> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Session Summary

> Enable session summaries with enable_session_summaries or a custom SessionSummaryManager, stored in Postgres.

Use the session summary to store the conversation summary.

```python session_summary.py theme={null}
"""
Session Summary
=============================

This example shows how to use the session summary to store the conversation summary.
"""

from agno.agent.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIResponses
from agno.session.summary import SessionSummaryManager  # noqa: F401

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

db = PostgresDb(db_url=db_url, session_table="sessions")

# Method 1: Set enable_session_summaries to True

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    model=OpenAIResponses(id="gpt-5-mini"),
    db=db,
    enable_session_summaries=True,
    session_id="session_123",
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    agent.print_response("Hi my name is John and I live in New York")
    agent.print_response("I like to play basketball and hike in the mountains")

    print(agent.get_session_summary(session_id="session_123"))

    # Method 2: Set session_summary_manager

    # session_summary_manager = SessionSummaryManager(model=OpenAIResponses(id="gpt-5-mini"))

    # agent = Agent(
    #     model=OpenAIResponses(id="gpt-5-mini"),
    #     db=db,
    #     session_id="session_summary",
    #     session_summary_manager=session_summary_manager,
    # )

    # agent.print_response("Hi my name is John and I live in New York")
    # agent.print_response("I like to play basketball and hike in the mountains")
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno "psycopg[binary]" openai sqlalchemy
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Snippet file="run-pgvector-step.mdx" />

  <Step title="Run the example">
    Save the code above as `session_summary.py`, then run:

    ```bash theme={null}
    python session_summary.py
    ```
  </Step>
</Steps>

Full source: [cookbook/02\_agents/05\_state\_and\_session/session\_summary.py](https://github.com/agno-agi/agno/blob/main/cookbook/02_agents/05_state_and_session/session_summary.py)