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‎docs/docs/agent/agent-to-agent.md‎

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@@ -62,64 +62,64 @@ flowchart LR
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3. 配置服务器参数（端口、主机等）
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=== "代码"
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```python title="server.py" linenums="1" hl_lines="5"
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from google.adk.a2a.utils.agent_to_a2a import to_a2a
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from veadk import Agent
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from veadk.tools.demo_tools import get_city_weather
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agent = Agent(
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name="weather_agent",
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description="An agent that can get the weather of a city",
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tools=[get_city_weather],
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)
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app = to_a2a(agent=agent)
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```
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```python title="server.py" linenums="1" hl_lines="1 11"
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from google.adk.a2a.utils.agent_to_a2a import to_a2a
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from veadk import Agent
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from veadk.tools.demo_tools import get_city_weather
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agent = Agent(
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name="weather_agent",
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description="An agent that can get the weather of a city",
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tools=[get_city_weather],
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)
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app = to_a2a(agent=agent)
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```
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### 客户端集成
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1. 导入 RemoteVeAgent 类
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2. 配置远程 Agent 连接参数
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3. 在 Root Agent 中添加 Remote Agent 作为 Sub Agent
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=== "代码"
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```python title="client.py" linenums="1"
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from veadk import Agent, Runner
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from veadk.a2a.remote_ve_agent import RemoteVeAgent
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async def main(prompt: str) -> str:
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"""Main function for run an agent.
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```python title="client.py" linenums="1"
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from veadk import Agent, Runner
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from veadk.a2a.remote_ve_agent import RemoteVeAgent
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Args:
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prompt (str): The prompt to run.
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async def main(prompt: str) -> str:
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"""Main function for run an agent.
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Returns:
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str: The response from the agent.
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"""
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weather_agent = RemoteVeAgent(
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name="weather_agent",
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url="http://localhost:8000/", # <--- url of A2A server
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)
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print(f"Remote agent name is {weather_agent.name}.")
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print(f"Remote agent description is {weather_agent.description}.")
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Args:
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prompt (str): The prompt to run.
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agent = Agent(
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name="root_agent",
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description="An assistant for fetching weather.",
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instruction="You are a helpful assistant. You can invoke weather agent to get weather information.",
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sub_agents=[weather_agent],
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)
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Returns:
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str: The response from the agent.
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"""
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weather_agent = RemoteVeAgent(
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name="weather_agent",
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url="http://localhost:8000/", # <--- url of A2A server
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)
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print(f"Remote agent name is {weather_agent.name}.")
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print(f"Remote agent description is {weather_agent.description}.")
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agent = Agent(
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name="root_agent",
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description="An assistant for fetching weather.",
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instruction="You are a helpful assistant. You can invoke weather agent to get weather information.",
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sub_agents=[weather_agent],
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)
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runner = Runner(agent=agent)
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response = await runner.run(messages=prompt)
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runner = Runner(agent=agent)
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response = await runner.run(messages=prompt)
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return response
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return response
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if __name__ == "__main__":
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import asyncio
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if __name__ == "__main__":
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import asyncio
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response = asyncio.run(main("What is the weather like of Beijing?"))
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print(response)
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```
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response = asyncio.run(main("What is the weather like of Beijing?"))
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print(response)
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```
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### 交互流程
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下图为示例对应的交互流程图
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```mermaid
@@ -195,52 +195,52 @@ veADK 的 A2A 鉴权机制提供了灵活的认证选项，支持标准的 Beare
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=== "代码"
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```python title="client.py" linenums="1"
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# <...code truncated...>
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# <...code truncated...>
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# 创建自定义的 httpx.AsyncClient 实例
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custom_client = httpx.AsyncClient(
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# 基础 URL 设置
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base_url="https://vefaas.example.com/agents/",
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# 超时设置（秒）
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timeout=30.0,
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# 连接池设置
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limits=httpx.Limits(
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max_connections=100, # 最大并发连接数
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max_keepalive_connections=20, # 最大保活连接数
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keepalive_expiry=60.0, # 保活连接过期时间
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),
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# 重试配置（需要 httpx >= 0.24.0）
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follow_redirects=True, # 跟随重定向
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# 创建自定义的 httpx.AsyncClient 实例
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custom_client = httpx.AsyncClient(
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# 基础 URL 设置
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base_url="https://vefaas.example.com/agents/",
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# 超时设置（秒）
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timeout=30.0,
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# 连接池设置
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limits=httpx.Limits(
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max_connections=100, # 最大并发连接数
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max_keepalive_connections=20, # 最大保活连接数
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keepalive_expiry=60.0, # 保活连接过期时间
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),
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# 重试配置（需要 httpx >= 0.24.0）
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follow_redirects=True, # 跟随重定向
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# 自定义默认请求头
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headers={
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"User-Agent": "Custom-VeADK-Client/1.0",
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"X-Custom-Header": "custom-value"
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},
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# SSL 验证选项（生产环境中建议保持默认的 True）
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verify=True,
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# 代理配置（如需使用代理）
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proxies="http://proxy.example.com:8080",
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# 并发请求设置
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http2=True, # 启用 HTTP/2 支持
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)
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# 自定义默认请求头
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headers={
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"User-Agent": "Custom-VeADK-Client/1.0",
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"X-Custom-Header": "custom-value"
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},
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# 创建 RemoteVeAgent 实例时，将自定义客户端传递给 httpx_client 参数
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remote_agent = RemoteVeAgent(
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name="a2a_agent",
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url="https://example.com/a2a",
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auth_token="your_token_here",
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auth_method="header",
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httpx_client=custom_client,
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)
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# <...code truncated...>
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# SSL 验证选项（生产环境中建议保持默认的 True）
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verify=True,
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# 代理配置（如需使用代理）
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proxies="http://proxy.example.com:8080",
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# 并发请求设置
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http2=True, # 启用 HTTP/2 支持
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)
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# 创建 RemoteVeAgent 实例时，将自定义客户端传递给 httpx_client 参数
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remote_agent = RemoteVeAgent(
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name="a2a_agent",
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url="https://example.com/a2a",
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auth_token="your_token_here",
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auth_method="header",
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httpx_client=custom_client,
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)
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# <...code truncated...>
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```
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‎docs/docs/agent/agent.md‎

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如果您想使用本地模型或其他提供商的模型，可以在初始化时指定模型相关配置：
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```python title="agent.py" linenums="1" hl_lines="4-6"
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```python title="agent.py" linenums="1" hl_lines="4-7"
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from veadk import Agent
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agent = Agent(
@@ -98,7 +98,7 @@ agent = Agent(model=llm)
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此外，您还可以根据[火山引擎方舟大模型平台](https://www.volcengine.com/product/ark)的能力，指定一些[额外选项](https://www.volcengine.com/docs/82379/1494384?lang=zh)，例如您可以禁用豆包 1.6 系列模型的思考能力，以实现更加快速的响应：
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```python title="agent.py" linenums="1" hl_lines="7-11"
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```python title="agent.py" linenums="1" hl_lines="7"
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import asyncio
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from veadk import Agent, Runner

‎docs/docs/knowledgebase/overview.md‎

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@@ -16,7 +16,7 @@ KnowledgeBase 在 veadk 框架中扮演 Agent 的外部知识库 角色。它像
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4) 与 Agent 无缝集成 ：通过在创建 Agent 时传入 knowledgebase=kb 参数，Agent 就能自动利用这个知识库来增强其回答能力。
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## 使用方法：
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## 使用方法
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以下是使用 KnowledgeBase 的典型步骤，并对比了 viking 和 opensearch 的配置差异。
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‎docs/docs/memory/long-term-memory.md‎

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)
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```
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### ...
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## 记忆管理
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### 添加会话到长期记忆
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- 设计长期记忆数据结构以支持多会话信息保存；
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- 配合短期记忆使用，实现会话内上下文快速访问。
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```
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# 占位: 单租户多会话长期记忆结构示例
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```
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### 示例
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以下示例演示了一个完整的流程：Runner1 告诉 Agent 一个信息（"My favorite project is Project Alpha"），将会话存入记忆，然后创建一个全新的 Runner2，验证其能否回答相关问题。

‎docs/docs/quickstart.md‎

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```
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2. 配置`uv`环境
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本项目使用`uv`进行构建，（了解如何[安装`uv`](https://docs.astral.sh/uv/getting-started/installation/)）
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```bash
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```plantext
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# 选择 3.10及以上版本
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uv venv --python 3.10
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```
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source .venv/bin/activate
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```
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=== "Windows CMD"
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```bash
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```cmd
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.venv\Scripts\activate.bat
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```
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=== "Windows PowerShell"
49-
```bash
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```powershell
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.venv\Scripts\activate.ps1
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```
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安装 VeADK

‎docs/docs/references/contributing.md‎

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`pre-commit` 将在您提交代码前进行一系列检查，例如代码格式规范检查、密钥泄漏检查等。未使用 `pre-commit` 检查过的提交将不会通过 Github 中的 CI/CD 工作流检查，这意味着代码将不会被合并。
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```bash [Terminal]
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```bash
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pip install pre-commit
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pre-commit install .

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