Memory

Use Perplexity for answers and an OpenAI memory manager to persist user memories in Postgres.

The source below reads user/session IDs it never sets, then dereferences a missing session. Its inherited Perplexity memory manager also cannot call the memory-storage tools through this adapter. Run the complete Current Example with explicit identity and a tool-capable memory model.

memory.py
"""
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 openai sqlalchemy 'psycopg[binary]' pgvector` to install the dependencies
3. Run: `python cookbook/agents/personalized_memories_and_summaries.py` to run the agent
"""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.perplexity import Perplexity
from rich.pretty import pprint

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

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
agent = Agent(
    model=Perplexity(id="sonar-pro"),
    # Store the memories and summary in a database
    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
)

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

if __name__ == "__main__":
    pass

Current Example

Perplexity answers and generates summaries; the OpenAI memory manager writes memories to the same database. Reuse these demo IDs for the same person/conversation and assign different user IDs to different people. Both providers need account/model access.

memory.py
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.memory import MemoryManager
from agno.models.openai import OpenAIChat
from agno.models.perplexity import Perplexity
from rich.pretty import pprint

user_id = "test_user"
session_id = "test_session"
db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")
agent = Agent(
    model=Perplexity(id="sonar-pro"),
    db=db,
    user_id=user_id,
    session_id=session_id,
    memory_manager=MemoryManager(model=OpenAIChat(id="gpt-5.6-luna"), db=db),
    update_memory_on_run=True,
    enable_session_summaries=True,
    add_history_to_context=True,
)
for message in (
    "My name is John Billings.",
    "I live in NYC.",
    "I'm going to a concert tomorrow.",
):
    agent.print_response(message, stream=True)
    pprint(agent.get_user_memories(user_id=user_id))
    session = agent.get_session(session_id=session_id)
    if session is not None:
        pprint(session.summary)
agent.print_response("What have we been talking about, do you know my name?", stream=True)

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]" openai sqlalchemy

Export your Perplexity API key

export PERPLEXITY_API_KEY="your_perplexity_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:18

Set the memory model key

export OPENAI_API_KEY="your_openai_api_key_here"

Run the example

Save the complete Current Example above as memory.py, then run:

python memory.py

Full source: cookbook/90_models/perplexity/memory.py