Human-in-the-Loop Review

from praisonaiagents import Agent, Task, AgentTeam
from praisonaiagents.config.feature_configs import MultiAgentHooksConfig

REVIEW_TASKS = {"research"}

def review_gate(task, task_output):        # signature: (task, task_output)
    if task.name not in REVIEW_TASKS:
        return
    print(f"\n--- Review: {task.name} ---\n{task_output.raw}\n")
    choice = input("Approve (y), reject (n), edit (e)? ").strip().lower()
    if choice == "e":
        # downstream tasks that read this task via context=[t1] see the edit
        task_output.raw = input("Edited output: ").strip()

researcher = Agent(name="Researcher", role="Researcher", goal="Research", backstory="Expert")
writer = Agent(name="Writer", role="Writer", goal="Write", backstory="Writer")

t1 = Task(name="research", description="List 5 facts about {{topic}}",
          expected_output="5 bullets", agent=researcher)
t2 = Task(name="summary", description="Write 3-sentence summary",
          expected_output="3 sentences", agent=writer, context=[t1])

team = AgentTeam(
    agents=[researcher, writer],
    tasks=[t1, t2],
    process="sequential",
    variables={"topic": "REST APIs"},   # NOT team.start(inputs=...) — see Gotchas
    hooks=MultiAgentHooksConfig(on_task_complete=review_gate),
)
team.start()

def review_output(task_output):          # signature: (task_output)
    print(f"\n--- Review output ---\n{task_output.raw}\n")
    if input("Approve? (y/n) ").strip().lower() == "n":
        raise RuntimeError("Human rejected output")

t1_strict = Task(
    name="research",
    description="List 5 facts about {{topic}}",
    expected_output="5 bullets",
    agent=researcher,
    variables={"topic": "REST APIs"},
    on_task_complete=review_output,       # 1-arg signature
    fail_on_callback_error=True,          # REQUIRED so reject halts the workflow
)