> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Scheduler Demo

> Running the scheduler inside AgentOS with programmatic schedule creation.

```python demo.py theme={null}
"""Running the scheduler inside AgentOS with programmatic schedule creation.

This example demonstrates:
- Setting scheduler=True on AgentOS to enable cron polling
- Using ScheduleManager to create schedules directly (no curl needed)
- The poller starts automatically on app startup and executes due schedules

Run with:
    .venvs/demo/bin/python cookbook/05_agent_os/scheduler/demo.py
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.os import AgentOS
from agno.scheduler import ScheduleManager

# --- Setup ---

db = SqliteDb(id="scheduler-os-demo", db_file="tmp/scheduler_os_demo.db")

greeter = Agent(
    name="Greeter",
    model=OpenAIChat(id="gpt-4o-mini"),
    instructions=["You are a friendly greeter."],
    db=db,
)

reporter = Agent(
    name="Reporter",
    model=OpenAIChat(id="gpt-4o-mini"),
    instructions=["You summarize news headlines in 2-3 sentences."],
    db=db,
)

# --- Create schedules programmatically ---

mgr = ScheduleManager(db)

# Create a schedule for the greeter agent (every 5 minutes)
greet_schedule = mgr.create(
    name="greet-every-5-min",
    cron="* * * * *",
    endpoint="/agents/greeter/runs",
    payload={"message": "Say hello!"},
    description="Greet every 5 minutes",
    if_exists="update",
)
print(f"Schedule ready: {greet_schedule.name} (next run: {greet_schedule.next_run_at})")

# Create a schedule for the reporter agent (daily at 9 AM)
report_schedule = mgr.create(
    name="daily-news-report",
    cron="* * * * *",
    endpoint="/agents/reporter/runs",
    payload={"message": "Summarize today's top headlines."},
    description="Daily news summary at 9 AM UTC",
    if_exists="update",
)
print(
    f"Schedule ready: {report_schedule.name} (next run: {report_schedule.next_run_at})"
)

# --- Create AgentOS with scheduler enabled ---

agent_os = AgentOS(
    name="Scheduled OS",
    agents=[greeter, reporter],
    db=db,
    scheduler=True,
    scheduler_poll_interval=15,
)

# --- Run the server ---
# The poller will automatically pick up the schedules created above.

if __name__ == "__main__":
    import uvicorn

    uvicorn.run(agent_os.get_app(), host="0.0.0.0", port=7777)
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U "agno[os,scheduler]" openai
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `demo.py`, then run:

    ```bash theme={null}
    python demo.py
    ```
  </Step>
</Steps>

Full source: [cookbook/05\_agent\_os/scheduler/demo.py](https://github.com/agno-agi/agno/blob/main/cookbook/05_agent_os/scheduler/demo.py)