import json
import os
import logging

import requests

from Config.Config import GLM_API_KEY, GLM_MODEL_NAME, GLM_BASE_URL, OBS_PREFIX, OBS_AK, OBS_SK, OBS_SERVER, OBS_BUCKET
from Util.ObsUtil import ObsUploader


# 配置日志
def setup_logger():
    logger = logging.getLogger(__name__)
    if not logger.handlers:
        logger.setLevel(logging.INFO)
        handler = logging.StreamHandler()
        formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
        handler.setFormatter(formatter)
        logger.addHandler(handler)
    return logger


logger = setup_logger()


# 批量处理图片
def batch_glm(output_dir, img_list):
    qvq_result = f"{output_dir}/QvqResult.json"
    if os.path.exists(qvq_result):
        logger.info(f"GLM结果文件已存在，直接返回: {qvq_result}")
        return qvq_result

    img_url_list = []
    for file_path in img_list:
        # 创建上传器实例
        uploader = ObsUploader(OBS_AK, OBS_SK, "https://" + OBS_SERVER)
        # 上传参数
        object_key = OBS_PREFIX + "/" + file_path
        # 执行上传
        success, result = uploader.upload_file(OBS_BUCKET, object_key, file_path)
        # 处理结果
        if success:
            logger.info(f'{file_path}上传成功!')
            # 获取上传文件的 URL
            file_url = f"https://{OBS_BUCKET}.{OBS_SERVER}/{object_key}"
            img_url_list.append(file_url)
        else:
            logger.error(f'{file_path}上传失败!')
            if 'errorCode' in result:
                logger.info(f'错误代码: {result["errorCode"]}')
                logger.info(f'错误信息: {result["errorMessage"]}')
            else:
                logger.error(f'错误信息: {result["error"]}')
    # 多张图片开始解析
    answer_content = ""
    for img_url in img_url_list:
        answer_content = answer_content + glm_single(img_url)

    # 保存结果到JSON文件
    with open(qvq_result, "w", encoding='utf-8') as f:
        f.write(answer_content)
    return qvq_result


def glm_single(img_url):
    logger.info(f"开始调用GLM API识别几何图形: {img_url}")
    url = GLM_BASE_URL
    headers = {
        "Authorization": "Bearer " + GLM_API_KEY,
        "Content-Type": "application/json"
    }
    prompt = """
    ### 几何图形识别专家指令（输入：纯几何图形照片）
    
    **任务目标**
    精确提取图形中的几何元素及其空间关系，为GeoGebra重建建立数学模型
    
    ## 一、坐标系建立规则（必须遵守）
    1. 原点设定：
       - 若存在明显顶点，选最左下角的点为原点(0,0)
       - 若图形对称，选对称中心为原点
       - 示例：原点O = 三角形ABC的顶点A
    
    2. 坐标轴定向：
       - 优先顺序：水平线段 > 垂直线段 > 最长线段
       - 具体规则：
         if 存在水平线段: 以该线段为x轴正方向
         elif 存在垂直结构: 以最左侧垂直线为y轴
         else: 以最长线段为基准轴
    
    ## 二、元素列举
    1. 按点，线，三角形，四边形，梯形，平行四边形，矩形，正方形，圆等由简单到复杂的顺序列举所有图形
    2. 详细描述元素之间的关系，比如点D在线段AB上
    3. 详细描述元素之间的位置关系，比如D 在A点正上方，B在CD边的上方中间位置
    
    """

    data = {
        "model": GLM_MODEL_NAME,
        "messages": [
            {
                "role": "user",
                "content":
                    [
                        {
                            "type": "text",
                            "text": prompt
                        },
                        {
                            "type": "image_url",
                            "image_url": {
                                "url": img_url
                            }
                        }
                    ]
            }
        ],
        "stream": True  # 启用流式调用
    }

    answer_content = ''
    try:
        with requests.post(url, headers=headers, json=data, stream=True) as response:
            for chunk in response.iter_lines():
                if chunk:
                    decoded = chunk.decode('utf-8')
                    if decoded.startswith('[DONE]'):
                        logger.info("GLM API调用完成！")
                        break
                    try:
                        decoded = decoded[5:]
                        json_data = json.loads(decoded)
                        content = json_data["choices"][0]["delta"]['content']
                        if content and len(content) > 0:
                            print(content, end="")
                            answer_content = answer_content + content
                    except Exception as e:
                        logger.error(f"解析响应 chunk 时出错: {e}")

        answer_content = answer_content.replace("```json", "")
        answer_content = answer_content.replace("```", "")
        return answer_content
    except Exception as e:
        logger.error(f"GLM API调用失败: {e}")
        raise