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Control how autonomous agents operate, including autonomy levels, doom-loop detection, memory integration, and completion signals.

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Quick Start

1

Simple Enable

Enable autonomy with defaults:
from praisonaiagents import Agent

agent = Agent(
    name="Autonomous Agent",
    instructions="Work autonomously",
    autonomy=True
)
2

With Configuration

Configure autonomy behavior:
from praisonaiagents import Agent, AutonomyConfig

agent = Agent(
    name="Autonomous Agent",
    instructions="Work autonomously",
    autonomy=AutonomyConfig(
        level="auto_edit",
        max_iterations=30,
        doom_loop_threshold=5,
        auto_escalate=True,
    )
)
3

With Memory Integration

Autonomy loops auto-save sessions between iterations when memory is enabled:
from praisonaiagents import Agent, AutonomyConfig

agent = Agent(
    name="Persistent Agent",
    instructions="Work autonomously with memory",
    autonomy=AutonomyConfig(max_iterations=20),
    memory=True,
    auto_save="my_session",
)

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Configuration Options

from praisonaiagents import AutonomyConfig, AutonomyLevel

config = AutonomyConfig(
    # Core settings
    enabled=True,                      # Enable/disable autonomy
    level="suggest",                   # Autonomy level (suggest, auto_edit, full_auto)
    max_iterations=20,                 # Max loop iterations before stopping
    
    # Doom loop detection
    doom_loop_threshold=3,             # Repeated actions before doom loop triggers
    auto_escalate=True,                # Escalate to user when stuck
    
    # Completion signals
    completion_promise="TASK_DONE",    # Structured promise tag for completion
    
    # Observability
    observe=False,                     # Emit trace events
    
    # Context management
    clear_context=False,               # Clear chat history between iterations
    
    # Verification
    verification_hooks=None,           # List of VerificationHook instances
)
ParameterTypeDefaultDescription
enabledboolTrueWhether autonomy is enabled
levelstr"suggest"Autonomy level (suggest, auto_edit, full_auto)
max_iterationsint20Maximum iterations before stopping
doom_loop_thresholdint3Number of repeated actions to trigger doom loop
auto_escalateboolTrueAutomatically escalate complexity when stuck
completion_promisestr | NoneNoneStructured completion signal (e.g. "DONE")
observeboolFalseEmit observability events during loop
clear_contextboolFalseClear chat history between iterations
verification_hookslist | NoneNoneVerificationHook instances for output verification

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Autonomy Levels

LevelEnum ValueDescription
suggestAutonomyLevel.SUGGESTAgent suggests actions, user approves
auto_editAutonomyLevel.AUTO_EDITAgent edits files, user reviews critical changes
full_autoAutonomyLevel.FULL_AUTOAgent operates fully autonomously
from praisonaiagents import AutonomyLevel

# Use enum or string - both work
config = AutonomyConfig(level=AutonomyLevel.AUTO_EDIT.value)
config = AutonomyConfig(level="auto_edit")

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Common Patterns

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Pattern 1: Safe Autonomous Agent

from praisonaiagents import Agent, AutonomyConfig

agent = Agent(
    name="Safe Agent",
    instructions="Work carefully",
    autonomy=AutonomyConfig(
        level="suggest",
        max_iterations=10,
        doom_loop_threshold=3,
        auto_escalate=True,
    )
)

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Pattern 2: Full Autonomy with Completion Promise

from praisonaiagents import Agent, AutonomyConfig

agent = Agent(
    name="Full Auto Agent",
    instructions="Complete autonomy",
    autonomy=AutonomyConfig(
        level="full_auto",
        max_iterations=50,
        completion_promise="ALL_DONE",
    )
)

# Unified API — start() automatically uses the autonomous loop!
result = agent.start("Build the feature end to end")
print(f"Success: {result.success}, Iterations: {result.iterations}")

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Pattern 3: Multi-Agent Autonomy Propagation

from praisonaiagents import Agent, AgentTeam, AutonomyConfig

researcher = Agent(name="Researcher", instructions="Research topics")
writer = Agent(name="Writer", instructions="Write articles")

# AgentTeam propagates autonomy to all agents
team = AgentTeam(
    agents=[researcher, writer],
    autonomy=AutonomyConfig(max_iterations=30),
)

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Best Practices

Begin with suggest level and increase autonomy as you gain confidence.
Keep doom_loop_threshold at 3-5 to prevent agents from repeating the same action.
Combine autonomy=True with memory=True and auto_save to persist progress between iterations.
Use completion_promise for structured completion signals instead of relying on keyword detection.

Autonomy Loop

Learn about the autonomy loop

Ralph Loops

Autonomous execution pattern