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import asyncio

from agno.agent import Agent
from agno.db.postgres.postgres import PostgresDb
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.web_search_reader import WebSearchReader
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

db = PostgresDb(id="web-search-db", db_url=db_url)

vector_db = PgVector(
    db_url=db_url,
    table_name="web_search_documents",
)
knowledge = Knowledge(
    name="Web Search Documents",
    contents_db=db,
    vector_db=vector_db,
)


# Initialize the Agent with the knowledge
agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
)


if __name__ == "__main__":
    # Comment out after first run
    asyncio.run(
        knowledge.ainsert(
            topics=["web3 latest trends 2025"],
            reader=WebSearchReader(
                max_results=3,
                search_engine="duckduckgo",
                chunk=True,
            ),
        )
    )

    # Create and use the agent
    asyncio.run(
        agent.aprint_response(
            "What are the latest AI trends according to the search results?",
            markdown=True,
        )
    )

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/07_knowledge/readers

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

# Optiona: Run PgVector (needs docker)
./cookbook/scripts/run_pgvector.sh

python web_search_reader_async.py