memory_manager.py
"""
Memory Manager
=============================
Use a MemoryManager to give agents persistent memory across sessions.
"""
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.memory.manager import MemoryManager
from agno.models.openai import OpenAIResponses
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
db = SqliteDb(db_file="tmp/memory_demo.db")
agent = Agent(
model=OpenAIResponses(id="gpt-5.2"),
db=db,
# Enable agentic memory so the agent can store and retrieve memories
enable_agentic_memory=True,
# Provide a MemoryManager for structured memory operations
memory_manager=MemoryManager(
db=db,
model=OpenAIResponses(id="gpt-5-mini"),
),
markdown=True,
)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# First interaction: tell the agent something to remember
agent.print_response(
"My name is Alice and I prefer Python over JavaScript.",
stream=True,
)
print("\n--- Second interaction ---\n")
# Second interaction: the agent should recall the preference
agent.print_response(
"What programming language do I prefer?",
stream=True,
)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno openai sqlalchemy
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
memory_manager.py, then run:python memory_manager.py