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Documentation Index

Fetch the complete documentation index at: https://docs.praison.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Include praisonai package in your project

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Option 0: One-liner (simplest)

import praisonai

result = praisonai.run("agents.yaml")
print(result)
That’s it. praisonai.run() reuses the same framework auto-detection and LLM endpoint resolution the praisonai CLI uses, so anything that works on the command line works here.

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What it does

1
Auto-detects the first installed framework in this order: crewai → praisonaiagents → autogen → ag2. Pass framework="..." to override.
2
Reads OPENAI_API_KEY, OPENAI_BASE_URL, OPENAI_MODEL_NAME (and the standard PraisonAI key/config files) — same as the CLI.
3
Returns the final task output as a string.

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Async variant for FastAPI / Jupyter

import praisonai

async def handler():
    result = await praisonai.arun("agents.yaml")
    return result
arun() offloads the synchronous work to a thread so it never blocks the event loop.

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Optional parameters

ParameterTypeDefaultDescription
agent_filestrrequiredPath to your agents.yaml.
frameworkstr | NoneNone (auto-detect)One of "crewai", "praisonai", "autogen", "ag2".
toolslist | NoneNoneOptional list of tool callables passed through to AgentsGenerator.
agent_yamlstr | NoneNoneInline YAML string; takes precedence over agent_file when both are given.
cli_configdict | NoneNoneAdvanced: override the resolved CLI config (rarely needed).
If no framework is installed, run() raises RuntimeError("No supported framework installed. Install one of: crewai, praisonaiagents, autogen, ag2."). Install one with pip install praisonaiagents (recommended for new projects).

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When to use PraisonAI(...) instead

Reach for the full PraisonAI class (Option 1 below) when you need:
  • Streaming / approval-system integration
  • Custom backends or the gradio UI
  • The auto="..." natural-language-to-YAML mode
  • Repeated runs against the same generator without re-parsing YAML

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Option 1: Using RAW YAML

from praisonai import PraisonAI

# Example agent_yaml content
agent_yaml = """
framework: "crewai"
topic: "Space Exploration"

agents:  # Canonical: use 'agents' instead of 'roles'
  astronomer:
    role: "Space Researcher"
    goal: "Discover new insights about {topic}"
    instructions:  # Canonical: use 'instructions' instead of 'backstory' "You are a curious and dedicated astronomer with a passion for unraveling the mysteries of the cosmos."
    tasks:
      investigate_exoplanets:
        description: "Research and compile information about exoplanets discovered in the last decade."
        expected_output: "A summarized report on exoplanet discoveries, including their size, potential habitability, and distance from Earth."
"""

# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml)

# Run PraisonAI
result = praisonai.run()

# Print the result
print(result)

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Option 2: Using separate agents.yaml file

Note: Please create agents.yaml file before hand. If you only need to run an agents.yaml once and want zero ceremony, see Option 0: One-liner above. 
from praisonai import PraisonAI

def basic(): # Basic Mode
    praisonai = PraisonAI(agent_file="agents.yaml")
    praisonai.run()

if __name__ == "__main__":
    basic()

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Other options

from praisonai import PraisonAI

def basic(): # Basic Mode
    praisonai = PraisonAI(agent_file="agents.yaml")
    praisonai.run()
    
def advanced(): # Advanced Mode with options
    praisonai = PraisonAI(
        agent_file="agents.yaml",
        framework="autogen", # use AG2 framework (Formerly AutoGen)
    )
    praisonai.run()
    
def auto(): # Full Automatic Mode
    praisonai = PraisonAI(
        auto="Create a movie script about car in mars",
        framework="autogen" # use AG2 framework
    )
    print(praisonai.framework)
    praisonai.run()

if __name__ == "__main__":
    basic()
    advanced()
    auto()

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Logging in scripts

If you want PraisonAI to configure your application’s logging, call configure_cli_logging() once at startup: 
from praisonai import PraisonAI
from praisonai._logging import configure_cli_logging

configure_cli_logging("INFO")  # opt in to root-logger setup
PraisonAI(agent_file="agents.yaml").run()
If you want PraisonAI to leave your application’s logging untouched, just don’t call configure_cli_logging — only namespaced praisonai.* loggers will be used.