DB

Store LM Studio agent sessions in Postgres and answer follow-ups with history in context.

db.py
"""Run `uv pip install ddgs sqlalchemy` to install dependencies."""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.lmstudio import LMStudio
from agno.tools.websearch import WebSearchTools

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

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

agent = Agent(
    model=LMStudio(id="qwen2.5-7b-instruct-1m"),
    db=db,
    tools=[WebSearchTools()],
    add_history_to_context=True,
)
agent.print_response("How many people live in Canada?")
agent.print_response("What is their national anthem called?")

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

if __name__ == "__main__":
    pass

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Install dependencies

uv pip install -U agno "psycopg[binary]" ddgs openai sqlalchemy

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:18

Prepare LM Studio

Load qwen2.5-7b-instruct-1m in LM Studio and start its local server at http://127.0.0.1:1234/v1.

Run the example

Save the code above as db.py, then run:

python db.py

Full source: cookbook/90_models/lmstudio/db.py