learned_knowledge.py
"""
Learning Machines: Learned Knowledge
====================================
Learned Knowledge stores insights that transfer across users.
One person teaches the agent something. Another person benefits.
In AGENTIC mode, the agent receives tools to:
- search_learnings: Find relevant past knowledge
- save_learning: Store a new insight
The agent decides when to save and apply learnings.
"""
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.knowledge import Knowledge
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.learn import LearnedKnowledgeConfig, LearningMachine, LearningMode
from agno.models.openai import OpenAIResponses
from agno.vectordb.chroma import ChromaDb, SearchType
# ---------------------------------------------------------------------------
# Create Knowledge and Agent
# ---------------------------------------------------------------------------
db = SqliteDb(db_file="tmp/agents.db")
knowledge = Knowledge(
name="Agent Learnings",
vector_db=ChromaDb(
name="learnings",
path="tmp/chromadb",
persistent_client=True,
search_type=SearchType.hybrid,
embedder=OpenAIEmbedder(id="text-embedding-3-small"),
),
)
agent = Agent(
model=OpenAIResponses(id="gpt-5.5"),
db=db,
learning=LearningMachine(
knowledge=knowledge,
learned_knowledge=LearnedKnowledgeConfig(mode=LearningMode.AGENTIC),
),
markdown=True,
)
# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# Session 1: User 1 teaches the agent
print("\n--- Session 1: User 1 saves a learning ---\n")
agent.print_response(
"We're trying to reduce our cloud egress costs. Remember this.",
user_id="engineer_1@example.com",
session_id="session_1",
stream=True,
)
lm = agent.learning_machine
lm.learned_knowledge_store.print(query="cloud")
# Session 2: User 2 benefits from the learning
print("\n--- Session 2: User 2 asks a related question ---\n")
agent.print_response(
"I'm picking a cloud provider for a data pipeline. Give me 2 key considerations.",
user_id="engineer_2@example.com",
session_id="session_2",
stream=True,
)
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 chromadb 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 the example
Save the code above as
learned_knowledge.py, then run:python learned_knowledge.py