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193
dsLightRag/Util/AllLiuCheng.py
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193
dsLightRag/Util/AllLiuCheng.py
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import asyncio
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import logging
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import os
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import sys
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import aiofiles # 添加aiofiles导入
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from openai import AsyncOpenAI
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from Config.Config import *
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# 配置日志
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logger = logging.getLogger(__name__)
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class LLMClient:
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"""
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大语言模型客户端封装类，提供与LLM的交互功能
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"""
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def __init__(self, api_key=None, base_url=None, model_name=None, system_prompt=""):
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"""
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初始化LLM客户端
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@param api_key: API密钥，默认为配置文件中的ALY_LLM_API_KEY
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@param base_url: API基础URL，默认为配置文件中的ALY_LLM_BASE_URL
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@param model_name: 模型名称，默认为配置文件中的ALY_LLM_MODEL_NAME
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@param system_prompt: 系统提示词，默认使用预设的学伴角色提示词
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"""
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self.api_key = api_key or ALY_LLM_API_KEY
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self.base_url = base_url or ALY_LLM_BASE_URL
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self.model_name = model_name or ALY_LLM_MODEL_NAME
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self.system_prompt = system_prompt # 添加这一行来初始化system_prompt属性
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async def get_response(self, query_text: str, knowledge_content: str = "", stream: bool = True):
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"""
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异步获取大模型响应
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@param query_text: 查询文本
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@param knowledge_content: 可选的知识内容，将作为上下文提供给模型
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@param stream: 是否使用流式输出
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@return: 流式响应生成器或完整响应文本
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"""
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try:
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# 创建AsyncOpenAI客户端
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client = AsyncOpenAI(
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api_key=self.api_key,
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base_url=self.base_url,
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)
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# 构建完整的查询文本
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full_query = query_text
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if knowledge_content:
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full_query = f"选择作答的相应知识内容:{knowledge_content}\n下面是用户提的问题：{query_text}"
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# 创建请求
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completion = await client.chat.completions.create(
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model=self.model_name,
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messages=[
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{'role': 'system', 'content': self.system_prompt},
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{'role': 'user', 'content': full_query}
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],
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stream=stream
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)
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if stream:
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# 流式输出模式，返回生成器
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async for chunk in completion:
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# 确保 chunk.choices 存在且不为空
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if chunk and chunk.choices and len(chunk.choices) > 0:
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# 确保 delta 存在
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delta = chunk.choices[0].delta
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if delta:
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# 确保 content 存在且不为 None 或空字符串
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content = delta.content
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if content is not None and content.strip():
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print(content, end='', flush=True)
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yield content
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else:
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# 非流式处理
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if completion and completion.choices and len(completion.choices) > 0:
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message = completion.choices[0].message
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if message:
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content = message.content
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if content is not None and content.strip():
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yield content
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except Exception as e:
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print(f"大模型请求异常: {str(e)}", file=sys.stderr)
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yield f"处理请求时发生异常: {str(e)}"
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# 保留原有接口以保持兼容性
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async def get_response_async(query_text: str, stream: bool = True):
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"""
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异步获取学伴角色的大模型响应（兼容旧接口）
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@param query_text: 查询文本
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@param stream: 是否使用流式输出
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@return: 流式响应生成器或完整响应文本
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"""
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# 创建LLM客户端实例
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llm_client = LLMClient()
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# 打开文件读取知识内容
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try:
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with open(r"D:\dsWork\dsProject\dsLightRag\static\YunXiao.txt", "r", encoding="utf-8") as f:
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zhishiContent = f.read()
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except Exception as e:
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print(f"读取知识文件失败: {str(e)}", file=sys.stderr)
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zhishiContent = ""
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# 调用封装的方法
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async for chunk in llm_client.get_response(query_text, zhishiContent, stream):
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yield chunk
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# 生成万有引力导学案函数（修改为异步函数）
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async def generate_gravitation_lesson_plan():
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"""
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生成万有引力导学案
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@return: 生成的导学案文本
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"""
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# 创建LLM客户端实例，设置专门的系统提示词
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system_prompt = """你是'国家中级教师资格'持证教研员，熟悉《中国义务教育物理课程标准（2022版）》，擅长设计'先学后教、以学定教'的导学案。请用'问题链'驱动学生自学，体现'学习目标—前置学习—问题探究—自主检测—疑问记录'五环节。"""
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llm_client = LLMClient(system_prompt=system_prompt)
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# 构建生成导学案的提示词
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prompt = """请围绕'万有引力'一节课，输出一份适用于八年级下的导学案，供学生课前45分钟完成。要求：
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1. 语言亲切，用'你'称呼学生；
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2. 问题难度梯度：识记→理解→应用；
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3. 至少2个生活化情境问题；
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4. 留3行空白让学生写'我还有哪些困惑'。
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【格式要求】
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严格按以下Markdown层级输出：
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### 1. 学习目标
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### 2. 前置学习（知识链接+阅读指引）
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### 3. 问题探究（问题链）
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### 4. 自主检测（5道客观题+1道开放题）
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### 5. 疑问记录区（留空）
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【变量】
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教材版本：{人教版八年级下第十章第2节}
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学生基础：{已学过重力、匀速圆周运动}
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课时长度：{45分钟}"""
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# 修改为流式获取响应
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# 确保这是一个异步生成器函数
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async def get_lesson_plan():
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async for chunk in llm_client.get_response(prompt, stream=True):
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yield chunk
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return get_lesson_plan()
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# 测试生成导学案的函数
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async def test_generate_lesson_plan():
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print("\n===== 测试生成万有引力导学案 =====")
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try:
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# 必须await生成器函数
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lesson_plan_chunks = await generate_gravitation_lesson_plan()
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full_response = ""
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output_file = "万有引力导学案.md"
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# 使用aiofiles进行异步文件写入
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async with aiofiles.open(output_file, 'w', encoding='utf-8') as f:
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print("\n生成的导学案：")
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async for chunk in lesson_plan_chunks:
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# 实时打印chunk并刷新缓冲区
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print(chunk, end='', flush=True)
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full_response += chunk
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await f.write(chunk)
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await f.flush() # 刷新文件缓冲区
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print(f"\n导学案已保存到：{os.path.abspath(output_file)}")
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except Exception as e:
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print(f"生成导学案时发生异常: {str(e)}", file=sys.stderr)
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# 修改主函数以包含导学案生成测试
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async def main():
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try:
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# 直接生成导学案，不进行交互式测试
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await test_generate_lesson_plan()
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except KeyboardInterrupt:
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print("\n程序被用户中断")
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except Exception as e:
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print(f"测试过程中发生异常: {str(e)}", file=sys.stderr)
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finally:
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print("\n测试程序结束")
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if __name__ == '__main__':
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# 运行异步主函数
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asyncio.run(main())
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