Workflow YAML Framework Field

How the framework: key in YAML chooses an execution backend

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 shape	Engine	framework: choices
roles: / topic: (agents.yaml)	AgentsGenerator + registry	Any registered adapter (crewai, praisonai, autogen, plus entry-point plugins)
steps: + workflow: (workflow YAML)	Native Workflow engine	Any adapter whose SUPPORTS_WORKFLOW = True (built-in praisonai qualifies)
type: job / type: hybrid (workflow YAML)	Native Workflow engine	Any 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

Use agents.yaml for multi-framework work

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.

Omit framework: in workflow YAML

The default is praisonai, so you can omit the framework: key entirely in workflow YAML. This avoids accidentally setting an unsupported value.

Validate early in custom code

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.

Set SUPPORTS_WORKFLOW to enable workflow YAML

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.

Check registry choices before building CLI menus

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']

---

Related

Add new execution backends via Python entry points

Full workflow YAML reference