learning_true_shorthand.py
"""
Learning=True Shorthand Test
============================
Tests the simplest way to enable learning: `learning=True`.
This is the most common user pattern and must work flawlessly.
When learning=True:
- A default LearningMachine is created
- UserProfile is enabled with ALWAYS mode (structured fields)
- UserMemory is enabled with ALWAYS mode (unstructured observations)
- db and model are injected from the agent
This test verifies the shorthand works identically to explicit config.
"""
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIResponses
# ---------------------------------------------------------------------------
# Create Agent - Using the simplest possible configuration
# ---------------------------------------------------------------------------
db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")
# This is the simplest way to enable learning - just set learning=True
agent = Agent(
model=OpenAIResponses(id="gpt-5.5"),
db=db,
learning=True, # <-- The shorthand we're testing
markdown=True,
)
# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------
if __name__ == "__main__":
user_id = "shorthand_test@example.com"
# Note: LearningMachine is lazily initialized - only set up when agent runs
print("\n" + "=" * 60)
print("SESSION 1: Share information (learning=True shorthand)")
print("=" * 60 + "\n")
agent.print_response(
"Hi! I'm Charlie Brown. Friends call me Chuck.",
user_id=user_id,
session_id="shorthand_session_1",
stream=True,
)
# Verify LearningMachine was created (after first run)
print("\n" + "=" * 60)
print("VERIFICATION: LearningMachine created from learning=True")
print("=" * 60 + "\n")
lm = agent.learning_machine
print(f"LearningMachine exists: {lm is not None}")
print(
f"UserProfileStore exists: {lm.user_profile_store is not None if lm else False}"
)
print(
f"UserMemoryStore exists: {lm.user_memory_store is not None if lm else False}"
)
print(f"DB injected: {lm.db is not None if lm else False}")
print(f"Model injected: {lm.model is not None if lm else False}")
if not lm:
print("\nFAILED: LearningMachine was not created!")
exit(1)
if not lm.user_profile_store:
print("\nFAILED: UserProfileStore was not created!")
exit(1)
if not lm.user_memory_store:
print("\nFAILED: UserMemoryStore was not created!")
exit(1)
print("\n--- User Profile ---")
lm.user_profile_store.print(user_id=user_id)
print("\n--- User Memory ---")
lm.user_memory_store.print(user_id=user_id)
# Session 2: Verify profile persisted
print("\n" + "=" * 60)
print("SESSION 2: Profile recall")
print("=" * 60 + "\n")
agent.print_response(
"What do my friends call me?",
user_id=user_id,
session_id="shorthand_session_2",
stream=True,
)
print("\n--- User Profile ---")
lm.user_profile_store.print(user_id=user_id)
print("\n--- User Memory ---")
lm.user_memory_store.print(user_id=user_id)
print("\n" + "=" * 60)
print("SHORTHAND TEST COMPLETE")
print("=" * 60)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno "psycopg[binary]" openai sqlalchemy
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
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
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
5
Run the example
Save the code above as
learning_true_shorthand.py, then run:python learning_true_shorthand.py