都会被自动追踪——无需任何代码变更。

pip install agent-seal
agent-seal server
# Dashboard at http://localhost:8081 — all LLM calls appear automatically
# 控制台地址：http://localhost:8081 — 所有 LLM 调用自动出现

The global sitecustomize.py hook intercepts httpx-based LLM calls (OpenAI, Anthropic, and any OpenAI-compatible API) in every Python process. Works with frameworks, scripts, notebooks — anything that imports openai or anthropic.

全局 sitecustomize.py Hook 会在每个 Python 进程中拦截基于 httpx 的 LLM 调用（OpenAI、Anthropic 及任何兼容 OpenAI 的 API）。适用于框架、脚本、Notebook——任何导入了 openai 或 anthropic 的代码。

2. @observe Decorator / @observe 装饰器 🆕

Trace any Python function with one decorator. Inputs, outputs, execution time, and nested call trees are recorded into the audit trail.

一行装饰器即可追踪任意 Python 函数。输入、输出、执行时间和嵌套调用树都会被记录到审计追踪中。

from agent_seal import observe, set_engine
from agent_seal.engine import AuditEngine

engine = AuditEngine("sqlite://audit.db")
set_engine(engine)

@observe(name="process_refund", metadata={"tier": "critical"})
def process_refund(order_id: str, amount: float) -> dict:
    user = lookup_user(order_id)
    result = issue_refund(user, amount)
    return result

# Nested calls are auto-linked as parent-child spans
# 嵌套调用自动关联为父子 Span
@observe(name="lookup_user")
def lookup_user(order_id: str) -> dict: ...

@observe(name="issue_refund")
def issue_refund(user: dict, amount: float) -> dict: ...

process_refund("ORD-123", 45.00)
# → 3 audit events: process_refund → lookup_user, process_refund → issue_refund
#   with parent_span_id linking inner calls to outer
# → 3 个审计事件：process_refund → lookup_user, process_refund → issue_refund
#   通过 parent_span_id 将内部调用链接到外部调用

3. LangChain Callback / LangChain 回调 🆕

One line registers a callback handler that audits every LLM call, tool invocation, chain step, and agent decision.

一行代码注册回调处理器，审计每一次 LLM 调用、工具调用、Chain 步骤和 Agent 决策。

from agent_seal.hooks.langchain import LangChainAuditHandler

handler = LangChainAuditHandler(agent_id="my-agent")

from langchain.agents import AgentExecutor
executor = AgentExecutor(agent=agent, tools=tools, callbacks=[handler])

Token counts, latency, model name, and errors are captured automatically.

Token 消耗、延迟、模型名称和错误信息均被自动捕获。

4. Hermes Middleware / Hermes 中间件 🆕

Native support for the Hermes Agent framework. Zero-config — install and it auto-instruments all agent actions.

原生支持 Hermes Agent 框架。零配置——安装后即自动插桩所有 Agent 动作。

# hermes_middleware.py is auto-detected
# hermes_middleware.py 会被自动检测
# No code changes needed in your Hermes agent
# 无需修改你的 Hermes Agent 代码

Note: langchain and langchain-core are optional dependencies. Install them separately: pip install langchain langchain-core. When unavailable, the module imports cleanly but raises a friendly RuntimeError with install instructions.

注意：langchain 和 langchain-core 是可选依赖。需单独安装：pip install langchain langchain-core。当这些包不可用时，模块可以正常导入，但会抛出一个带有安装指引的友好 RuntimeError。

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Key Features / 核心特性

Core Audit Trail / 核心审计追踪

• Immutable Hash Chain / 不可篡改的哈希链 — SHA-256 chain linking every event. Break one link = tampering detected. / SHA-256 链条串联每个事件。断裂任一环节 = 篡改即被发现。
• Ed25519 Digital Signatures / Ed25519 数字签名 — Cryptographic non-repudiation per event. / 每个事件的密码学不可否认性。
• AES-256-GCM Encryption / AES-256-GCM 加密 — Transparent encryption at rest. / 透明的静态数据加密。
• PII Redaction / PII 脱敏 — Automatic PII scrubbing (emails, phones, SSNs, credit cards) before storage. / 存储前自动脱敏 PII（邮箱、电话、社保号、信用卡）。

v1.1 Highlights / v1.1 亮点 🆕

• 🆕 Zero-Code Global Hook / 零代码全局 Hook — sitecustomize.py auto-instruments all Python processes. No imports, no decorators, no config. / sitecustomize.py 自动插桩所有 Python 进程。无需导入、无需装饰器、无需配置。
• 🆕 @observe Decorator / @observe 装饰器 — Lightweight function tracing with nested span trees, latency, and custom metadata. / 轻量级函数追踪，支持嵌套 Span 树、延迟和自定义元数据。
• 🆕 LangChain CallbackHandler / LangChain 回调处理器 — Native LangChainAuditHandler for LCEL chains, agents, and tools. / 原生 LangChainAuditHandler，支持 LCEL Chain、Agent 和工具。
• 🆕 Hermes Middleware / Hermes 中间件 — First-class Hermes Agent framework integration. / 一等公民级别的 Hermes Agent 框架集成。
• 🆕 Enhanced SPA Dashboard / 增强版 SPA 控制台 — Expandable event details, smart previews, model/latency columns, binary output filtering. / 可展开的事件详情、智能预览、模型/延迟列、二进制输出过滤。

Governance & Compliance / 治理与合规

• Policy Engine / 策略引擎 — YAML-based guardrail rules. Block dangerous tool calls before execution. / 基于 YAML 的护栏规则。在危险工具调用执行前将其阻止。
• Evidence Bundles / 证据包 — Export signed .zip bundles for external auditors with SHA-256 verification. / 导出带签名的 .zip 证据包，供外部审计师使用，附带 SHA-256 验证。
• EU AI Act Reports / EU AI Act 报告 — Generate Article 12 compliance reports on demand (agent-seal report <agent>). / 按需生成第 12 条合规报告（agent-seal report <agent>）。
• Prompt Version Tracking / Prompt 版本追踪 — Git-like prompt history with diffs — who changed what, when, and why. / 类 Git 的 Prompt 历史记录，支持差异对比——谁在何时因何原因修改了什么。

Observability / 可观测性

• LLM Auto-Tracing / LLM 自动追踪 — Monkey-patch instrumentation for OpenAI, Anthropic, OpenTelemetry. Token counts, latency, cost. / 针对 OpenAI、Anthropic、OpenTelemetry 的 Monkey-patch 插桩。Token 消耗、延迟、费用。
• Prometheus Metrics / Prometheus 指标 — GET /metrics exporting audit_events_total, audit_sessions_active, audit_policy_denials_total. / GET /metrics 导出 audit_events_total、audit_sessions_active、audit_policy_denials_total。
• Slack + Email Alerts / Slack + 邮件告警 — Notifications for policy blocks, integrity failures, error spikes. / 针对策略阻止、完整性失败、错误激增的通知。

Storage / 存储

• JSONL — Zero-dependency file backend for development. / 零依赖文件后端，用于开发环境。
• SQLite — Single-file embedded database for small-scale deployments. / 单文件嵌入式数据库，用于小规模部署。
• PostgreSQL — Production-grade concurrent-safe storage with connection pooling and Alembic migrations. / 生产级并发安全存储，支持连接池和 Alembic 迁移。

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Installation / 安装

pip install agent-seal

With PostgreSQL support / 带 PostgreSQL 支持：

pip install agent-seal[postgresql]

Or everything / 或安装全部：

pip install agent-seal[all]

From source / 从源码安装

git clone https://github.com/user/agent-seal.git
cd agent-seal
pip install -e .

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Dashboard / 控制台 🆕

📸 Screenshot placeholder — Dashboard screenshot coming soon. / 截图占位 — 控制台截图即将上线。

The SPA Dashboard provides real-time visibility into your audit trail:

SPA 控制台为你的审计追踪提供实时可视性：

• Event list with expandable detail rows — inputs, outputs, metadata / 事件列表，支持展开详情行——输入、输出、元数据
• Smart previews — truncated long content with "Show more" / 智能预览——截断长内容并显示"展开更多"
• Model & latency columns — at-a-glance performance monitoring / 模型与延迟列——一目了然的性能监控
• Binary/garbled output filtering — clean display of structured data / 二进制/乱码输出过滤——结构化数据的清晰展示
• SSE live updates — new events stream in real time, no page refresh / SSE 实时更新——新事件实时流式推送，无需刷新页面

Start the dashboard: agent-seal server → open http://localhost:8081

启动控制台：agent-seal server → 打开 http://localhost:8081

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Architecture / 架构

┌──────────────────────────────────────────────────────────────┐
│                   INTEGRATION LAYER / 集成层                   │
│                                                              │
│  ┌─────────────────┐  ┌──────────────┐  ┌──────────────────┐ │
│  │  Zero-Code Hook  │  │  @observe    │  │ Framework Hooks  │ │
│  │  (sitecustomize) │  │  (decorator) │  │ (LangChain/Hermes)│ │
│  │                 │  │              │  │                  │ │
│  │  Auto-intercept  │  │  Manual trace│  │  Native callback │ │
│  │  all LLM calls   │  │  any function│  │  integration     │ │
│  └────────┬────────┘  └──────┬───────┘  └────────┬─────────┘ │
│           │                  │                    │           │
└───────────┼──────────────────┼────────────────────┼───────────┘
            │                  │                    │
            ▼                  ▼                    ▼
┌──────────────────────────────────────────────────────────────┐
│                   AUDIT ENGINE / 审计引擎                      │
│                                                              │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────────┐ │
│  │Hash Chain│  │ Ed25519  │  │AES-256-GCM│  │ PII Redact   │ │
│  │ SHA-256  │  │Signatures│  │Encryption │  │              │ │
│  └──────────┘  └──────────┘  └──────────┘  └──────────────┘ │
│                                                              │
│  ┌──────────────────────────────────────────────────────┐    │
│  │           Storage Backends / 存储后端                  │    │
│  │     JSONL (dev)  │  SQLite (small)  │  PostgreSQL     │    │
│  └──────────────────────────────────────────────────────┘    │
└───────────────────────────┬──────────────────────────────────┘
                            │
          ┌─────────────────┼─────────────────┐
          ▼                 ▼                 ▼
   ┌────────────┐  ┌──────────────┐  ┌──────────────┐
   │  REST API  │  │SPA Dashboard │  │  Prometheus   │
   │  /api/v1/* │  │  :8081       │  │  /metrics     │
   └────────────┘  └──────────────┘  └──────────────┘

agent_seal/
├── trail.py              # Hash-chained audit trail (entry point) / 哈希链审计追踪（入口）
├── engine.py             # Unified AuditEngine (JSONL/SQLite/PG) / 统一审计引擎
├── observe.py            # @observe decorator / @observe 装饰器 🆕
├── config.py             # 12-Factor configuration / 12-Factor 配置
├── cli.py                # CLI commands / CLI 命令
├── core/
│   ├── chain.py          # SessionChain — per-session hash chains / 按会话的哈希链
│   ├── storage.py        # Storage backends (JSONL, SQLite, PostgreSQL) / 存储后端
│   ├── crypto.py         # Ed25519 signing / Ed25519 签名
│   ├── encrypted.py      # AES-256-GCM encryption / AES-256-GCM 加密
│   ├── redact.py         # PII redaction / PII 脱敏
│   └── rotation.py       # Log rotation / 日志轮转
├── server/
│   ├── app.py            # FastAPI application / FastAPI 应用
│   ├── hermes_middleware.py  # Hermes Agent middleware / Hermes Agent 中间件 🆕
│   └── routes/           # REST endpoints / REST 端点
├── policy/engine.py      # YAML-based guardrail rules / 基于 YAML 的护栏规则
├── tracing/              # LLM auto-instrumentation / LLM 自动插桩 (OpenAI, Anthropic, OTel)
├── hooks/
│   ├── langchain.py      # LangChain CallbackHandler / LangChain 回调处理器 🆕
│   ├── hermes_worker.py  # Hermes worker hook / Hermes Worker 钩子 🆕
│   ├── slack.py          # Slack notifications / Slack 通知
│   └── email.py          # Email alerts / 邮件告警
├── integrations/         # LangChain, MCP server adapters / LangChain、MCP 服务适配器
├── models/               # SQLAlchemy models / SQLAlchemy 模型
├── evidence.py           # Evidence bundle export / 证据包导出
├── report.py             # EU AI Act compliance reports / EU AI Act 合规报告
├── prompt_version.py     # Prompt version tracking / Prompt 版本追踪
├── replay.py             # Trail replay / 追踪回放
└── regression.py         # Regression testing / 回归测试

For detailed architecture see docs/architecture-v1.md. / 详细架构请参阅 docs/architecture-v1.md。

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CLI Reference / CLI 参考

agent-seal <command> [options]

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REST API

Start the server / 启动服务：

agent-seal server
# OR: uvicorn agent_seal.server.app:app --host 0.0.0.0 --port 8081

Endpoints / 端点：

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Configuration / 配置

All settings via environment variables (12-Factor App). See .env.example for a complete template.

所有设置均通过环境变量配置（12-Factor App）。完整模板参见 .env.example。

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Docker Deployment / Docker 部署

# 1. Copy and configure environment
# 1. 复制并配置环境变量
cp .env.example .env
# Edit .env — set POSTGRES_PASSWORD, AGENT_SEAL_SECRET_KEY, API keys
# 编辑 .env —— 设置 POSTGRES_PASSWORD、AGENT_SEAL_SECRET_KEY、API 密钥

# 2. Start the stack
# 2. 启动服务栈
docker compose up -d

# 3. Verify
# 3. 验证
curl http://localhost/health

The stack includes / 服务栈包含：

• nginx — Reverse proxy (port 80/443) + SPA static files / 反向代理（80/443 端口）+ SPA 静态文件
• api — FastAPI application server (internal port 8081) / FastAPI 应用服务器（内部端口 8081）
• db — PostgreSQL 15 (audit data + prompt versions) / PostgreSQL 15（审计数据 + Prompt 版本）
• redis — Caching, rate limiting (optional) / 缓存、速率限制（可选）

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Development / 开发

Quick Start / 快速开始

# Clone & install
# 克隆并安装
git clone https://github.com/user/agent-seal.git && cd agent-seal
pip install -e ".[all]"

# Run tests
# 运行测试
pytest tests/ -v

# Code quality
# 代码质量
ruff check .
mypy agent_seal/

# Run demo
# 运行演示
python examples/demo.py

Embedded PostgreSQL (development only) / 嵌入式 PostgreSQL（仅开发环境）

For local development with PostgreSQL, the project ships pg_embedded/ — an embedded PostgreSQL 17.10 instance that runs on-demand. This is a development tool, not for production.

为便于本地使用 PostgreSQL 进行开发，项目内置了 pg_embedded/——一个按需启动的嵌入式 PostgreSQL 17.10 实例。这是一个开发工具，请勿用于生产环境。

Security note / 安全说明: The embedded PostgreSQL uses trust authentication and listens on 127.0.0.1/::1 only — no external network access. For production, use the Docker Compose stack which configures proper authentication. / 嵌入式 PostgreSQL 使用 trust 认证，仅监听 127.0.0.1/::1——无外部网络访问。生产环境请使用 Docker Compose 栈，其已配置了正确的认证方式。

# One-time initialization (creates data/ directory and database)
# 一次性初始化（创建 data/ 目录和数据库）
pg_embedded/init.bat

# Start on demand
# 按需启动
pg_embedded/start.bat

# Stop when done
# 用完后停止
pg_embedded/stop.bat

Configure via .env / 通过 .env 配置：

AGENT_SEAL_DB_URL=postgresql://audit:***@127.0.0.1:5432/agent_seal
AGENT_SEAL_STORAGE_BACKEND=postgresql

Why embedded? Avoids Docker/brew/system-PG dependency for quick local testing. Why stop it? 942 MB never-idle memory. Start it only when you need PG, stop it when you don't. For always-on development, prefer docker compose up -d db.

为什么用嵌入式？ 避免依赖 Docker/brew/系统 PG 即可快速本地测试。为什么要停止它？ 942 MB 永不释放的内存。只在需要 PG 时启动，不需要时停止。对于持续运行的开发环境，推荐使用 docker compose up -d db。

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License / 许可证

MIT — see LICENSE for details. / 详见 LICENSE。