motosan-agent-workflow (Python)
A general-purpose DAG-based agent workflow engine for orchestrating LLM agents.
Installation
pip install motosan-agent-workflow
# Optional YAML support:
pip install "motosan-agent-workflow[yaml]"
Quick Start
import asyncio
from motosan_agent_workflow import (
Workflow, Node, Runtime, LlmClient, LlmResponse,
)
class MyLlm(LlmClient):
async def call(self, system_prompt: str, input_data: dict, tools: list[str]) -> LlmResponse:
return LlmResponse(content={"answer": "..."}, input_tokens=100, output_tokens=50)
async def main():
workflow = (
Workflow.builder("my-pipeline")
.node(Node.agent("researcher", system_prompt="Find key facts about the topic."))
.node(Node.agent("writer", system_prompt="Write a report.", input_from=["researcher"]))
.edge("researcher", "writer")
.build()
)
runtime = Runtime(MyLlm())
result = await runtime.execute(workflow, {"topic": "Python in 2026"})
print(result.node_output("writer").content)
asyncio.run(main())
YAML Workflow
from motosan_agent_workflow import load_workflow, load_workflow_from_str, Format
# From file
workflow = load_workflow("my-workflow.yaml")
# From string
workflow = load_workflow_from_str(yaml_str, Format.YAML)
Node Types
| Type | Description | LLM |
|---|---|---|
Node.agent() |
LLM-powered agent | Yes |
Node.human() |
Human-in-the-loop gate | No |
Node.transform() |
Pure function transform | No |
Node.condition() |
Conditional branching | No |
Node.loop_node() |
Iterative loop | Depends |
Node.sub_workflow() |
Nested sub-workflow | Depends |
Features
- Parallel execution — Nodes in the same DAG layer run concurrently via
asyncio.gather - Output schema validation — JSON Schema with auto self-correction
- Retry policies — Per-node exponential backoff with Skip/Abort/Fallback modes
- Human-in-the-loop — Gates with timeout and default action
- Event streaming —
WorkflowEventvia async callback - Token tracking — Per-node and total, with budget enforcement
- Cost estimation — Pre-execution cost estimates with configurable pricing
- YAML/JSON loader —
load_workflow()andload_workflow_from_str() - 8 built-in templates — code-review, research, brainstorm, report, playlist, content, architecture-review, sprint-planning
Requirements
- Python >= 3.10
- Optional:
pyyaml >= 6.0for YAML support
Publishing
git tag python-v0.3.0
git push origin python-v0.3.0
# → triggers publish-python.yml → PyPI
Metadata
Release files for motosan-agent-workflow 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| motosan_agent_workflow-0.3.0.tar.gz | 22.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| motosan_agent_workflow-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 43.5 kB
Release files / motosan_agent_workflow-0.3.0.tar.gz
| Download URL | motosan_agent_workflow-0.3.0.tar.gz |
|---|---|
| Size | 22.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b4fdb824fc9faef4cf58d42d301e23c957b1c6debdf753db6511f537b18230db
|
|
BLAKE2b-256 checksum How to use checksums |
069870fd8d0bf746a32f799501422e9d047354e21d700851e7821af8389d2916
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.6
|
Release files / motosan_agent_workflow-0.3.0-py3-none-any.whl
| Download URL | motosan_agent_workflow-0.3.0-py3-none-any.whl |
|---|---|
| Size | 21.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
462fc6b50069f986aba81bc00d89d48abf80950ce34acf929de2f7ec5070de88
|
|
BLAKE2b-256 checksum How to use checksums |
3c2225840b047f2e6792d114c786cd2131f49e5c89bb30a4e65ab91ffc90e02a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.6
|
Security for motosan-agent-workflow 0.3.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.