"""用例7：多轮对话累积 —— 追踪连续多轮对话中延迟随上下文累积的变化"""
from ..ollama_client import OllamaClient
from .base import case_meta, make_result

DEBUG_SCENARIOS = [
    "修复Python中的索引越界错误",
    "修复JavaScript闭包变量捕获问题",
    "修复SQL注入漏洞",
    "修复多线程竞态条件",
    "修复递归栈溢出",
    "修复正则表达式灾难回溯",
]


def run_test(client: OllamaClient, repeats: int = 1, stop_event=None) -> dict:
    """执行多轮对话累积测试（使用 /api/chat 累积上下文）

    repeats 控制总轮次数，每轮切换不同调试场景。
    """
    results = []
    messages = []

    for i in range(repeats):
        if stop_event and stop_event.is_set():
            break
        scenario = DEBUG_SCENARIOS[i % len(DEBUG_SCENARIOS)]

        user_msg = f"（对话第{i + 1}轮）请协助：{scenario}。请简要给出你的分析。"
        messages.append({"role": "user", "content": user_msg})

        infer = client.chat(messages, options={"temperature": 0.3, "num_predict": 120})

        assistant_reply = infer.response
        messages.append({"role": "assistant", "content": assistant_reply})

        results.append(make_result(
            infer, i + 1,
            round=i + 1,
            scenario=scenario,
            messages_in_context=len(messages),
        ))

    meta = case_meta(
        "case_07_multiturn", "多轮对话累积",
        "追踪连续多轮对话中延迟随上下文累积的变化", "耗时", 10,
    )
    meta["results"] = results
    meta["total_rounds"] = len(results)
    return meta