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Configuration file

We will first create a YAML file with the extra configuration we want to pass to our AgentOS:
configuration.yaml
chat:
  quick_prompts:
    marketing-agent:
      - "What can you do?"
      - "How is our latest post working?"
      - "Tell me about our active marketing campaigns"
memory:
  dbs:
    - db_id: db-0001
      domain_config:
        display_name: Main app user memories
    - db_id: db-0002
      domain_config:
        display_name: Support flow user memories

​
Code

cookbook/06_agent_os/os_config/yaml_config.py
"""Example showing how to pass extra configuration to your AgentOS."""

from pathlib import Path

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.team import Team
from agno.vectordb.pgvector import PgVector
from agno.workflow.step import Step
from agno.workflow.workflow import Workflow

# Get the path to our configuration file
cwd = Path(__file__).parent
config_file_path = str(cwd.joinpath("configuration.yaml"))

# Setup the database
db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

# Setup basic agents, teams and workflows
basic_agent = Agent(
    name="Basic Agent",
    db=db,
    enable_session_summaries=True,
    update_memory_on_run=True,
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
)
basic_team = Team(
    id="basic-team",
    name="Basic Team",
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    members=[basic_agent],
    update_memory_on_run=True,
)
basic_workflow = Workflow(
    id="basic-workflow",
    name="Basic Workflow",
    description="Just a simple workflow",
    db=db,
    steps=[
        Step(
            name="step1",
            description="Just a simple step",
            agent=basic_agent,
        )
    ],
)
basic_knowledge = Knowledge(
    name="Basic Knowledge",
    description="A basic knowledge base",
    contents_db=db,
    vector_db=PgVector(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai", table_name="vectors"),
)

# Setup our AgentOS app
agent_os = AgentOS(
    description="Example AgentOS",
    agents=[basic_agent],
    teams=[basic_team],
    workflows=[basic_workflow],
    knowledge=[basic_knowledge],
    # We pass the configuration file to our AgentOS here
    config=config_file_path,
)
app = agent_os.get_app()


if __name__ == "__main__":
    """Run our AgentOS.

    You can see the configuration and available apps at:
    http://localhost:7777/config

    """
    agent_os.serve(app="yaml_config:app", reload=True)
It’s recommended to add id for better management and easier identification in the AgentOS interface. You can add it to your database configuration like this:
from agno.db.postgres import PostgresDb

db = PostgresDb(
  id="my_agent_db",
  db_url="postgresql+psycopg://ai:ai@localhost:5532/ai"
)

​
Usage

1

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate
2

Set Environment Variables

export OPENAI_API_KEY=your_openai_api_key
3

Install dependencies

uv pip install -U agno fastapi uvicorn sqlalchemy pgvector psycopg
4

Setup PostgreSQL Database

# Using Docker
docker run -d \
  --name agno-postgres \
  -e POSTGRES_DB=ai \
  -e POSTGRES_USER=ai \
  -e POSTGRES_PASSWORD=ai \
  -p 5532:5432 \
  pgvector/pgvector:pg17
5

Run Example

python cookbook/06_agent_os/os_config/yaml_config.py