stepflow-agent 0.1.0

A beginner-friendly Python SDK for building step-based agent workflows.

StepFlow Agent

StepFlow Agent is an open-source Python SDK for building agent workflows with plain Python classes, step decorators, shared state, retries, structured execution results, persistent approval pause/resume, child workflow composition, and metadata-only graph export.

Status

The main MVP is implemented.

Today, the SDK already supports:

• workflow classes with @workflow
• ordered step methods with @step
• shared mutable state through self.state
• synchronous execution
• retry handling for transient failures
• conditional branching with explicit route maps
• synchronous human approval callbacks
• explicit approval pause/resume with user-managed checkpoints
• synchronous lifecycle hooks for logging and observability
• synchronous child workflow composition through RunContext
• workflow graph export as Mermaid diagrams
• structured WorkflowResult and StepResult
• optional raise_on_failure=True

This makes the project useful today for linear agent-style workflows such as:

• refund handling
• support triage
• content review
• branching refund decisions
• approval-gated refund decisions
• paused approval workflows that resume later
• hook-based execution logging
• composed workflows that delegate to child workflows
• workflow graph inspection
• internal multi-step automations

Why this project exists

Many useful agent workflows do not need graph-first complexity on day one.

StepFlow Agent is meant to provide a simpler path:

• more structure than ad hoc scripts
• less framework overhead than graph-first orchestration tools
• a class-based Python authoring model that is easy to teach and debug

Quickstart

from dataclasses import dataclass

from agentflow import step, workflow


@dataclass
class RefundState:
    order_id: str
    amount: float
    order_found: bool = False
    policy_ok: bool = False
    response_text: str = ""


@workflow
class RefundWorkflow:
    @step
    def check_order(self) -> str:
        self.state.order_found = True
        return f"Order {self.state.order_id} located."

    @step
    def verify_policy(self) -> str:
        self.state.policy_ok = self.state.order_found and self.state.amount <= 100.0
        return "Refund policy check completed."

    @step
    def generate_response(self) -> str:
        if self.state.policy_ok:
            self.state.response_text = f"Refund approved for {self.state.order_id}."
        else:
            self.state.response_text = f"Refund denied for {self.state.order_id}."
        return self.state.response_text


workflow_instance = RefundWorkflow()
result = workflow_instance.run(RefundState(order_id="ord_123", amount=42.50))

print(result.status.value)
print(result.state.response_text)
print(result.steps[-1].output)

Current capabilities

The current SDK already gives you:

• a decorator-based authoring model
• ordered workflow execution
• conditional routing to later steps or END
• human approval callbacks before selected steps run
• persistent approval pause/resume through user-managed checkpoints
• lifecycle hooks for workflow and step events
• synchronous child workflow execution from context-aware steps
• step-level retries with fixed delay
• validation for workflow definitions and step signatures
• framework-specific exceptions
• workflow and step timing information
• per-step outputs, errors, and attempt counts
• metadata-only workflow graph export with Mermaid rendering

The public agentflow package currently exposes:

• workflow
• step
• WorkflowResult
• StepResult
• RunContext
• RetryPolicy
• END
• ApprovalRequest
• ApprovalDecision
• ApprovalPause
• RouteDecision
• WorkflowStartedEvent
• StepStartedEvent
• StepFinishedEvent
• WorkflowFinishedEvent
• WorkflowEvent
• WorkflowHook
• WorkflowGraph
• WorkflowGraphNode
• WorkflowGraphEdge
• export_workflow_graph
• HookExecutionError
• ApprovalResumeError
• ChildWorkflowExecutionError
• ApprovalRequiredError
• RouteResolutionError
• framework exception types

Examples

The repository includes runnable examples under examples/.

Refund workflow

This example shows the simplest happy path:

• linear step execution
• state mutation across steps
• a final response generated from earlier decisions

Run it with:

python examples/refund_workflow.py

See: examples/refund_workflow.py

Support triage workflow

This example shows:

• a typed support-ticket state object
• the optional step context parameter
• queue assignment from computed workflow state
• readable inspection of per-step results

Run it with:

python examples/support_triage.py

See: examples/support_triage.py

Content review workflow

This example shows:

• a retrying moderation step
• transient failure recovery with TimeoutError
• final decision output and attempt counts

Run it with:

python examples/content_review.py

See: examples/content_review.py

Branching refund workflow

This example shows:

• route-based branching from a decision step
• explicit terminal paths with END
• route trace inspection
• skipped step results

Run it with:

python examples/branching_refund_workflow.py

See: examples/branching_refund_workflow.py

Approval refund workflow

This example shows:

• a synchronous approval handler
• approval request metadata
• approved and denied approval decisions
• approval details recorded on StepResult

Run it with:

python examples/approval_refund_workflow.py

See: examples/approval_refund_workflow.py

Persistent approval workflow

This example shows:

• explicit pause_on_approval=True
• a paused result with an approval checkpoint
• resuming later with ApprovalDecision

Run it with:

python examples/persistent_approval_workflow.py

See: examples/persistent_approval_workflow.py

Workflow hooks

This example shows:

• synchronous lifecycle hooks
• workflow and step event logging
• normal result inspection after hooks run

Run it with:

python examples/workflow_hooks.py

See: examples/workflow_hooks.py

Workflow composition

This example shows:

• a parent workflow running a child workflow from a step
• nested child results on StepResult.child_workflows
• manual inspection with fail_parent_on_failure=False

Run it with:

python examples/workflow_composition.py

See: examples/workflow_composition.py

Graph export workflow

This example shows:

• graph export from workflow metadata
• Mermaid rendering without running the workflow
• route edges, approval-gated nodes, and terminal END paths

Run it with:

python examples/graph_export.py

See: examples/graph_export.py

Installation

Install from PyPI:

pip install stepflow-agent

The installed Python package is imported as agentflow:

from agentflow import step, workflow

For local development:

pip install -e .[dev]

The project currently targets Python 3.11+.

Development

Run the local checks with:

ruff check .
pytest

Run the examples with:

python examples/refund_workflow.py
python examples/support_triage.py
python examples/content_review.py
python examples/branching_refund_workflow.py
python examples/approval_refund_workflow.py
python examples/persistent_approval_workflow.py
python examples/workflow_hooks.py
python examples/workflow_composition.py
python examples/graph_export.py

Repository layout

The repository uses a src/ layout.

• src/agentflow/ contains the SDK implementation
• tests/ contains behavior-focused tests
• examples/ contains runnable example workflows
• .github/workflows/ contains CI and release validation
• docs/ contains deeper public documentation, including current status, architecture, and usage guides

Documentation

If you want a high-level current-state summary, start with:

• docs/current-status.md

If you want the broader public docs index, start with:

• docs/README.md

If you want deeper technical documentation, start with:

• docs/architecture/README.md
• docs/guides/README.md

Not implemented yet

The current SDK does not yet include:

• async execution
• database-backed approval persistence
• async event buses or tracing backends
• worker backends
• dashboards or interactive visual editors
• graph execution
• durable child workflow orchestration
• framework adapters such as LangGraph integration

Those remain future extensions beyond the current MVP.

Roadmap direction

The next stage of the project is not "finish the MVP."

The likely next areas of work are:

• release hardening
• repository and contributor polish
• docs hardening
• post-MVP features such as async execution or external adapters