agentstateprotocol 0.1.0

Checkpointing and recovery protocol for AI agents

AgentStateProtocol

Checkpointing and recovery protocol for AI agents.

AgentStateProtocol lets an agent save state at each reasoning step, branch into alternatives, and roll back safely after failures.

Install

pip install agentstateprotocol

Quick Start

from agentstateprotocol import AgentStateProtocol

agent = AgentStateProtocol("my-agent")

agent.checkpoint(
    state={"task": "summarize quarterly report", "stage": "parsed"},
    metadata={"confidence": 0.91},
    description="Initial parse",
    logic_step="parse_input",
)

agent.checkpoint(
    state={"task": "summarize quarterly report", "stage": "drafted"},
    metadata={"confidence": 0.86},
    description="Draft generated",
    logic_step="draft_summary",
)

# Roll back one step if needed
agent.rollback()

Core Operations

• agent.checkpoint(...): save a state snapshot
• agent.rollback(...): restore a previous checkpoint
• agent.branch(name): start an alternate reasoning path
• agent.switch_branch(name): move between branches
• agent.merge(source_branch): merge branch outcomes
• agent.history(): inspect checkpoint timeline
• agent.visualize_tree(): show decision tree

Decorators

from agentstateprotocol.decorators import agentstateprotocol_step

@agentstateprotocol_step("analyze")
def analyze(state):
    return {"result": "ok", **state}

Storage

from agentstateprotocol.storage import FileSystemStorage, SQLiteStorage

file_storage = FileSystemStorage(".agentstateprotocol")
sqlite_storage = SQLiteStorage(".agentstateprotocol/agentstateprotocol.db")

CLI

agentstateprotocol demo
agentstateprotocol log
agentstateprotocol tree
agentstateprotocol branches
agentstateprotocol diff <checkpoint_a> <checkpoint_b>
agentstateprotocol metrics

Project

• Repository: https://github.com/ekessh/agentstateprotocol
• License: MIT