Recursive Context

from praisonaiagents.context.artifacts import ArtifactRef, ArtifactStoreProtocol

# ArtifactRef replaces large content in context
ref = ArtifactRef(
    path="/path/to/artifact.json",
    summary="API response with 50,000 records",
    size_bytes=1_200_000,
    mime_type="application/json",
)

# In context window: [Artifact: /path/to/artifact.json (1.2 MB) - API response...]

from praisonaiagents.agents.delegator import SubagentDelegator

delegator = SubagentDelegator()
result = await delegator.delegate(
    agent_name="analyzer",
    objective="Count billing questions",
    context={"user_ids": [12345, 67890]}
)

# Automatic doom loop detection
agent = Agent(
    instructions="...",
    autonomy={"doom_loop_threshold": 3}  # Stop after 3 repeated actions
)

from praisonaiagents import Agent

# Enable recursive context handling
agent = Agent(
    instructions="You are a data analyst.",
    autonomy=True,  # Enables all RLM features
    allow_code_execution=True,  # REPL capability
)

# Runs with automatic:
# - Context windowing (artifacts for large outputs)
# - Subagent delegation (recursive problem decomposition)
# - Escalation (progressive complexity)
# - Doom loop protection
result = agent.run_autonomous("Analyze 5000 tickets and count billing issues")

agent = Agent(
    instructions="...",
    autonomy={
        "max_iterations": 30,      # Max turns before stopping
        "doom_loop_threshold": 3,  # Repeated actions limit
        "auto_escalate": True,     # Auto-increase complexity
    }
)

from praisonaiagents.context.artifacts import QueueConfig

config = QueueConfig(
    enabled=True,
    inline_max_bytes=32 * 1024,  # >32KB → artifact
    redact_secrets=True,          # Auto-redact API keys
    summary_max_chars=200,
)