import json
import requests
import os

# 配置文件路径
test_file_path = r"D:\workstation\chinese-roberta-wwm-ext\model-train-eval-NN\AI标注\test.json"
output_dir = r"D:\workstation\chinese-roberta-wwm-ext\model-train-eval-NN\AI标注\test01"

# 确保输出目录存在
os.makedirs(output_dir, exist_ok=True)

# 读取测试数据
with open(test_file_path, 'r', encoding='utf-8') as f:
    test_data = json.load(f)

print(f"📁 加载测试数据: {len(test_data)} 条记录")

# 服务地址
url = "http://localhost:8888/segment_batch_simple"

# 准备请求数据 - 直接使用原始格式
broadcasts = test_data

print(f"🚀 开始调用双路径边界分类器批量分段接口...")

# 发送请求
try:
    response = requests.post(url, json=broadcasts)

    if response.status_code == 200:
        result = response.json()
        print("✅ 批量分段成功!")
        print(f"模型: {result['model']}")
        print(f"总计: {result['total']}")
        print(f"成功: {result['success']}")
        print(f"失败: {result['failed']}")
        print(f"处理时间: {result['processing_time']}秒")

        print("\n📝 分段结果:")
        print("=" * 80)

        for broadcast_id, segments in result['results'].items():
            print(f"\n📻 {broadcast_id}:")

            if 'error' in segments:
                print(f"❌ 错误: {segments['error']}")
            else:
                for para_key, para_content in segments.items():
                    print(f"  {para_key}: {para_content}")

        # 保存结果到文件
        output_file = os.path.join(output_dir, "batch_segment_results.json")
        with open(output_file, 'w', encoding='utf-8') as f:
            json.dump(result, f, ensure_ascii=False, indent=2)

        print(f"\n💾 结果已保存到: {output_file}")

    else:
        print(f"❌ 请求失败: HTTP {response.status_code}")
        print(response.text)

except requests.exceptions.ConnectionError:
    print("❌ 连接失败，请确保双路径边界分类器服务正在运行")
    print("   启动命令: python simplified_dual_path_boundary_classifier_api.py")
    print("   服务地址: http://localhost:8888")
except Exception as e:
    print(f"❌ 调用失败: {e}")