Harness Backends¶

PyFlue uses a backend registry so the public session API can stay stable while teams can choose the harness runtime that fits their project.

Built-In Backends¶

Backend	Status	Package line
`deepagents`	Implemented	`deepagents>=0.5.6,<0.6.0`
`openai_agents`	Extension point	`openai-agents>=0.15.1,<0.16.0`
`google_adk`	Extension point	`google-adk>=1.32.0,<1.33.0`
`pydanticai`	Extension point	`pydantic-ai>=1.89.1,<1.90.0`

DeepAgents Backend¶

The DeepAgents backend is the default:

agent = await init(harness="deepagents")

The DeepAgents backend provides:

model
project instructions
Markdown skills
session continuity
sandbox file tools
shell execution through policy
task-friendly agent behavior
optional Python code tool when Monty is enabled

Custom Backend Registration¶

from pyflue import register_harness
from pyflue.harnesses.base import HarnessBackend


class CustomBackend(HarnessBackend):
    name = "custom"

    async def run(self, **kwargs):
        ...


register_harness("custom", CustomBackend)

Then use it:

agent = await init(harness="custom")

Optional Backends¶

OpenAI Agents SDK, Google ADK, and Pydantic AI are available as optional package extras for teams that want to build custom backends behind the PyFlue API.

uv add "pyflue[openai]"
uv add "pyflue[google]"
uv add "pyflue[pydanticai]"

pip install "pyflue[openai]"
pip install "pyflue[google]"
pip install "pyflue[pydanticai]"