This example demonstrates how to use session summaries with context references, enabling the agent to maintain conversation context and reference previous session summaries.
"""This example shows how to use the `add_session_summary_to_context` parameter in the Agent config toadd session summaries to the Agent context.Start the postgres db locally on Docker by running: cookbook/scripts/run_pgvector.sh"""from agno.agent.agent import Agentfrom agno.db.postgres import PostgresDbfrom agno.models.openai import OpenAIChatdb_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"db = PostgresDb(db_url=db_url, session_table="sessions")agent = Agent( model=OpenAIChat(id="gpt-5-mini"), db=db, session_id="session_summary", enable_session_summaries=True,)# This will create a new session summaryagent.print_response( "My name is John Doe and I like to hike in the mountains on weekends.",)# You can use existing session summaries from session storage without creating or updating any new ones.agent = Agent( model=OpenAIChat(id="gpt-5-mini"), db=db, session_id="session_summary", add_session_summary_to_context=True,)agent.print_response("I also like to play basketball.")# Alternatively, you can create a new session summary without adding the session summary to context.# agent = Agent(# model=OpenAIChat(id="gpt-5-mini"),# db=db,# session_id="session_summary",# enable_session_summaries=True,# add_session_summary_to_context=False,# )# agent.print_response("I also like to play basketball.")