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fix tool name, add more callbacks, fix bugs
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config.yaml.full

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@@ -67,8 +67,8 @@ tool:
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computer_sandbox:
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url: #mcp sse/streamable-http url
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api_key: #mcp api key
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# [optional] for Volcengine LLM Firewall https://www.volcengine.com/product/LLM-FW
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llm_firewall:
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# [optional] for Volcengine LLM Shield https://www.volcengine.com/product/LLM-FW
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llm_shield:
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app_id:
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docs/content/5.tools/1.builtin-tools.md

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@@ -17,10 +17,9 @@ VeADK 中集成了多个火山引擎提供的工具:
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| [`image_generate`](https://www.volcengine.com/docs/82379/1541523) | 图片生成 | `from veadk.tools.builtin_tools.image_generate import image_generate` |
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| [`image_edit`](https://www.volcengine.com/docs/82379/1541523) | 图片编辑(图生图) | `from veadk.tools.builtin_tools.image_edit import image_edit` |
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| [`video_generate`](https://www.volcengine.com/docs/82379/1520757) | 视频生成 | `from veadk.tools.builtin_tools.video_generate import video_generate` |
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| [`LLMFirewallPlugin`](https://www.volcengine.com/docs/84990/1520619) | 模型防火墙 | `from veadk.tools.builtin_tools.llm_firewall import LLMFirewallPlugin` |
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::note
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使用 `vesearch` 前,请先在火山引擎控制台创建一个搜索智能体,并获取其 Endpoint;使用 `LLMFirewallPlugin` 前,请先购买实例并添加资产,并获取其 AppID
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使用 `vesearch` 前,请先在火山引擎控制台创建一个搜索智能体,并获取其 Endpoint。
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::
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## 使用
@@ -46,28 +45,6 @@ response = asyncio.run(runner.run(messages="今天的新闻"))
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print(response)
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```
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以下示例展示了如何在 VeADK 中集成并调用内置的模型护栏插件 `LLMFirewallPlugin`,以对用户输入进行审计:
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```python [agent.py]
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import asyncio
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from veadk import Agent, Runner
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from veadk.tools.builtin_tools.llm_firewall import LLMFirewallPlugin
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governance = LLMFirewallPlugin()
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agent = Agent(
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name="robot",
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description="A robot can help user.",
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instruction="Talk with user friendly.",
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before_model_callback=governance.before_model_callback
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)
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runner = Runner(agent=agent)
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response = asyncio.run(runner.run(messages="网上都说A地很多骗子和小偷,他们的典型伎俩..."))
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print(response) # Your request has been blocked due to: Model Misuse. Please modify your input and try again.
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```
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## 系统工具
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---
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title: 护栏工具
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description: VeADK Guardrails
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navigation:
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icon: i-lucide-wrench
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---
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## 概述
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VeADK 基于 Agent 的插件机制,提供了内容安全护栏工具 `content_safety`。该工具通过以下回调函数嵌入 Agent 的执行流程,实现多阶段内容审计:
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- Before Agent Callback
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- After Agent Callback
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- Before Model Callback
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- After Model Callback
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- Before Tool Callback
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- After Tool Callback
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在这些回调中,`content_safety` 基于[火山大模型应用防火墙](https://www.volcengine.com/product/LLM-FW)服务,对 Agent 生命周期的各个阶段进行内容检测与合规审查,确保生成与交互内容安全可靠。
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::note
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使用 `content_safety` 前,请先购买实例并添加资产,并获取其 AppID。
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::
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## 使用
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以下示例展示了如何在 VeADK 中集成并调用内置的模型护栏工具 `content_safety`,以对 Agent 的执行过程进行审计:
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```python [agent.py]
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import asyncio
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from veadk import Agent, Runner
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from veadk.tools.builtin_tools.llm_shield import content_safety
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agent = Agent(
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name="robot",
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description="A robot can help user.",
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instruction="Talk with user friendly.",
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before_agent_callback=content_safety.before_agent_callback,
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before_model_callback=content_safety.before_model_callback,
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after_model_callback=content_safety.after_model_callback,
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before_tool_callback=content_safety.before_tool_callback,
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after_tool_callback=content_safety.after_tool_callback,
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after_agent_callback=content_safety.after_agent_callback
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)
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runner = Runner(agent=agent)
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response = asyncio.run(runner.run(messages="网上都说A地很多骗子和小偷,他们的典型伎俩..."))
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print(response) # Your request has been blocked due to: Model Misuse. Please modify your input and try again.
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```

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