Create Memories From Text and Message History
Create user memories from direct text and from a message list using MemoryManager.
"""
Create Memories From Text and Message History
=============================================
This example shows how to create user memories from direct text and from a
message list using MemoryManager.
"""
from agno.db.postgres import PostgresDb
from agno.memory import MemoryManager, UserMemory
from agno.models.message import Message
from agno.models.openai import OpenAIChat
from rich.pretty import pprint
# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
memory_db = PostgresDb(db_url=db_url)
# ---------------------------------------------------------------------------
# Create Memory Manager
# ---------------------------------------------------------------------------
memory = MemoryManager(model=OpenAIChat(id="gpt-5.6-luna"), db=memory_db)
# ---------------------------------------------------------------------------
# Run Memory Manager
# ---------------------------------------------------------------------------
if __name__ == "__main__":
john_doe_id = "john_doe@example.com"
memory.add_user_memory(
memory=UserMemory(
memory="""
I enjoy hiking in the mountains on weekends,
reading science fiction novels before bed,
cooking new recipes from different cultures,
playing chess with friends,
and attending live music concerts whenever possible.
Photography has become a recent passion of mine, especially capturing landscapes and street scenes.
I also like to meditate in the mornings and practice yoga to stay centered.
"""
),
user_id=john_doe_id,
)
memories = memory.get_user_memories(user_id=john_doe_id)
print("John Doe's memories:")
pprint(memories)
jane_doe_id = "jane_doe@example.com"
memory.create_user_memories(
messages=[
Message(role="user", content="My name is Jane Doe"),
Message(role="assistant", content="That is great!"),
Message(role="user", content="I like to play chess"),
Message(role="assistant", content="That is great!"),
],
user_id=jane_doe_id,
)
memories = memory.get_user_memories(user_id=jane_doe_id)
print("Jane Doe's memories:")
pprint(memories)add_user_memory() stores John's supplied text directly without calling a model. create_user_memories(messages=...) asks the configured model to extract memories for Jane from the conversation.
Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno "psycopg[binary]" openai sqlalchemyExport your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"Run PgVector
docker run -d \
-e POSTGRES_DB=ai \
-e POSTGRES_USER=ai \
-e POSTGRES_PASSWORD=ai \
-e PGDATA=/var/lib/postgresql \
-v pgvolume:/var/lib/postgresql \
-p 5532:5432 \
--name pgvector \
agnohq/pgvector:18Run the example
Save the code above as memory_creation.py, then run:
python memory_creation.pyFull source: cookbook/11_memory/memory_manager/02_memory_creation.py