Team with Knowledge Base

from pathlib import Path

from agno.agent import Agent
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIResponses
from agno.team import Team
from agno.tools.websearch import WebSearchTools
from agno.vectordb.lancedb import LanceDb, SearchType

cwd = Path(__file__).parent
tmp_dir = cwd.joinpath("tmp")
tmp_dir.mkdir(parents=True, exist_ok=True)

agno_docs_knowledge = Knowledge(
    vector_db=LanceDb(
        uri=str(tmp_dir.joinpath("lancedb")),
        table_name="agno_docs",
        search_type=SearchType.hybrid,
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
)

web_agent = Agent(
    name="Web Search Agent",
    role="Handle web search requests",
    model=OpenAIResponses(id="gpt-5-mini"),
    tools=[WebSearchTools()],
    instructions=["Always include sources"],
)

team_with_knowledge = Team(
    name="Team with Knowledge",
    members=[web_agent],
    model=OpenAIResponses(id="gpt-5-mini"),
    knowledge=agno_docs_knowledge,
    show_members_responses=True,
    markdown=True,
)

if __name__ == "__main__":
    agno_docs_knowledge.insert(url="https://docs.agno.com/llms-full.txt")
    team_with_knowledge.print_response("Tell me about the Agno framework", stream=True)