对diagnose重构了一下
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Before Width: | Height: | Size: 928 KiB After Width: | Height: | Size: 928 KiB |
@ -1,9 +1,12 @@
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from django.contrib import admin
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# Register your models here.
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from . models import Papers
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from . models import Papers, OpenAIDiagnose
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@admin.register(Papers)
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class PaperAdmin(admin.ModelAdmin):
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list_display = ('id', 'uuid', 'status', 'created_at', 'updated_at')
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list_display = ('id', 'uuid', 'status', 'created_at', 'updated_at')
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@admin.register(OpenAIDiagnose)
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class OpenAIDiagnoseAdmin(admin.ModelAdmin):
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list_display = ('id', 'uuid', 'status', 'diagnose_type', 'created_at', 'updated_at')
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69
diagnose/db_views.py
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69
diagnose/db_views.py
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@ -0,0 +1,69 @@
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from rest_framework.views import APIView
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from rest_framework.permissions import IsAuthenticated
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from authentication.authentication import CustomTokenAuthentication
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import uuid
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import os
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from django.conf import settings
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from django.http import JsonResponse
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from rest_framework import status
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from .models import OpenAIDiagnose
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from .openai_dia import openai_diagnoser_asyna_wraper
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from django.core.exceptions import ObjectDoesNotExist
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import json
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class MyProtectedUploadDiagnose(APIView):
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authentication_classes = [CustomTokenAuthentication] # 使用自定义的 Token 认证
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permission_classes = [IsAuthenticated] # 需要用户认证才能访问
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def post(self, request):
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user = request.user
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uuid_str = str(uuid.uuid4())
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save_file_path = os.path.join(settings.BASE_DIR, 'upload_file', user.username, uuid_str)
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os.makedirs(os.path.dirname(save_file_path), exist_ok=True)
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# 获取上传的文件
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uploaded_file = request.FILES.get('file')
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if not uploaded_file:
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return JsonResponse({"error": "No file uploaded."}, status=status.HTTP_400_BAD_REQUEST)
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# 保存文件
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try:
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with open(save_file_path, 'wb+') as destination:
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for chunk in uploaded_file.chunks():
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destination.write(chunk)
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except:
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return JsonResponse({"error": "Error saving file."}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
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obj = OpenAIDiagnose.objects.create(uuid=uuid_str, user=user, status='P')
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obj.save()
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user.subject_usage_count = user.subject_usage_count - 1
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user.save()
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openai_diagnoser_asyna_wraper.delay(uuid_str, user.username, "")
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return JsonResponse({"message": "File uploaded successfully.", "uuid": uuid_str}, status=status.HTTP_200_OK)
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class MyProtectedDiagnoseCheck(APIView):
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authentication_classes = [CustomTokenAuthentication] # 使用自定义的 Token 认证
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permission_classes = [IsAuthenticated] # 需要用户认证才能访问
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def post(self, request):
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user = request.user
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# 处理 POST 请求，更新用户的联系信息
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try:
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data = json.loads(request.body)
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uuid_str = data.get("uuid")
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except json.JSONDecodeError:
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return JsonResponse({"error": "Invalid JSON format"}, status=400)
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try:
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# print(uuid_str)
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obj = OpenAIDiagnose.objects.get(uuid=uuid_str, user=user) # 只获取一个对象
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if obj.status == 'D':
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return JsonResponse({"status": "done"})
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else:
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return JsonResponse({"status": "processing"})
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except ObjectDoesNotExist:
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return JsonResponse({"error_code": "2004"}, status=404)
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@ -1,14 +1,9 @@
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# -*- coding: utf-8 -*-
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import os
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from openai import OpenAI
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import markdown2
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import pdfkit
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from django.conf import settings
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from django.http import JsonResponse, FileResponse
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from celery import shared_task
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import uuid
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from django.utils import timezone
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from rest_framework.views import APIView
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from rest_framework.permissions import IsAuthenticated
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from authentication.authentication import CustomTokenAuthentication
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@ -16,6 +11,8 @@ from django.core.exceptions import ObjectDoesNotExist
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from .models import Papers
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from ec_user.models import SchoolInfo
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import json
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from .openai_gen import paper_gen_async_wraper, convert_to_pdf
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# ============== PYdoc ===================
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# from docx import Document
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# import pypandoc
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@ -57,101 +54,6 @@ class DpArguments():
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def generate_html_paper(md_result, file_path_name):
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# 写到md中
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md_file = open(f'{file_path_name}.md', 'w', encoding='utf-8')
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md_file.write(md_result)
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md_file.close()
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# 从md中读出来再写到html中
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md_read_file = open(f'{file_path_name}.md', 'r', encoding='utf-8')
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md_text = md_read_file.read()
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md_read_file.close()
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html = markdown2.markdown(md_text)
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html_write_file = open(f'{file_path_name}.html', 'w', encoding='utf-8')
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html_write_file.write(
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"""<head>
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<meta charset="utf-8">
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<script type="text/javascript" async
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src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/MathJax.js?config=TeX-MML-AM_CHTML">
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</script>
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</head>"""+html)
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html_write_file.close()
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def convert_to_pdf(file_path_name):
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# =============== pdfkit ================
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# 从html中读出来再写到pdf中
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f = open(f'{file_path_name}.html', 'r', encoding='utf-8')
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content = f.read()
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f.close()
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config = pdfkit.configuration(wkhtmltopdf=settings.WKHTMLTOPDF_PATH)
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pdfkit.from_string(content, f'{file_path_name}.pdf', configuration=config)
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@shared_task
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def async_wraper(file_path_name, uuid_str, subject, textbook_version, start_grade, \
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start_semester, start_chapter, end_grade, end_semester, end_chapter, student):
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# client = OpenAI(
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# api_key = settings.OPAI_API_KEY,
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# base_url = settings.OPAI_BASE_URL,
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# )
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# completion = client.chat.completions.create(
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# model = "deepseek-r1-250120", # your model endpoint ID
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# messages = [
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# {"role": "system", "content": "你是教学助手"},
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# # {"role": "user",
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# # "content": f"请根据以下信息生成一份检测卷：学科为{subject}，教材版本是{textbook_version},\
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# # 检测范围从{start_grade}年级{start_semester}学期{start_chapter}章\
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# # 到{end_grade}年级{end_semester}学期{end_chapter}章，学生年级为{student.get('grade')},\
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# # 年龄为{student.get('age')}，所在学校是{student.get('school')}。\
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# # 根据答题所需时间一个半小时设置题量。题目有梯度。\
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# # 试卷题目为{subject}{textbook_version}检测卷。只生成题目，不输出答案及说明等其他内容。"
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# # },
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# {"role": "user", "content": f"""请严格按照以下要求生成一份{subject}检测卷：
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# 【试卷信息】
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# 1. 标题：**{subject}{textbook_version}综合检测卷**
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# 2. 检测范围：{start_grade}年级{start_semester}学期第{start_chapter}章 至
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# {end_grade}年级{end_semester}学期第{end_chapter}章
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# 3. 适用对象：{student.get('school')} {student.get('grade')}年级学生（年龄{student.get('age')}）
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# 【命题要求】
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# 1. 题型结构：
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# - 按难度梯度分为基础题（60%）、中档题（30%）、提高题（10%）
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# - 根据学科特点设计合理的题型（如数学可设置选择题/填空题/计算题/应用题，语文可设置阅读理解/文言文/写作等）
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# - 同一知识点不重复考查
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# 2. 题量控制：
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# - 总题数控制在18-22题（以优秀学生完成时间约75分钟为标准）
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# - 选择题不超过5题，填空题不超过6题
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# - 需包含至少1道综合应用题（理科）或材料分析题（文科）
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# 3. 内容要求：
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# - 严格按照指定章节范围命题
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# - 题目表述清晰无歧义，数字单位标注完整
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# - 禁止出现需图片辅助的题目
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# - 数学类题目需给出必要公式位置（如"（提示：可用公式____）"）
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# 【输出格式】
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# 仅输出以下内容：
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# 1. 试卷标题（加粗居中）
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# 2. 考试说明（含总分值100分、考试时长、姓名班级填写处）
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# 3. 分模块的题目内容（标注题型、分值和题号）
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# 4. "——以下为题目区域——" 分隔线
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# 禁止包含：
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# - 答案及解析
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# - 评分标准
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# - 额外说明文字
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# - markdown格式及特殊符号"""}
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# ],
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# )
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# generate_html_paper(completion.choices[0].message.content, file_path_name)
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import time
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time.sleep(30)
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generate_html_paper(""" # Test md""", file_path_name)
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try:
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obj = Papers.objects.get(uuid=uuid_str) # 只获取一个对象
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obj.status = 'D'
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obj.updated_at = timezone.now()
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obj.save()
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except ObjectDoesNotExist:
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print("warning: record not found")
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class MyProtectedGeneratePaper(APIView):
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authentication_classes = [CustomTokenAuthentication] # 使用自定义的 Token 认证
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permission_classes = [IsAuthenticated] # 需要用户认证才能访问
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@ -197,7 +99,7 @@ class MyProtectedGeneratePaper(APIView):
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obj.save()
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user.subject_usage_count = user.subject_usage_count - 1
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user.save()
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async_wraper.delay(file_path_name, uuid_str, \
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paper_gen_async_wraper.delay(file_path_name, uuid_str, \
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dp_args.subject, dp_args.textbook_version, dp_args.start_grade, dp_args.start_semester, dp_args.start_chapter, \
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dp_args.end_grade, dp_args.end_semester, dp_args.end_chapter, dp_args.student)
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return JsonResponse({"status": "success", "uuid": uuid_str})
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28
diagnose/migrations/0003_openaidiagnose.py
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28
diagnose/migrations/0003_openaidiagnose.py
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# Generated by Django 4.2.19 on 2025-02-28 15:39
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from django.conf import settings
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from django.db import migrations, models
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import django.db.models.deletion
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class Migration(migrations.Migration):
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dependencies = [
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migrations.swappable_dependency(settings.AUTH_USER_MODEL),
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('diagnose', '0002_papers_created_at_papers_updated_at'),
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]
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operations = [
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migrations.CreateModel(
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name='OpenAIDiagnose',
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fields=[
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('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
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('uuid', models.CharField(max_length=100)),
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('status', models.CharField(choices=[('C', '任务创建'), ('P', '生成中'), ('D', '已完成')], default='C', max_length=1)),
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('created_at', models.DateTimeField(auto_now_add=True, null=True)),
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('updated_at', models.DateTimeField(auto_now=True, null=True)),
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('diagnose_type', models.CharField(choices=[('M', '大模型试卷诊断'), ('S', '学校试卷诊断'), ('H', '作业诊断'), ('N', '课堂笔记诊断')], default='M', max_length=1)),
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('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
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],
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),
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]
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@ -16,4 +16,27 @@ class Papers(models.Model):
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updated_at = models.DateTimeField(auto_now=True,null=True, blank=True) # 更新时间
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def __str__(self):
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return self.user.username + '的试卷'
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return self.user.name + '的试卷'
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class OpenAIDiagnose(models.Model):
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STATUS_CHOICES = (
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('C', '任务创建'),
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('P', '生成中'),
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('D', '已完成')
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)
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DIAGNOSE_TYPE = (
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('M', '大模型试卷诊断'), # big model
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('S', '学校试卷诊断'), # school
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('H', '作业诊断'), # homework
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('N', '课堂笔记诊断') # notebook
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)
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uuid = models.CharField(max_length=100) # 一次分析唯一标识符
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# 定义一个与EcUser一对多关联的外键
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user = models.ForeignKey(EcUser, on_delete=models.CASCADE) # 当EcUser被删除时，关联的Papers也会被删除
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status = models.CharField(max_length=1, choices=STATUS_CHOICES, default='C') # 默认值设置为'C'
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created_at = models.DateTimeField(auto_now_add=True,null=True, blank=True) # 创建时间
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updated_at = models.DateTimeField(auto_now=True,null=True, blank=True) # 更新时间
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diagnose_type = models.CharField(max_length=1, choices=DIAGNOSE_TYPE, default='M') # 默认值设置为'M'
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def __str__(self):
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return self.user.name + '的诊断'
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90
diagnose/openai_dia.py
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90
diagnose/openai_dia.py
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import os
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from openai import OpenAI
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import base64
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from PIL import Image
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from celery import shared_task
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from django.conf import settings
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import markdown2
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from django.utils import timezone
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from .models import OpenAIDiagnose
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from django.core.exceptions import ObjectDoesNotExist
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def get_image_type(image_path):
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with Image.open(image_path) as img:
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return img.format # 返回图片的格式，例如 'PNG' 或 'JPEG'
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def encode_image(image_path):
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with open(image_path, "rb") as image_file:
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return base64.b64encode(image_file.read()).decode('utf-8')
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# 将图片转为Base64编码
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def generate_html_paper(md_result, file_path_name):
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# 写到md中
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md_file = open(f'{file_path_name}.md', 'w', encoding='utf-8')
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md_file.write(md_result)
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md_file.close()
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# 从md中读出来再写到html中
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md_read_file = open(f'{file_path_name}.md', 'r', encoding='utf-8')
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md_text = md_read_file.read()
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md_read_file.close()
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html = markdown2.markdown(md_text)
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html_write_file = open(f'{file_path_name}.html', 'w', encoding='utf-8')
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html_write_file.write(
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"""<head>
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<meta charset="utf-8">
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<script type="text/javascript" async
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src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/MathJax.js?config=TeX-MML-AM_CHTML">
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</script>
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</head>"""+html)
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html_write_file.close()
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@shared_task
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def openai_diagnoser_asyna_wraper(uuid_str: str, username: str, diagnose_type: str):
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client = OpenAI(
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api_key = settings.OPAI_IMG_API_KEY,
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base_url = settings.OPAI_IMG_BASE_URL
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)
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# 需要传给大模型的图片
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# image_path = "ch.jpg"
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image_path = os.path.join(settings.BASE_DIR, 'upload_file', username, uuid_str)
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base64_image = encode_image(image_path)
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image_type = get_image_type(image_path)
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image_type = image_type.lower()
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# print("===> image type:" + image_type)
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# Image input:
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response = client.chat.completions.create(
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model="doubao-1-5-vision-pro-32k-250115",
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "图中是几个题目，帮我分析一下，我是否做对了",
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},
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{
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"type": "image_url",
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"image_url": {
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# 需要注意：传入Base64编码前需要增加前缀 data:image/{图片格式};base64,{Base64编码}：
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# PNG图片："url": f"data:image/png;base64,{base64_image}"
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# JEPG图片："url": f"data:image/jpeg;base64,{base64_image}"
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# WEBP图片："url": f"data:image/webp;base64,{base64_image}"
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"url": f"data:image/{image_type};base64,{base64_image}"
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},
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},
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],
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}
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],
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)
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# print(response.choices[0].message.content)
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generate_html_paper(response.choices[0].message.content, image_path)
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try:
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obj = OpenAIDiagnose.objects.get(uuid=uuid_str) # 只获取一个对象
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obj.status = 'D'
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obj.updated_at = timezone.now()
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obj.save()
|
||||
except ObjectDoesNotExist:
|
||||
print("warning: record not found")
|
||||
116
diagnose/openai_gen.py
Normal file
116
diagnose/openai_gen.py
Normal file
@ -0,0 +1,116 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
from openai import OpenAI
|
||||
import markdown2
|
||||
import pdfkit
|
||||
from django.conf import settings
|
||||
from celery import shared_task
|
||||
from django.utils import timezone
|
||||
from django.core.exceptions import ObjectDoesNotExist
|
||||
from .models import Papers
|
||||
|
||||
# ============== PYdoc ===================
|
||||
# from docx import Document
|
||||
# import pypandoc
|
||||
# pypandoc.download_pandoc()
|
||||
|
||||
# ================ weasyprint ===========
|
||||
# 库用不了
|
||||
# from weasyprint import HTML
|
||||
# HTML(string=html).write_pdf("output.pdf")
|
||||
|
||||
|
||||
|
||||
def generate_html_paper(md_result, file_path_name):
|
||||
# 写到md中
|
||||
md_file = open(f'{file_path_name}.md', 'w', encoding='utf-8')
|
||||
md_file.write(md_result)
|
||||
md_file.close()
|
||||
|
||||
# 从md中读出来再写到html中
|
||||
md_read_file = open(f'{file_path_name}.md', 'r', encoding='utf-8')
|
||||
md_text = md_read_file.read()
|
||||
md_read_file.close()
|
||||
html = markdown2.markdown(md_text)
|
||||
html_write_file = open(f'{file_path_name}.html', 'w', encoding='utf-8')
|
||||
html_write_file.write(
|
||||
"""<head>
|
||||
<meta charset="utf-8">
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/MathJax.js?config=TeX-MML-AM_CHTML">
|
||||
</script>
|
||||
</head>"""+html)
|
||||
html_write_file.close()
|
||||
|
||||
def convert_to_pdf(file_path_name):
|
||||
# =============== pdfkit ================
|
||||
# 从html中读出来再写到pdf中
|
||||
f = open(f'{file_path_name}.html', 'r', encoding='utf-8')
|
||||
content = f.read()
|
||||
f.close()
|
||||
config = pdfkit.configuration(wkhtmltopdf=settings.WKHTMLTOPDF_PATH)
|
||||
pdfkit.from_string(content, f'{file_path_name}.pdf', configuration=config)
|
||||
|
||||
@shared_task
|
||||
def paper_gen_async_wraper(file_path_name, uuid_str, subject, textbook_version, start_grade, \
|
||||
start_semester, start_chapter, end_grade, end_semester, end_chapter, student):
|
||||
|
||||
# client = OpenAI(
|
||||
# api_key = settings.OPAI_API_KEY,
|
||||
# base_url = settings.OPAI_BASE_URL,
|
||||
# )
|
||||
# completion = client.chat.completions.create(
|
||||
# model = "deepseek-r1-250120", # your model endpoint ID
|
||||
# messages = [
|
||||
# {"role": "system", "content": "你是教学助手"},
|
||||
# # {"role": "user",
|
||||
# # "content": f"请根据以下信息生成一份检测卷：学科为{subject}，教材版本是{textbook_version},\
|
||||
# # 检测范围从{start_grade}年级{start_semester}学期{start_chapter}章\
|
||||
# # 到{end_grade}年级{end_semester}学期{end_chapter}章，学生年级为{student.get('grade')},\
|
||||
# # 年龄为{student.get('age')}，所在学校是{student.get('school')}。\
|
||||
# # 根据答题所需时间一个半小时设置题量。题目有梯度。\
|
||||
# # 试卷题目为{subject}{textbook_version}检测卷。只生成题目，不输出答案及说明等其他内容。"
|
||||
# # },
|
||||
# {"role": "user", "content": f"""请严格按照以下要求生成一份{subject}检测卷：
|
||||
# 【试卷信息】
|
||||
# 1. 标题：**{subject}{textbook_version}综合检测卷**
|
||||
# 2. 检测范围：{start_grade}年级{start_semester}学期第{start_chapter}章 至
|
||||
# {end_grade}年级{end_semester}学期第{end_chapter}章
|
||||
# 3. 适用对象：{student.get('school')} {student.get('grade')}年级学生（年龄{student.get('age')}）
|
||||
# 【命题要求】
|
||||
# 1. 题型结构：
|
||||
# - 按难度梯度分为基础题（60%）、中档题（30%）、提高题（10%）
|
||||
# - 根据学科特点设计合理的题型（如数学可设置选择题/填空题/计算题/应用题，语文可设置阅读理解/文言文/写作等）
|
||||
# - 同一知识点不重复考查
|
||||
# 2. 题量控制：
|
||||
# - 总题数控制在18-22题（以优秀学生完成时间约75分钟为标准）
|
||||
# - 选择题不超过5题，填空题不超过6题
|
||||
# - 需包含至少1道综合应用题（理科）或材料分析题（文科）
|
||||
# 3. 内容要求：
|
||||
# - 严格按照指定章节范围命题
|
||||
# - 题目表述清晰无歧义，数字单位标注完整
|
||||
# - 禁止出现需图片辅助的题目
|
||||
# - 数学类题目需给出必要公式位置（如"（提示：可用公式____）"）
|
||||
# 【输出格式】
|
||||
# 仅输出以下内容：
|
||||
# 1. 试卷标题（加粗居中）
|
||||
# 2. 考试说明（含总分值100分、考试时长、姓名班级填写处）
|
||||
# 3. 分模块的题目内容（标注题型、分值和题号）
|
||||
# 4. "——以下为题目区域——" 分隔线
|
||||
# 禁止包含：
|
||||
# - 答案及解析
|
||||
# - 评分标准
|
||||
# - 额外说明文字
|
||||
# - markdown格式及特殊符号"""}
|
||||
# ],
|
||||
# )
|
||||
# generate_html_paper(completion.choices[0].message.content, file_path_name)
|
||||
import time
|
||||
time.sleep(30)
|
||||
generate_html_paper(""" # Test md""", file_path_name)
|
||||
try:
|
||||
obj = Papers.objects.get(uuid=uuid_str) # 只获取一个对象
|
||||
obj.status = 'D'
|
||||
obj.updated_at = timezone.now()
|
||||
obj.save()
|
||||
except ObjectDoesNotExist:
|
||||
print("warning: record not found")
|
||||
@ -1,43 +0,0 @@
|
||||
import os
|
||||
from openai import OpenAI
|
||||
import base64
|
||||
|
||||
client = OpenAI(
|
||||
api_key = 'd04d386a-7c67-4927-8251-171a236583a6',
|
||||
base_url = "https://ark.cn-beijing.volces.com/api/v3",
|
||||
)
|
||||
def encode_image(image_path):
|
||||
with open(image_path, "rb") as image_file:
|
||||
return base64.b64encode(image_file.read()).decode('utf-8')
|
||||
# 将图片转为Base64编码
|
||||
|
||||
# 需要传给大模型的图片
|
||||
image_path = "ch.jpg"
|
||||
base64_image = encode_image(image_path)
|
||||
# Image input:
|
||||
response = client.chat.completions.create(
|
||||
model="doubao-1-5-vision-pro-32k-250115",
|
||||
messages=[
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": "图中是几个语文题目，帮我分析一下，我是否做对了",
|
||||
},
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {
|
||||
# 需要注意：传入Base64编码前需要增加前缀 data:image/{图片格式};base64,{Base64编码}：
|
||||
# PNG图片："url": f"data:image/png;base64,{base64_image}"
|
||||
# JEPG图片："url": f"data:image/jpeg;base64,{base64_image}"
|
||||
# WEBP图片："url": f"data:image/webp;base64,{base64_image}"
|
||||
"url": f"data:image/jpg;base64,{base64_image}"
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
],
|
||||
)
|
||||
|
||||
print(response.choices[0].message.content)
|
||||
@ -1,36 +0,0 @@
|
||||
|
||||
|
||||
from rest_framework.views import APIView
|
||||
from rest_framework.permissions import IsAuthenticated
|
||||
from authentication.authentication import CustomTokenAuthentication
|
||||
import uuid
|
||||
import os
|
||||
from django.conf import settings
|
||||
from django.http import JsonResponse
|
||||
from rest_framework import status
|
||||
|
||||
class MyProtectedUploadfile(APIView):
|
||||
authentication_classes = [CustomTokenAuthentication] # 使用自定义的 Token 认证
|
||||
permission_classes = [IsAuthenticated] # 需要用户认证才能访问
|
||||
|
||||
def post(self, request):
|
||||
user = request.user
|
||||
uuid_str = str(uuid.uuid4())
|
||||
save_file_path = os.path.join(settings.BASE_DIR, 'upload_file', user.username, uuid_str)
|
||||
|
||||
os.makedirs(os.path.dirname(save_file_path), exist_ok=True)
|
||||
|
||||
# 获取上传的文件
|
||||
uploaded_file = request.FILES.get('file')
|
||||
if not uploaded_file:
|
||||
return JsonResponse({"error": "No file uploaded."}, status=status.HTTP_400_BAD_REQUEST)
|
||||
|
||||
# 保存文件
|
||||
try:
|
||||
with open(save_file_path, 'wb+') as destination:
|
||||
for chunk in uploaded_file.chunks():
|
||||
destination.write(chunk)
|
||||
except:
|
||||
return JsonResponse({"error": "Error saving file."}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)
|
||||
|
||||
return JsonResponse({"message": "File uploaded successfully."}, status=status.HTTP_200_OK)
|
||||
@ -1,11 +1,12 @@
|
||||
|
||||
from django.urls import path
|
||||
from .dp_views import MyProtectedGeneratePaper, MyProtectedGenerateCheck, MyProtectedDownloadPaper
|
||||
from .upload_views import MyProtectedUploadfile
|
||||
from .db_views import MyProtectedUploadDiagnose, MyProtectedDiagnoseCheck
|
||||
urlpatterns = [
|
||||
path('', MyProtectedGeneratePaper.as_view(), name='api_generate_paper'),
|
||||
path('check/', MyProtectedGenerateCheck.as_view(), name='api_generate_check'),
|
||||
path('download/', MyProtectedDownloadPaper.as_view(), name='api_download_paper'),
|
||||
|
||||
path('upload/', MyProtectedUploadfile.as_view(), name='api_upload_file')
|
||||
path('upload/', MyProtectedUploadDiagnose.as_view(), name='api_upload_file'),
|
||||
path('upload_diagnose_check/', MyProtectedDiagnoseCheck.as_view(), name='api_diagnose_file')
|
||||
]
|
||||
|
||||
@ -172,6 +172,9 @@ ERROR_CODE_MAP = {
|
||||
OPAI_API_KEY = 'e119bd6c-a22a-404e-a002-6d72a2cea65d'
|
||||
OPAI_BASE_URL = 'https://ark.cn-beijing.volces.com/api/v3'
|
||||
|
||||
OPAI_IMG_BASE_URL = 'https://ark.cn-beijing.volces.com/api/v3'
|
||||
OPAI_IMG_API_KEY = 'd04d386a-7c67-4927-8251-171a236583a6'
|
||||
|
||||
WKHTMLTOPDF_PATH = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
|
||||
|
||||
# settings.py
|
||||
|
||||
Loading…
Reference in New Issue
Block a user