# A single trajectory: one complete agent interaction
traj = art.Trajectory(
    messages_and_choices=[
        {"role": "system", "content": "You are a RAG support agent..."},
        {"role": "user", "content": "What is the refund policy?\n\n[Context]: ..."},
        Choice(finish_reason="stop", index=0,
               message=ChatCompletionMessage(role="assistant", content="...")),
    ],
    reward=0.0,  # RULER fills this in
)

# A group: multiple trajectories for the same scenario
group = art.TrajectoryGroup([traj_a, traj_b, traj_c, traj_d])

# Score the entire group relatively
judged_group = await ruler_score_group(group, "openai/o3")