QingLong/AI/T3_TextSummarize.py

from pathlib import Path
from typing import Optional, Tuple
from openai import OpenAI, APIError


class ContentAnalyzer:
    """课程内容分析器"""

    def __init__(
            self,
            api_key: str = "sk-01d13a39e09844038322108ecdbd1bbc",
            base_url: str = "https://dashscope.aliyuncs.com/compatible-mode/v1",
            model: str = "deepseek-v3"
    ):
        """
        初始化分析器

        :param api_key: 阿里云API密钥
        :param base_url: API基础地址
        :param model: 使用的模型名称
        """
        self.client = OpenAI(api_key=api_key, base_url=base_url)
        self.model = model

    def analyze_content(
            self,
            content: str,
            prompt_template: str = "帮我梳理：这节课分了几个部分，每部分的名称和开始的时间是多少：{}"
    ) -> Tuple[bool, str]:
        """
        分析课程内容结构

        :param content: 需要分析的文本内容
        :param prompt_template: 提示词模板，需包含一个{}用于插入内容
        :return: (成功标志, 分析结果或错误信息)
        """
        try:
            full_prompt = prompt_template.format(content)

            completion = self.client.chat.completions.create(
                model=self.model,
                messages=[{'role': 'user', 'content': full_prompt}]
            )

            if not completion.choices:
                return False, "API响应中未包含有效结果"

            return True, completion.choices[0].message.content

        except APIError as e:
            return False, f"API调用失败: {str(e)}"
        except Exception as e:
            return False, f"未处理的异常: {str(e)}"

    def analyze_file(
            self,
            file_path: Path,
            output_path: Optional[Path] = None,
            encoding: str = 'utf-8'
    ) -> Tuple[bool, str]:
        """
        从文件读取内容并分析

        :param file_path: 输入文件路径
        :param output_path: 输出文件路径（可选）
        :param encoding: 文件编码格式
        :return: (成功标志, 最终结果或错误信息)
        """
        try:
            if not file_path.exists():
                return False, f"文件不存在: {file_path}"

            content = file_path.read_text(encoding=encoding)
            success, result = self.analyze_content(content)

            if not success:
                return False, result

            # 保存结果
            if output_path:
                try:
                    output_path.write_text(result, encoding=encoding)
                except IOError as e:
                    return False, f"结果保存失败: {str(e)}"

            return True, result

        except UnicodeDecodeError:
            return False, f"文件解码失败，请尝试使用正确的编码格式（当前使用 {encoding}）"
        except Exception as e:
            return False, f"文件处理异常: {str(e)}"


def analyzer_action(input_file, output_file):
    # 使用示例
    analyzer = ContentAnalyzer()
    success, result = analyzer.analyze_file(input_file, output_file)
    if success:
        print("✅ 分析成功！结果如下：\n")
        print(result)
    else:
        print(f"❌ 分析失败: {result}")

if __name__ == '__main__':
    input_file = Path(r"D:\dsWork\QingLong\AI\音频文本.txt")
    output_file = Path(r"D:\dsWork\QingLong\AI\分析结果.txt")
    analyzer_action(input_file, output_file)