​
Code

cookbook/models/vllm/memory.py
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.vllm import VLLM
from agno.utils.pprint import pprint

# Change this if your Postgres container is running elsewhere
DB_URL = "postgresql+psycopg://ai:ai@localhost:5532/ai"

agent = Agent(
    model=VLLM(id="microsoft/Phi-3-mini-128k-instruct"),
    db=PostgresDb(db_url=DB_URL),
    enable_user_memories=True,
    enable_session_summaries=True,
)

# -*- Share personal information
agent.print_response("My name is john billings?", stream=True)
# -*- Print memories and summary
if agent.db:
    pprint(agent.get_user_memories(user_id="test_user"))
    pprint(
        agent.get_session(session_id="test_session").summary  # type: ignore
    )

# -*- Share personal information
agent.print_response("I live in nyc?", stream=True)
# -*- Print memories and summary
if agent.db:
    pprint(agent.get_user_memories(user_id="test_user"))
    pprint(
        agent.get_session(session_id="test_session").summary  # type: ignore
    )

# -*- Share personal information
agent.print_response("I'm going to a concert tomorrow?", stream=True)
# -*- Print memories and summary
if agent.db:
    pprint(agent.get_user_memories(user_id="test_user"))
    pprint(
        agent.get_session(session_id="test_session").summary  # type: ignore
    )

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

​
Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Start Postgres database

./cookbook/scripts/run_pgvector.sh
3

Install Libraries

pip install -U agno openai vllm sqlalchemy psycopg pgvector
4

Start vLLM server

vllm serve microsoft/Phi-3-mini-128k-instruct \
    --dtype float32 \
    --enable-auto-tool-choice \
    --tool-call-parser pythonic
5

Run Agent

python cookbook/models/vllm/memory.py