Teams with Knowledge

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.hackernews import HackerNewsTools
from agno.vectordb.lancedb import LanceDb

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",
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
)

hackernews_agent = Agent(
    name="HackerNews Agent",
    role="Search HackerNews for tech news",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[HackerNewsTools()],
    instructions=["Always include sources"],
)

team_with_knowledge = Team(
    name="Team with Knowledge",
    members=[hackernews_agent],
    model=OpenAIResponses(id="gpt-5.2"),
    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)

uv pip install -U agno lancedb openai