"""
带流式输出的调试脚本 - 实时显示Agent的执行情况

使用方法：
    export PYTHONIOENCODING=utf-8 && python tests/debug_with_stream.py
"""

import sys
import os
from datetime import datetime

# 添加项目根目录到Python路径
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from src.agents.coordinator import create_research_coordinator
from src.config import Config


def stream_research(question: str, depth: str = "quick"):
    """
    调试研究流程，实时显示执行情况

    Args:
        question: 研究问题
        depth: 深度模式
    """
    print("\n" + "🔬 " * 40)
    print("智能深度研究系统 - 流式调试模式")
    print("🔬 " * 40)

    print(f"\n研究问题: {question}")
    print(f"深度模式: {depth}")
    print(f"开始时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")

    # 创建Agent
    print("\n" + "="*80)
    print("创建Agent...")
    print("="*80)

    try:
        agent = create_research_coordinator(
            question=question,
            depth=depth,
            format="technical",
            min_tier=3
        )
        print("✅ Agent创建成功")
    except Exception as e:
        print(f"❌ Agent创建失败: {e}")
        import traceback
        traceback.print_exc()
        return

    # 执行研究（使用stream模式）
    print("\n" + "="*80)
    print("开始执行（流式模式）...")
    print("="*80)

    try:
        start_time = datetime.now()

        # 使用stream方法实时显示
        step_count = 0
        for chunk in agent.stream({
            "messages": [
                {
                    "role": "user",
                    "content": f"请开始研究这个问题：{question}"
                }
            ]
        }):
            step_count += 1
            print(f"\n{'='*60}")
            print(f"步骤 #{step_count} - {datetime.now().strftime('%H:%M:%S')}")
            print('='*60)

            # 显示当前chunk的内容
            if isinstance(chunk, dict):
                # 检查是否有新消息
                if 'messages' in chunk:
                    messages = chunk['messages']
                    if messages:
                        last_msg = messages[-1]
                        msg_type = type(last_msg).__name__
                        print(f"消息类型: {msg_type}")

                        if hasattr(last_msg, 'content'):
                            content = last_msg.content
                            if content:
                                print(f"内容: {content[:200]}")

                        if hasattr(last_msg, 'tool_calls') and last_msg.tool_calls:
                            print(f"工具调用:")
                            for tc in last_msg.tool_calls:
                                print(f"  - {tc.get('name', 'unknown')}")

                # 检查是否有文件更新
                if 'files' in chunk:
                    files = chunk['files']
                    print(f"文件系统: {len(files)} 个文件")
                    for path in list(files.keys())[:5]:
                        print(f"  - {path}")

            # 超时保护
            elapsed = (datetime.now() - start_time).total_seconds()
            if elapsed > 120:  # 2分钟
                print("\n⚠️  超过2分钟，停止...")
                break

        end_time = datetime.now()
        duration = (end_time - start_time).total_seconds()

        print("\n" + "="*80)
        print("执行完成")
        print("="*80)
        print(f"总步骤数: {step_count}")
        print(f"总耗时: {duration:.2f}秒")

    except KeyboardInterrupt:
        print("\n\n⚠️  用户中断")
    except Exception as e:
        print(f"\n\n❌ 执行失败: {e}")
        import traceback
        traceback.print_exc()


if __name__ == "__main__":
    question = "Python asyncio最佳实践"
    stream_research(question, depth="quick")