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

# Persisting Sessions

> Store session data in a database for multi-turn conversations

To enable sessions across multiple runs, you need to configure a database. Once configured, Agno automatically stores conversation history, session state, and run metadata. Paused runs persist their status and requirements so they can be continued later.

<Note>
  Database selection, connection strings, credentials management, and operational guidance live in the [Database overview](/database/overview). Reuse that setup here—this page only adds the session-specific considerations.
</Note>

## Quick Start

Once you have a `db` object (Postgres, SQLite, DynamoDB, …) configured per the storage docs, persistence is enabled simply by passing it to your Agent, Team, or Workflow:

```python theme={null}
db = PostgresDb(db_url="postgresql+psycopg://...")

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,                 # Enables persistence
    session_id="user_123", # Same ID = same conversation
)
```

## Supported Databases

Nothing new lives here—simply reuse the database drivers and guidance from `/basics/storage`:

* **PostgreSQL** (recommended) – Production-grade, supports custom `session_table` names for isolating workloads.
* **SQLite** – Great for local development; swap the file path just as you would elsewhere.
* **InMemoryDb** – Useful for tests or demos only. Data disappears when the process exits.

If you need to tune indexing, retention, or connection pools, do that in the shared storage layer so every feature (sessions, memories, knowledge, etc.) benefits from the same configuration.

## Session IDs

Sessions are identified by `session_id`. Use the same ID to continue a conversation:

```python theme={null}
# First run
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    session_id="conversation_123",
)
agent.run("My name is Alice")

# Later run with same session_id
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    session_id="conversation_123",  # Same ID
    add_history_to_context=True,     # Enable history
)
agent.run("What's my name?")  # Agent remembers "Alice"
```

Need custom naming conventions, caching, or UI-friendly labels? Continue with the [Session Management](/sessions/session-management) guide.

## What Gets Stored

When you configure a database, Agno automatically stores:

* ✅ **Messages** - User inputs and agent responses
* ✅ **Run metadata** - Timestamps, token usage, model info
* ✅ **Session state** - Custom key-value data
* ✅ **Tool calls** - Tool usage and results (optional)
* ✅ **Media** - Images, audio, files (optional)

See [Storage Control](/sessions/persisting-sessions/storage-control) to customize what gets saved.

## Multi-User Sessions

Use `user_id` to track different users:

```python theme={null}
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
)

# Specify the user_id and session_id on run to start or continue the conversation
agent.print_response("Hello!", session_id="session_456", user_id="alice@example.com")
```

## Session Storage Schema

When you configure a database, Agno stores sessions in a structured format. Here's what gets saved for each session:

| Field           | Type   | Description                                     |
| --------------- | ------ | ----------------------------------------------- |
| `session_id`    | `str`  | Unique identifier for this conversation thread  |
| `session_type`  | `str`  | Type of session (agent, team, or workflow)      |
| `agent_id`      | `str`  | The agent ID (if this is an agent session)      |
| `team_id`       | `str`  | The team ID (if this is a team session)         |
| `workflow_id`   | `str`  | The workflow ID (if this is a workflow session) |
| `user_id`       | `str`  | The user this session belongs to                |
| `session_data`  | `dict` | Session-specific data and state                 |
| `agent_data`    | `dict` | Agent configuration and metadata                |
| `team_data`     | `dict` | Team configuration and metadata                 |
| `workflow_data` | `dict` | Workflow configuration and metadata             |
| `metadata`      | `dict` | Additional custom metadata                      |
| `runs`          | `list` | All the runs (interactions) in this session     |
| `summary`       | `dict` | The session summary (if enabled)                |
| `created_at`    | `int`  | Unix timestamp when session was created         |
| `updated_at`    | `int`  | Unix timestamp of last update                   |

<Tip>
  Want to visualize your sessions? Check out the [AgentOS UI sessions page](https://os.agno.com/sessions) for a beautiful interface to view and manage all your conversation threads.
</Tip>

## Guides

Now that you have persistence configured, explore what you can do with sessions:

* [Storage Control](/sessions/persisting-sessions/storage-control) - Optimize what gets saved
* [History Management](/sessions/history-management) - Control conversation history
* [Session Summaries](/sessions/session-summaries) - Condense long conversations
* [Session Management](/sessions/session-management) - Naming, caching, and more