Skip to main content
"""
From GCS
========

Demonstrates loading knowledge from GCS remote content using sync and async inserts.
"""

import asyncio

from agno.agent import Agent
from agno.db.postgres.postgres import PostgresDb
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.remote_content.remote_content import GCSContent
from agno.vectordb.pgvector import PgVector

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
contents_db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")
vector_db = PgVector(
    table_name="vectors", db_url="postgresql+psycopg://ai:ai@localhost:5532/ai"
)


# ---------------------------------------------------------------------------
# Create Knowledge Base
# ---------------------------------------------------------------------------
def create_knowledge() -> Knowledge:
    return Knowledge(
        name="Basic SDK Knowledge Base",
        description="Agno 2.0 Knowledge Implementation",
        contents_db=contents_db,
        vector_db=vector_db,
    )


# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
def create_agent(knowledge: Knowledge) -> Agent:
    return Agent(
        name="My Agent",
        description="Agno 2.0 Agent Implementation",
        knowledge=knowledge,
        search_knowledge=True,
        debug_mode=True,
    )


# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
def run_sync() -> None:
    knowledge = create_knowledge()
    knowledge.insert(
        name="GCS PDF",
        remote_content=GCSContent(
            bucket_name="thai-recepies", blob_name="ThaiRecipes.pdf"
        ),
        metadata={"remote_content": "GCS"},
    )

    agent = create_agent(knowledge)
    agent.print_response(
        "What is the best way to make a Thai curry?",
        markdown=True,
    )


async def run_async() -> None:
    knowledge = create_knowledge()
    await knowledge.ainsert(
        name="GCS PDF",
        remote_content=GCSContent(
            bucket_name="thai-recepies", blob_name="ThaiRecipes.pdf"
        ),
        metadata={"remote_content": "GCS"},
    )

    agent = create_agent(knowledge)
    agent.print_response(
        "What is the best way to make a Thai curry?",
        markdown=True,
    )


if __name__ == "__main__":
    run_sync()
    asyncio.run(run_async())

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/07_knowledge/01_quickstart

# 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 07_from_gcs.py