Skip to main content
The framework: key in YAML picks which execution backend runs your agents — but the rules differ between agents.yaml and workflow YAML. 
from praisonaiagents import Agent, PraisonAIAgents

agent = Agent(name="Writer", instructions="Write helpful posts")
PraisonAIAgents(agents=[agent]).start("Write about caching")
The user picks a YAML file; framework: selects the backend that runs the workflow.

​
Quick Start

1

agents.yaml — any registered framework

framework: crewai
topic: Write a blog post
roles:
  writer:
    role: Writer
    goal: Write engaging posts
    backstory: Senior editor
    tasks:
      draft:
        description: Write a post about {topic}
        expected_output: A 500-word post

praisonai agents.yaml
2

workflow YAML — needs SUPPORTS_WORKFLOW

framework: praisonai
type: job
steps:
  - id: research
    agent: researcher
  - id: write
    agent: writer
    depends_on: [research]

praisonai workflow.yaml

​
Which file uses which?

YAML shapeEngineframework: choices
roles: / topic: (agents.yaml)AgentsGenerator + registryAny registered adapter (crewai, praisonai, autogen, plus entry-point plugins)
steps: + workflow: (workflow YAML)Native Workflow engineAny adapter whose SUPPORTS_WORKFLOW = True (built-in praisonai qualifies)
type: job / type: hybrid (workflow YAML)Native Workflow engineAny adapter whose SUPPORTS_WORKFLOW = True (built-in praisonai qualifies)
Workflow YAML dispatch requires an adapter whose SUPPORTS_WORKFLOW = True. The built-in praisonai adapter has it. Third-party adapters opt in by setting the flag on their subclass — see Capability Flags. If framework: is omitted, agents.yaml defaults via FrameworkAdapterRegistry.pick_default() and workflow YAML defaults to praisonai.

​
What you’ll see if the framework isn’t workflow-capable

Selecting a framework whose adapter has SUPPORTS_WORKFLOW = False raises: 
ValueError: framework='crewai' in workflow YAML is not supported for workflow execution.
The workflow engine requires an adapter whose SUPPORTS_WORKFLOW flag is set (the native 'praisonai' adapter does).
Use a non-workflow agents.yaml with a supported registered framework, or set framework: praisonai. Frameworks supporting workflow execution: praisonai.
The trailing list names every registered adapter whose SUPPORTS_WORKFLOW flag is True, so it grows as you install workflow-capable plugins.

​
Make a custom framework workflow-capable

Set SUPPORTS_WORKFLOW = True on your adapter subclass to accept workflow YAML dispatch: 
from praisonaiagents import BaseFrameworkAdapter

class MyWorkflowFrameworkAdapter(BaseFrameworkAdapter):
    name = "myframework"
    SUPPORTS_WORKFLOW = True

    def is_available(self) -> bool:
        return True

    def run(self, config, llm_config, topic, *,
            tools_dict=None, agent_callback=None,
            task_callback=None, cli_config=None) -> str:
        return f"myframework ran: {topic}"
Once registered, myframework is accepted in workflow YAML and appears in the “Frameworks supporting workflow execution” list. See Capability Flags.

​
What to do

​
Programmatic check

from praisonai.framework_adapters.workflow_framework import (
    validate_workflow_framework,
    framework_from_config,
)

cfg = {"framework": "praisonai", "steps": []}
fw = framework_from_config(cfg)         # "praisonai"
validate_workflow_framework(fw)         # no-op when valid; raises ValueError otherwise
framework_from_config({}) returns "praisonai" (safe default). framework_from_config({"framework": "CrewAI"}) returns "crewai" (lowercased before validation). validate_workflow_framework() reads the adapter’s SUPPORTS_WORKFLOW flag from the default registry. Pass registry= to test against an isolated registry: 
from praisonai.framework_adapters.registry import FrameworkAdapterRegistry

reg = FrameworkAdapterRegistry()
reg.register("myframework", MyWorkflowFrameworkAdapter)
validate_workflow_framework("myframework", registry=reg)   # passes when SUPPORTS_WORKFLOW = True

​
How It Works

​
Best Practices

If you need CrewAI, AutoGen, or a custom framework, write your config as roles:/topic: agents.yaml. The framework: key there accepts any registered adapter.
The default is praisonai, so you can omit the framework: key entirely in workflow YAML. This avoids accidentally setting an unsupported value.
Call validate_workflow_framework(fw) immediately after parsing config if you’re building tooling around workflow YAML. It raises ValueError with an actionable message before any execution starts. Pass registry= to validate against an isolated registry in tests.
A custom adapter cannot run workflow YAML until it sets SUPPORTS_WORKFLOW = True (class-level). Leaving it False keeps the adapter agents.yaml-only and blocks workflow dispatch with a clear error.
Use list_framework_choices() from praisonai.framework_adapters.registry to populate dropdowns or CLI help text — it includes entry-point plugins automatically.
from praisonai.framework_adapters.registry import list_framework_choices

choices = list_framework_choices()
print(choices)  # ['crewai', 'praisonai', 'autogen', 'my_plugin']

Add new execution backends via Python entry points

Full workflow YAML reference