chat_history.py
"""
Chat History
=============================
Chat History.
"""
from agno.agent.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIResponses
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db_url=db_url, session_table="sessions")
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
model=OpenAIResponses(id="gpt-5-mini"),
db=db,
session_id="chat_history",
instructions="You are a helpful assistant that can answer questions about space and oceans.",
add_history_to_context=True,
)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
agent.print_response("Tell me a new interesting fact about space")
print(agent.get_chat_history())
agent.print_response("Tell me a new interesting fact about oceans")
print(agent.get_chat_history())
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
chat_history.py, then run:python chat_history.py