This recipe shows how to use personalized memories and summaries in an agent.

Steps: 1. Run: ./cookbook/scripts/run_pgvector.sh to start a postgres container with pgvector 2. Run: uv pip install mistralai sqlalchemy 'psycopg[binary]' pgvector to install the dependencies 3. Run: python cookbook/92_models/mistral/memory.py to run the agent

"""
This recipe shows how to use personalized memories and summaries in an agent.
Steps:
1. Run: `./cookbook/scripts/run_pgvector.sh` to start a postgres container with pgvector
2. Run: `uv pip install mistralai sqlalchemy 'psycopg[binary]' pgvector` to install the dependencies
3. Run: `python cookbook/92_models/mistral/memory.py` to run the agent
"""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.mistral.mistral import MistralChat
from agno.tools.websearch import WebSearchTools

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
# Setup the database
db = PostgresDb(db_url=db_url)

agent = Agent(
    model=MistralChat(id="mistral-large-latest"),
    tools=[WebSearchTools()],
    # Pass the database to the Agent
    db=db,
    # Enable user memories
    update_memory_on_run=True,
    # Enable session summaries
    enable_session_summaries=True,
    # Show debug logs so, you can see the memory being created
)

# -*- Share personal information
agent.print_response("My name is john billings?", stream=True)

# -*- Share personal information
agent.print_response("I live in nyc?", stream=True)

# -*- Share personal information
agent.print_response("I'm going to a concert tomorrow?", stream=True)

# -*- Make tool call
agent.print_response("What is the weather in nyc?", stream=True)

# Ask about the conversation
agent.print_response(
    "What have we been talking about, do you know my name?", stream=True
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass

Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/90_models/mistral

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

# Optiona: Run PgVector (needs docker)
./cookbook/scripts/run_pgvector.sh

python memory.py

​Run the Example

Run the Example