Agentic Patterns

from turingpulse_sdk import instrument

@instrument(
    name="react-agent",
    agentic_pattern="react",
    metadata={
        "max_iterations": 10,
        "tools": ["search", "calculate"]
    }
)
def react_agent(query: str):
    # Captured automatically:
    # - Each thought/action/observation step
    # - Iteration count and early stops
    # - Tool calls with inputs/outputs
    return run_react_loop(query)

@instrument(
    name="planner-agent",
    agentic_pattern="plan_and_execute",
    metadata={
        "max_plan_steps": 5,
        "replanning_enabled": True
    }
)
def planner_agent(query: str):
    # Captured automatically:
    # - Initial plan generation
    # - Each execution step
    # - Plan modifications/replanning
    return run_plan_and_execute(query)

@instrument(
    name="reflexion-agent",
    agentic_pattern="reflexion",
    metadata={
        "max_reflections": 3,
        "improvement_threshold": 0.1
    }
)
def reflexion_agent(query: str):
    # Captured automatically:
    # - Initial attempt
    # - Reflection/critique steps
    # - Improvement iterations
    return run_reflexion_loop(query)

@instrument(
    name="multi-agent-team",
    agentic_pattern="multi_agent",
    metadata={
        "agents": ["researcher", "writer", "reviewer"],
        "communication": "sequential"
    }
)
def multi_agent_team(query: str):
    # Captured automatically:
    # - Parent-child span relationships
    # - Inter-agent messages
    # - Agent handoffs
    return run_multi_agent(query)