knowledge_tool.py
"""
Knowledge Tool
=============================
Demonstrates knowledge tool.
"""
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.team.team import Team
from agno.vectordb.pgvector import PgVector
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
kb = Knowledge(
vector_db=PgVector(
table_name="documents",
db_url=db_url,
),
)
agent = Agent(
knowledge=kb,
update_knowledge=True,
)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
agent.print_response(
"Update your knowledge with the fact that cats and dogs are pets", markdown=True
)
team = Team(
name="Knowledge Team",
members=[agent],
knowledge=kb,
update_knowledge=True,
)
team.print_response(
"Update your knowledge with the fact that cats don't like water", markdown=True
)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno openai pgvector psycopg-binary sqlalchemy
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run PgVector
docker run -d \
-e POSTGRES_DB=ai \
-e POSTGRES_USER=ai \
-e POSTGRES_PASSWORD=ai \
-e PGDATA=/var/lib/postgresql \
-v pgvolume:/var/lib/postgresql \
-p 5532:5432 \
--name pgvector \
agnohq/pgvector:18
5
Run the example
Save the code above as
knowledge_tool.py, then run:python knowledge_tool.py