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import asyncio
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import socket
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import time
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import uvicorn
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from fastapi import FastAPI, Body
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import StreamingResponse, PlainTextResponse
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from openai import OpenAI
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from AiService.MarkdownToJsonConverter import MarkdownToJsonConverter
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# 阿里云中用来调用 deepseek v3 的密钥
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MODEL_API_KEY = "sk-01d13a39e09844038322108ecdbd1bbc"
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MODEL_NAME = "qwen-plus"
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# 初始化 OpenAI 客户端
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client = OpenAI(
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api_key=MODEL_API_KEY,
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base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
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)
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def convertMarkdownToJson(markdown_content: str, language: str):
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# 创建转换器实例
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converter = MarkdownToJsonConverter(client, language)
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# 转换 Markdown 为 JSON
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for item in converter.convert_markdown_to_json(markdown_content, language): # 使用普通 for 循环
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yield f"{item}\n" # 每行数据后添加换行符
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# 添加结束标记
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yield '{"type": "end" }\n' # 结束标记后也添加换行符
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# 获取本机所有 IPv4 地址
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def get_local_ips():
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ips = []
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hostname = socket.gethostname()
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try:
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# 获取所有 IP 地址
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addrs = socket.getaddrinfo(hostname, None, family=socket.AF_INET) # 只获取 IPv4 地址
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for addr in addrs:
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ip = addr[4][0]
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if ip not in ips:
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ips.append(ip)
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except Exception as e:
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print(f"获取 IP 地址失败: {e}")
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return ips
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# 流式生成数据的函数
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async def generate_stream_markdown(course_name: str, language: str):
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"""
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流式生成 Markdown 数据，并在控制台输出完整的 Markdown 内容
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"""
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prompt = ''
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if language == 'cn':
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prompt = '请使用中文回答'
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elif language == 'en':
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prompt = 'Please answer in English。'
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# 调用阿里云 API，启用流式响应
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stream = client.chat.completions.create(
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model=MODEL_NAME,
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messages=[
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{'role': 'system', 'content': '你是一个教学经验丰富的基础教育教师'},
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{'role': 'user',
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'content': prompt + ',帮我设计一下' + course_name + '的课件提纲，用markdown格式返回。强调1、标签只能返回 #,##,###,-,其它标签一率不可以返回，这个非常重要！2、不要返回 ```markdown 或者 ``` 这样的内容！ 3、每部分都有生成完整的一、二、三级内容，不能省略。'}
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],
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stream=True, # 启用流式响应
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timeout=6000,
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)
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# 初始化完整的 Markdown 内容
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full_markdown = ""
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# 逐字返回数据
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for chunk in stream:
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if chunk.choices[0].delta.content:
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chunk_content = chunk.choices[0].delta.content
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full_markdown += chunk_content # 拼接 Markdown 内容
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for char in chunk_content:
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yield char.encode("utf-8")
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await asyncio.sleep(0.05) # 控制逐字输出的速度
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# 在控制台输出完整的 Markdown 内容
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print("\n完整的 Markdown 内容：")
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print(full_markdown)
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app = FastAPI()
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# 添加 CORS 中间件
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# 根路由，返回提示信息
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@app.get("/")
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def root():
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return PlainTextResponse("Hello ApiStream")
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@app.post("/api/tools/aippt_outline") # 仅支持 POST 方法
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async def aippt_outline(
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course_name: str = Body(..., embed=True, description="课程名称"), # 从请求体中获取 course_name
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language: str = Body(..., embed=True, description="语言"),
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):
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# 返回流式响应
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return StreamingResponse(
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generate_stream_markdown(course_name, language),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"Access-Control-Allow-Origin": "*",
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"X-Accel-Buffering": "no"
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}
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)
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@app.post("/api/tools/aippt") # 修改为 POST 方法
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def aippt(content: str = Body(..., embed=True, description="Markdown 内容"),
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language: str = Body(..., embed=True, description="语言")): # 使用 Body 接收请求体参数
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return StreamingResponse(
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convertMarkdownToJson(content, language), # 传入 content
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media_type="text/plain", # 使用 text/plain 格式
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"Access-Control-Allow-Origin": "*",
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"X-Accel-Buffering": "no",
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"Content-Type": "text/plain; charset=utf-8" # 明确设置 Content-Type
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}
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)
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# 运行应用
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if __name__ == "__main__":
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# 获取本机所有 IPv4 地址
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ips = get_local_ips()
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if not ips:
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print("无法获取本机 IP 地址，使用默认地址 127.0.0.1")
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ips = ["127.0.0.1"]
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# 打印所有 IP 地址
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print("服务将在以下 IP 地址上运行：")
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for ip in ips:
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print(f"http://{ip}:5173")
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# 启动 FastAPI 应用，绑定到所有 IP 地址
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uvicorn.run(app, host="0.0.0.0", port=5173)
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