penguiflow 3.3.0

Async-first orchestration library for multi-agent and data pipelines

PenguiFlow

Async-first orchestration library for typed, reliable, concurrent workflows — from deterministic data pipelines to LLM agents.

Why PenguiFlow

• Graph runtime: run async node graphs with bounded queues (backpressure).
• Reliability controls: per-node timeouts + retries, plus per-trace cancellation and deadlines (envelope mode).
• Streaming: emit partial output (StreamChunk) and a final answer with deterministic correlation.
• Planner (ReactPlanner): JSON-first tool orchestration with pause/resume (HITL), parallel fan-out + joins, and trajectory logging.
• Tool integrations: native + ToolNode (MCP / UTCP / HTTP) with auth and resilience patterns.

Concepts at a glance

• Flow: a directed graph (runtime) you run(), emit() into, and fetch() results from.
• Node: an async function + NodePolicy (validation, retries, timeout).
• Message (recommended for production): Message(payload=..., headers=Headers(tenant=...), trace_id=...) enabling trace correlation, cancellation, deadlines, and streaming.
• StateStore (optional): durability/audit/event persistence for distributed and “ops-ready” deployments.

Install

Requirements: Python 3.11+

pip install penguiflow

Common extras:

pip install "penguiflow[planner]"      # ReactPlanner + ToolNode integrations
pip install "penguiflow[a2a-server]"   # A2A HTTP+JSON server bindings
pip install "penguiflow[a2a-client]"   # A2A client bindings

If you use uv:

uv pip install penguiflow

Quickstart

1) Minimal typed flow (runtime)

from __future__ import annotations

import asyncio

from pydantic import BaseModel

from penguiflow import ModelRegistry, Node, NodePolicy, create


class In(BaseModel):
    text: str


class Out(BaseModel):
    upper: str


async def to_upper(msg: In, _ctx) -> Out:
    return Out(upper=msg.text.upper())


async def main() -> None:
    node = Node(to_upper, name="to_upper", policy=NodePolicy(validate="both"))

    registry = ModelRegistry()
    registry.register("to_upper", In, Out)

    flow = create(node.to())
    flow.run(registry=registry)

    await flow.emit(In(text="hello"))
    result: Out = await flow.fetch()
    await flow.stop()

    print(result.upper)


if __name__ == "__main__":
    asyncio.run(main())

2) ReactPlanner via CLI (fastest path)

uv run penguiflow new my-agent --template react
cd my-agent
uv sync
uv run penguiflow dev --project-root .

Documentation (canonical)

• Docs site (MkDocs): https://hurtener.github.io/penguiflow/
• Source docs in repo: docs/

Suggested starting points (in-repo sources):

• Getting started: docs/getting-started/quickstart.md
• Core runtime: docs/core/flows-and-nodes.md, docs/core/messages-and-envelopes.md
• Planner: docs/planner/overview.md
• Tool integrations: docs/tools/configuration.md
• Deployment runbooks: docs/deployment/production-deployment.md
• Observability runbooks: docs/observability/metrics-and-alerts.md
• CLI: docs/cli/overview.md

Stability, versioning, and public API

PenguiFlow follows a 2.x line and aims to follow SemVer with a clear public surface.

• Changelog: CHANGELOG.md
• Versioning & deprecations: VERSIONING.md
• Public API surface: docs/reference/public-api.md

Contributing, security, and support

• Contributing: CONTRIBUTING.md
• Code of Conduct: CODE_OF_CONDUCT.md
• Security: SECURITY.md
• Support: SUPPORT.md

License

MIT — see LICENSE.