LiteLLM Memory
Keep up to three previous runs in context and inspect session messages using an in-memory database.
"""
Litellm Memory
==============
Cookbook example for `litellm/memory.py`.
"""
from agno.agent import Agent
from agno.models.litellm import LiteLLM
from rich.pretty import pprint
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
model=LiteLLM(id="gpt-5.6-luna"),
# Set add_history_to_context=true to add the previous chat history to the context sent to the Model.
add_history_to_context=True,
# Number of historical responses to add to the messages.
num_history_runs=3,
description="You are a helpful assistant that always responds in a polite, upbeat and positive manner.",
)
# -*- Create a run
agent.print_response("Share a 2 sentence horror story", stream=True)
# -*- Print the messages in the memory
pprint(
[m.model_dump(include={"role", "content"}) for m in agent.get_session_messages()]
)
# -*- Ask a follow up question that continues the conversation
agent.print_response("What was my first message?", stream=True)
# -*- Print the messages in the memory
pprint(
[m.model_dump(include={"role", "content"}) for m in agent.get_session_messages()]
)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
passRun the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno litellmSet your OpenAI credentials
Use an OpenAI API key with access to the requested model. The LiteLLM SDK calls the provider directly. An existing LITELLM_API_KEY overrides provider-specific credentials, so clear it for this example.
unset LITELLM_API_KEY
export OPENAI_API_KEY="your_provider_api_key_here"Set compatible sampling options
Add temperature=None, top_p=None to every LiteLLM(...) using id="gpt-5.6-luna" or id="openai/gpt-5.6-luna" in your saved file. The adapter defaults to temperature=0.7 and top_p=1.0; the LiteLLM SDK rejects those sampling settings for this model's default reasoning mode before sending a request.
Add a session database
Import InMemoryDb with from agno.db.in_memory import InMemoryDb, then add db=InMemoryDb() to the Agent constructor. Keep add_history_to_context=True and num_history_runs=3. This store lasts for the current Python process; use a persistent database when history must survive a restart.
Run the example
Save the code above as memory.py, then run:
python memory.pyFull source: cookbook/90_models/litellm/memory.py