zep_integration.py
"""
Zep Integration
===============
Demonstrates Zep-powered memory retrieval for an Agno agent.
"""
import time
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.zep import ZepTools
# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
# Initialize the ZepTools
zep_tools = ZepTools(user_id="agno", session_id="agno-session")
zep_tools.add_zep_message(role="user", content="My name is John Billings")
zep_tools.add_zep_message(role="user", content="I live in NYC")
zep_tools.add_zep_message(role="user", content="I'm going to a concert tomorrow")
# Allow the memories to sync with Zep database
time.sleep(10)
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
model=OpenAIChat(),
tools=[zep_tools],
dependencies={"memory": zep_tools.get_zep_memory(memory_type="context")},
add_dependencies_to_context=True,
)
# ---------------------------------------------------------------------------
# Run Example
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# Ask the Agent about the user
agent.print_response("What do you know about me?")
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 zep-cloud
3
Export your API keys
export OPENAI_API_KEY="your_openai_api_key_here"
export ZEP_API_KEY="your_zep_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
$Env:ZEP_API_KEY="your_zep_api_key_here"
4
Run the example
Save the code above as
zep_integration.py, then run:python zep_integration.py