Agent with Memory

Code

cookbook/11_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),
    update_memory_on_run=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. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
2. Start Postgres database

   ./cookbook/scripts/run_pgvector.sh
   
3. Install Libraries

   uv 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/11_models/vllm/memory.py