"""
端到端验证脚本 — 用于无运营场景的 pipeline 测试

与 execute_once.py 的区别：
  - 用户消息里明确告诉 Agent"运营当前不在，发完审批请求不要阻塞等待"
  - send_approval_request 用 wait_for_reply=False
  - 跳过 execute_decisions（没审批结果不执行）
  - 生成报告收尾
"""
import asyncio
import os
import sys
from pathlib import Path

# 代理设置
os.environ.setdefault("HTTP_PROXY", "http://127.0.0.1:29758")
os.environ.setdefault("HTTPS_PROXY", "http://127.0.0.1:29758")

# 添加项目根目录到 Python 路径
sys.path.insert(0, str(Path(__file__).parent.parent.parent))

from dotenv import load_dotenv
load_dotenv()

from agent.core.runner import AgentRunner
from agent.trace import FileSystemTraceStore, Trace, Message
from agent.llm import create_openrouter_llm_call
from agent.utils import setup_logging

from examples.auto_put_ad_mini.config import (
    MAIN_CONFIG, SKILLS_DIR, TRACE_STORE_PATH, LOG_LEVEL, LOG_FILE,
)

# 导入自定义工具
from examples.auto_put_ad_mini.tools.data_query import fetch_creative_data, merge_creative_data
from examples.auto_put_ad_mini.tools.roi_calculator import calculate_roi_metrics
from examples.auto_put_ad_mini.tools.portfolio_metrics import calculate_portfolio_summary
from examples.auto_put_ad_mini.tools.ad_decision import get_ads_for_review, apply_decisions, query_ad_detail, modify_decisions
from examples.auto_put_ad_mini.tools.report_generator import generate_report
from examples.auto_put_ad_mini.tools.guardrails import validate_decisions
from examples.auto_put_ad_mini.tools.execution_engine import execute_decisions, check_execution_feedback
from examples.auto_put_ad_mini.tools.im_approval import send_approval_request, check_approval_status, send_feishu_text_message

try:
    from examples.auto_put_ad_mini.tools.feishu_doc import import_to_feishu
except ImportError:
    pass


async def main():
    base_dir = Path(__file__).parent
    setup_logging(level=LOG_LEVEL, file=LOG_FILE)

    prompt_path = base_dir / "prompts" / "system.prompt"
    system_prompt = prompt_path.read_text(encoding="utf-8") if prompt_path.exists() else ""

    presets_path = base_dir / "presets.json"
    if presets_path.exists():
        from agent.core.presets import load_presets_from_json
        load_presets_from_json(str(presets_path))

    store = FileSystemTraceStore(base_path=TRACE_STORE_PATH)
    runner = AgentRunner(
        trace_store=store,
        llm_call=create_openrouter_llm_call(model=MAIN_CONFIG.model),
        skills_dir=SKILLS_DIR if Path(SKILLS_DIR).exists() else None,
        logger_name="agents.auto_put_ad_mini_test",
    )

    config = MAIN_CONFIG
    if system_prompt:
        config.system_prompt = system_prompt

    print("=" * 70)
    print("  [端到端验证] 广告智能调控助手 — 无运营模式")
    print("=" * 70)
    print()

    # 关键指令（测试用）：告诉 Agent 跳过阻塞等待
    user_message = (
        "分析广告，执行完整的ROI计算和决策流程。请使用 2026-04-19（end_date=20260419）"
        "作为数据截止日期，因为 2026-04-20 的数据尚未回流。\n\n"
        "⚠️ 本次为端到端验证运行，运营当前不在：\n"
        "1. send_approval_request 必须用 wait_for_reply=False（不要阻塞等待飞书回复）\n"
        "2. 发送完审批请求后，直接调用 generate_report 生成报告收尾\n"
        "3. 不要调用 execute_decisions，因为没有实际审批通过\n"
        "4. 决策数量较多时，请严格按第四部分的 agent(task=[...]) 并发模式按 tier 拆分"
    )
    messages = [{"role": "user", "content": user_message}]
    config.trace_id = None

    step_count = 0
    last_approval_path = None

    try:
        async for item in runner.run(messages=messages, config=config):
            if isinstance(item, Trace):
                if item.status == "completed":
                    print(f"\n✅ [Trace] 完成 id={item.trace_id}")
                elif item.status == "failed":
                    print(f"\n❌ [Trace] 失败 id={item.trace_id}")

            elif isinstance(item, Message):
                if item.role == "assistant" and item.content:
                    content = item.content
                    text = content.get("text", "") if isinstance(content, dict) else content
                    if text and text.strip():
                        truncated = text[:300] + ("..." if len(text) > 300 else "")
                        print(f"\n💭 {truncated}\n")

                elif item.role == "tool" and item.content:
                    content = item.content
                    if isinstance(content, dict):
                        tool_name = content.get("tool_name", "unknown")
                        result = content.get("result", content.get("text", str(content)))
                        step_count += 1
                        marker = f"📌 步骤 {step_count}: {tool_name}"
                        print(f"\n{'='*70}\n{marker}\n{'='*70}")
                        text = result if isinstance(result, str) else str(result)
                        print(text[:400] + ("..." if len(text) > 400 else ""))

                        # 记录最后一个审批消息文件路径
                        if tool_name == "send_approval_request" and isinstance(result, str) and "req_" in result:
                            import re
                            m = re.search(r"req_\d+_\d+_[a-f0-9]+", result)
                            if m:
                                last_approval_path = f"outputs/approvals/{m.group(0)}.txt"

        print("\n" + "=" * 70)
        print("✅ 执行完成")
        print("=" * 70)
        if last_approval_path:
            print(f"📂 审批消息文件: {last_approval_path}")

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


if __name__ == "__main__":
    asyncio.run(main())