Praison AI

Session Resume

Resume interrupted agent sessions

Resume interrupted sessions to continue where you left off.

python
from praisonaiagents import Agent, Session

session = Session(session_id="task-123", persistence="sqlite")
agent = Agent(name="Worker", session=session)

agent.resume()

The user reopens the same session ID after a crash or deploy and the agent continues the in-flight task.

Diagram

Session Resume

📋 session_id

💾 Load state

✅ Continue task

Quick Start

  1. Simple Usage

    Reopen a session by its ID and call resume() to continue the in-flight task.

    python
    from praisonaiagents import Agent, Session

session = Session(session_id="task-123", persistence="sqlite")
agent = Agent(name="Worker", session=session)
agent.resume()
  2. With Configuration

    Add automatic checkpoints so long tasks resume from the latest step, not the start.

    python
    from praisonaiagents import Agent, Session

session = Session(
    session_id="task-123",
    persistence="sqlite",
    checkpoint_interval=5,
)
agent = Agent(name="Worker", session=session)
agent.start("Process 1000 items...")

How It Works

Diagram
SessionAgentUserSessionAgentUserCrash or deploystart(“long task”)Checkpoint progressresume()Load last checkpointContinue from where it stopped

Basic Resume

python
from praisonaiagents import Agent, Session

# Original session
session = Session(session_id="task-123", persistence="sqlite")
agent = Agent(name="Worker", session=session)
agent.start("Start a long task...")

# ... application crashes or restarts ...

# Resume session
session = Session(session_id="task-123", persistence="sqlite")
agent = Agent(name="Worker", session=session)
agent.resume()  # Continues from last checkpoint

With Checkpoints

python
from praisonaiagents import Agent, Session

session = Session(
    session_id="task-123",
    persistence="sqlite",
    checkpoint_interval=5  # Checkpoint every 5 steps
)

agent = Agent(name="Worker", session=session)

# Long-running task with automatic checkpoints
agent.start("Process 1000 items...")

Manual Checkpoints

python
from praisonaiagents import Agent, Session

session = Session(session_id="task-123", persistence="sqlite")
agent = Agent(name="Worker", session=session)

# Create checkpoint manually
session.checkpoint(
    state={"processed": 500, "remaining": 500},
    message="Halfway done"
)

# Resume from checkpoint
session.resume_from_checkpoint()

List Sessions

python
from praisonaiagents import Session

# List all sessions
sessions = Session.list_all(persistence="sqlite")
for s in sessions:
    print(f"{s.session_id}: {s.status}")

Best Practices

Keep the session_id stable across restarts

resume() finds prior state by session_id. Store the ID (env var, queue message, or DB row) so a restarted process reopens the right session.

Tune checkpoint_interval to task length

Frequent checkpoints cost writes but lose less on failure. For step-heavy tasks, a small interval like checkpoint_interval=5 balances safety and overhead.

Save state at natural boundaries

Call session.save_state({...}) after a meaningful unit of work so session.restore_state() reopens at a clean point when the same session_id resumes.

List sessions to reconcile state

Session.list_all(persistence=...) shows every stored session and its status — useful for dashboards and cleanup jobs.

Related

Session Module

Session API reference

 Checkpoints

Checkpoint API