CLI Module

PraisonAI command-line interface and programmatic access

CLI Module

The CLI module provides the main PraisonAI class for running agents from YAML configurations and command-line.

Installation

pip install praisonai

PraisonAI Class

Main entry point for running PraisonAI agents.

from praisonai import PraisonAI

praison = PraisonAI(agent_file="agents.yaml")
result = praison.run()

Constructor

PraisonAI(
    agent_file: str = "agents.yaml",
    framework: str = "praisonai",
    auto: bool = False,
    agent_yaml: str = None,
    tools: list = None
)

Parameter	Type	Default	Description
agent_file	str	"agents.yaml"	Path to YAML agent definition
framework	str	"praisonai"	Framework: praisonai, crewai, autogen, langgraph, openai_agents, google_adk (precedence: CLI flag → YAML framework: → default)
auto	bool	False	Enable auto mode for agent generation
agent_yaml	str	None	YAML content as string (alternative to file)
tools	list	None	List of tools to make available

If neither --framework CLI flag nor YAML framework: key is set, PraisonAI defaults to the praisonai adapter.

Methods

run()

Execute the agents defined in the configuration.

result = praison.run()
print(result)

Returns: Agent execution result (string or structured output)

main()

CLI entry point method.

praison = PraisonAI()
praison.main()  # Parses CLI arguments and runs

CLI Usage

# Run with default agents.yaml
praisonai

# Specify agent file
praisonai --agent-file my-agents.yaml

# Auto mode - generate agents from prompt
praisonai --auto "Create a research team"

# Use specific framework
praisonai --framework crewai

# Interactive chat mode
praisonai --chat

# Code mode
praisonai --code "Fix the bug in main.py"

CLI Flags

Flag	Description
--agent-file	Path to YAML agent definition
--framework	Framework to use
--auto	Enable auto mode with prompt
--chat	Interactive chat mode
--code	Code agent mode
--ui	Launch web UI
--deploy	Deploy as API

YAML Configuration

framework: praisonaiagents
topic: Research AI trends
roles:
  researcher:
    role: Research Analyst
    goal: Research and analyze AI trends
    backstory: Expert researcher with deep knowledge
    tasks:
      research_task:
        description: Research the latest AI developments
        expected_output: Comprehensive research report

Programmatic Usage

With Tools

from praisonai import PraisonAI

def my_tool(query: str) -> str:
    return f"Result for {query}"

praison = PraisonAI(
    agent_file="agents.yaml",
    tools=[my_tool]
)
result = praison.run()

With YAML String

yaml_content = """
framework: praisonaiagents
topic: Test
roles:
  assistant:
    role: Helper
    goal: Help users
    tasks:
      help_task:
        description: Provide assistance
        expected_output: Helpful response
"""

praison = PraisonAI(agent_yaml=yaml_content)
result = praison.run()

See Also

• Auto Module - Automated agent generation
• Deploy Module - Deployment utilities
• CLI Documentation - Full CLI reference