这是一个带有知识工具的团队推理示例。

在团队领导者上启用推理选项可以通过选择性地在需要时调用更深入的推理来优化代理分配，并增强多代理协作。

​
代码

cookbook/reasoning/teams/knowledge_tool_team.py
from textwrap import dedent

from agno.agent import Agent
from agno.knowledge.url import UrlKnowledge
from agno.models.openai import OpenAIChat
from agno.team.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.knowledge import KnowledgeTools
from agno.tools.yfinance import YFinanceTools
from agno.vectordb.lancedb import LanceDb, SearchType

agno_docs = UrlKnowledge(
    urls=["https://www.paulgraham.com/read.html"],
    # 使用 LanceDB 作为向量数据库并将嵌入存储在 `agno_docs` 表中
    vector_db=LanceDb(
        uri="tmp/lancedb",
        table_name="agno_docs",
        search_type=SearchType.hybrid,
    ),
)

knowledge_tools = KnowledgeTools(
    knowledge=agno_docs,
    think=True,
    search=True,
    analyze=True,
    add_few_shot=True,
)

web_agent = Agent(
    name="Web Search Agent",
    role="处理网络搜索请求",
    model=OpenAIChat(id="gpt-4o-mini"),
    tools=[DuckDuckGoTools()],
    instructions="始终包含来源",
    add_datetime_to_instructions=True,
)

finance_agent = Agent(
    name="Finance Agent",
    role="处理财务数据请求",
    model=OpenAIChat(id="gpt-4o-mini"),
    tools=[
        YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)
    ],
    add_datetime_to_instructions=True,
)

team_leader = Team(
    name="推理金融团队",
    mode="coordinate",
    model=OpenAIChat(id="gpt-4o"),
    members=[
        web_agent,
        finance_agent,
    ],
    tools=[knowledge_tools],
    instructions=[
        "只输出最终答案，不包含其他文本。",
        "使用表格展示数据",
    ],
    markdown=True,
    show_members_responses=True,
    enable_agentic_context=True,
    add_datetime_to_instructions=True,
    success_criteria="团队已成功完成任务。",
    debug_mode=True,
)


def run_team(task: str):
    # 首次运行后注释掉此行
    agno_docs.load(recreate=True)
    team_leader.print_response(
        task,
        stream=True,
        stream_intermediate_steps=True,
        show_full_reasoning=True,
    )


if __name__ == "__main__":
    run_team("保罗·格雷厄姆在这篇论文中谈到阅读的必要性是什么？")

​
用法

1

创建虚拟环境

打开 Terminal 并创建一个 python 虚拟环境。

python3 -m venv .venv
source .venv/bin/activate
2

设置您的 API 密钥

export OPENAI_API_KEY=xxx
3

安装库

pip install -U openai agno
4

运行示例

python cookbook/reasoning/teams/knowledge_tool_team.py