> ## Documentation Index
> Fetch the complete documentation index at: https://ikun.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 多用户多会话聊天

本示例演示了如何运行一个多用户、多会话的聊天程序。

在本例中，我们有 3 位用户和 4 个会话。

* 用户 1 有 2 个会话。
* 用户 2 有 1 个会话。
* 用户 3 有 1 个会话。

## 代码

```python cookbook/agent_concepts/memory/11_multi_user_multi_session_chat.py theme={null}

import asyncio

from agno.agent.agent import Agent
from agno.memory.v2.db.sqlite import SqliteMemoryDb
from agno.memory.v2.memory import Memory
from agno.models.google.gemini import Gemini
from agno.storage.sqlite import SqliteStorage

agent_storage = SqliteStorage(
    table_name="agent_sessions", db_file="tmp/persistent_memory.db"
)
memory_db = SqliteMemoryDb(table_name="memory", db_file="tmp/memory.db")

memory = Memory(db=memory_db)

# 为此示例重置内存
memory.clear()

user_1_id = "user_1@example.com"
user_2_id = "user_2@example.com"
user_3_id = "user_3@example.com"

user_1_session_1_id = "user_1_session_1"
user_1_session_2_id = "user_1_session_2"
user_2_session_1_id = "user_2_session_1"
user_3_session_1_id = "user_3_session_1"

chat_agent = Agent(
    model=Gemini(id="gemini-2.0-flash-exp"),
    storage=agent_storage,
    memory=memory,
    enable_user_memories=True,
)


async def run_chat_agent():
    await chat_agent.aprint_response(
        "My name is Mark Gonzales and I like anime and video games.",
        user_id=user_1_id,
        session_id=user_1_session_1_id,
    )
    await chat_agent.aprint_response(
        "I also enjoy reading manga and playing video games.",
        user_id=user_1_id,
        session_id=user_1_session_1_id,
    )

    # 与用户 1 - 会话 2 进行聊天
    await chat_agent.aprint_response(
        "I'm going to the movies tonight.",
        user_id=user_1_id,
        session_id=user_1_session_2_id,
    )

    # 与用户 2 进行聊天
    await chat_agent.aprint_response(
        "Hi my name is John Doe.", user_id=user_2_id, session_id=user_2_session_1_id
    )
    await chat_agent.aprint_response(
        "I'm planning to hike this weekend.",
        user_id=user_2_id,
        session_id=user_2_session_1_id,
    )

    # 与用户 3 进行聊天
    await chat_agent.aprint_response(
        "Hi my name is Jane Smith.", user_id=user_3_id, session_id=user_3_session_1_id
    )
    await chat_agent.aprint_response(
        "I'm going to the gym tomorrow.",
        user_id=user_3_id,
        session_id=user_3_session_1_id,
    )

    # 继续与用户 1 的对话
    # 代理应该考虑到用户 1 的所有记忆。
    await chat_agent.aprint_response(
        "What do you suggest I do this weekend?",
        user_id=user_1_id,
        session_id=user_1_session_1_id,
    )


if __name__ == "__main__":
    # 与用户 1 - 会话 1 进行聊天
    asyncio.run(run_chat_agent())

    user_1_memories = memory.get_user_memories(user_id=user_1_id)
    print("User 1's memories:")
    for i, m in enumerate(user_1_memories):
        print(f"{i}: {m.memory}")

    user_2_memories = memory.get_user_memories(user_id=user_2_id)
    print("User 2's memories:")
    for i, m in enumerate(user_2_memories):
        print(f"{i}: {m.memory}")

    user_3_memories = memory.get_user_memories(user_id=user_3_id)
    print("User 3's memories:")
    for i, m in enumerate(user_3_memories):
        print(f"{i}: {m.memory}")
```

## 使用方法

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="设置您的 API 密钥">
    ```bash theme={null}
    export GOOGLE_API_KEY=xxx
    ```
  </Step>

  <Step title="安装库">
    ```bash theme={null}
    pip install -U agno google-generativeai anthropic
    ```
  </Step>

  <Step title="运行示例">
    <CodeGroup>
      ```bash Mac theme={null}
      python cookbook/agent_concepts/memory/11_multi_user_multi_session_chat.py
      ```

      ```bash Windows theme={null}
      python cookbook/agent_concepts/memory/11_multi_user_multi_session_chat.py
      ```
    </CodeGroup>
  </Step>
</Steps>