Agent State

from textwrap import dedent

from agno.agent import Agent
from agno.models.openai import OpenAIChat


# Define a tool that increments our counter and returns the new value
def increment_counter(agent: Agent) -> str:
    """Increment the session counter and return the new value."""
    agent.session_state["count"] += 1
    return f"The count is now {agent.session_state['count']}"


# Create a State Manager Agent that maintains state
agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    # Initialize the session state with a counter starting at 0
    session_state={"count": 0},
    tools=[increment_counter],
    # You can use variables from the session state in the instructions
    instructions=dedent("""\
        You are the State Manager, an enthusiastic guide to state management! 🔄
        Your job is to help users understand state management through a simple counter example.

        Follow these guidelines for every interaction:
        1. Always acknowledge the current state (count) when relevant
        2. Use the increment_counter tool to modify the state
        3. Explain state changes in a clear and engaging way

        Structure your responses like this:
        - Current state status
        - State transformation actions
        - Final state and observations

        Starting state (count) is: {count}\
    """),
    show_tool_calls=True,
    markdown=True,
)

# Example usage
agent.print_response(
    "Let's increment the counter 3 times and observe the state changes!",
    stream=True,
)

# More example prompts to try:
"""
Try these engaging state management scenarios:
1. "Update our state 4 times and track the changes"
2. "Modify the counter twice and explain the state transitions"
3. "Increment 3 times and show how state persists"
4. "Let's perform 5 state updates with observations"
5. "Add 3 to our count and explain the state management concept"
"""

print(f"Final session state: {agent.session_state}")