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@@ -1,20 +1,31 @@
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from fastapi import APIRouter, Depends, Request
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from sqlalchemy.orm import Session
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-from pydantic import BaseModel
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+from pydantic import BaseModel, Field
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from typing import Optional
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from database import get_db
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from models.chat import AIMessage
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from services.qwen_service import qwen_service
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-import time
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router = APIRouter()
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+class QuestionTypeItem(BaseModel):
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+ questionType: str = ""
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+ name: str = ""
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+ count: int = 0
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+ questionCount: int = 0
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+ scorePerQuestion: int = 0
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+ romanNumeral: str = ""
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+
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+
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class BuildPromptRequest(BaseModel):
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- exam_type: str
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- topic: str
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- difficulty: str
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- question_count: int
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+ mode: str = ""
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+ client: str = ""
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+ projectType: str = ""
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+ examTitle: str = ""
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+ totalScore: int = 0
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+ questionTypes: list[QuestionTypeItem] = Field(default_factory=list)
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+ pptContent: str = ""
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@router.post("/exam/build_prompt")
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@@ -23,12 +34,58 @@ async def build_exam_prompt(
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data: BuildPromptRequest,
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db: Session = Depends(get_db)
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):
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- """生成考试提示词 - 对齐Go版本函数名"""
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+ """根据前端考试工坊参数生成提示词"""
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user = request.state.user
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if not user:
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return {"statusCode": 401, "msg": "未授权"}
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-
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- prompt = f"""请生成{data.question_count}道关于{data.topic}的{data.exam_type}，难度为{data.difficulty}。"""
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+
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+ question_desc = []
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+ total_count = 0
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+ for item in data.questionTypes:
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+ count = item.count or item.questionCount or 0
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+ score = item.scorePerQuestion or 0
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+ qtype = item.questionType or item.name or "未命名题型"
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+ total_count += count
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+ question_desc.append(f"{qtype}{count}道，每道{score}分")
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+
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+ question_text = "；".join(question_desc) if question_desc else "题型未提供"
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+ question_schema_lines = []
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+ for item in data.questionTypes:
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+ count = item.count or item.questionCount or 0
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+ score = item.scorePerQuestion or 0
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+ qtype = item.questionType or item.name or "未命名题型"
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+ if count <= 0:
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+ continue
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+ question_schema_lines.append(f"- {qtype}: {count}道，每道{score}分")
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+
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+ question_schema = "\n".join(question_schema_lines) if question_schema_lines else "- 未提供有效题型"
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+
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+ prompt = (
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+ "请根据以下要求直接生成一份完整试卷，并严格返回纯 JSON，不要输出 markdown 代码块、解释说明或额外文字。\n"
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+ f"生成模式：{data.mode or '未指定'}\n"
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+ f"客户端：{data.client or '未指定'}\n"
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+ f"项目类型：{data.projectType or '未指定'}\n"
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+ f"考试标题：{data.examTitle or '未命名考试'}\n"
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+ f"总分：{data.totalScore or 0}\n"
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+ f"总题量：{total_count}\n"
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+ f"题型要求：{question_text}\n"
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+ f"课件内容：{data.pptContent or '无'}\n"
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+ "请结合课件内容、工程类型和题型要求，生成有具体内容、具体选项、具体答案、具体解析的试卷。\n"
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+ "禁止输出“选项A”“题目1”这类占位内容，所有题目必须是可直接展示和作答的真实内容。\n"
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+ "JSON 输出结构必须符合以下格式：\n"
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+ "{\n"
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+ ' "title": "试卷标题",\n'
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+ ' "totalScore": 100,\n'
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+ ' "totalQuestions": 10,\n'
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+ ' "singleChoice": {"scorePerQuestion": 2, "totalScore": 20, "count": 10, "questions": [{"text": "题目内容", "options": [{"key": "A", "text": "具体选项内容"}, {"key": "B", "text": "具体选项内容"}, {"key": "C", "text": "具体选项内容"}, {"key": "D", "text": "具体选项内容"}], "answer": "A", "analysis": "解析内容"}]},\n'
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+ ' "judge": {"scorePerQuestion": 2, "totalScore": 0, "count": 0, "questions": [{"text": "题目内容", "answer": "正确", "analysis": "解析内容"}]},\n'
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+ ' "multiple": {"scorePerQuestion": 3, "totalScore": 0, "count": 0, "questions": [{"text": "题目内容", "options": [{"key": "A", "text": "具体选项内容"}, {"key": "B", "text": "具体选项内容"}, {"key": "C", "text": "具体选项内容"}, {"key": "D", "text": "具体选项内容"}], "answers": ["A", "C"], "analysis": "解析内容"}]},\n'
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+ ' "short": {"scorePerQuestion": 10, "totalScore": 0, "count": 0, "questions": [{"text": "题目内容", "outline": {"keyFactors": "答题要点", "measures": "参考措施"}}]}\n'
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+ "}\n"
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+ "请按下面的题型配置生成对应数量的题目，没有的题型 count 返回 0、questions 返回空数组：\n"
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+ f"{question_schema}"
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+ )
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+
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return {
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"statusCode": 200,
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"msg": "success",
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@@ -52,7 +109,7 @@ async def build_single_question_prompt(
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user = request.state.user
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if not user:
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return {"statusCode": 401, "msg": "未授权"}
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-
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+
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prompt = f"""请生成1道关于{data.topic}的{data.question_type}，难度为{data.difficulty}。"""
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return {
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"statusCode": 200,
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@@ -76,23 +133,24 @@ async def re_modify_question(
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user = request.state.user
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if not user:
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return {"statusCode": 401, "msg": "未授权"}
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-
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+
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# 修改ai_message表中type='ai'的content
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result = db.query(AIMessage).filter(
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AIMessage.ai_conversation_id == data.ai_conversation_id,
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AIMessage.type == 'ai'
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).update({"content": data.content})
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-
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+
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if result == 0:
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return {"statusCode": 404, "msg": "消息不存在"}
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-
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+
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db.commit()
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return {"statusCode": 200, "msg": "success"}
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class ReproduceSingleQuestionRequest(BaseModel):
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- ai_conversation_id: int
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- regenerate_reason: str
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+ message: str = ""
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+ ai_conversation_id: Optional[int] = None
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+ regenerate_reason: str = ""
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@router.post("/re_produce_single_question")
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@@ -105,22 +163,41 @@ async def re_produce_single_question(
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user = request.state.user
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if not user:
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return {"statusCode": 401, "msg": "未授权"}
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-
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- # 获取原消息
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- message = db.query(AIMessage).filter(
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- AIMessage.ai_conversation_id == data.ai_conversation_id,
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- AIMessage.type == 'ai'
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- ).first()
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-
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- if not message:
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- return {"statusCode": 404, "msg": "消息不存在"}
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-
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- new_question = f"重新生成的题目（原因：{data.regenerate_reason}）"
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+
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+ prompt = (data.message or "").strip()
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+
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+ # 兼容旧版调用：未传 message 时，尝试根据会话和重生成原因构造提示词。
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+ if not prompt and data.ai_conversation_id:
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+ message = db.query(AIMessage).filter(
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+ AIMessage.ai_conversation_id == data.ai_conversation_id,
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+ AIMessage.type == 'ai'
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+ ).first()
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+
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+ if not message:
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+ return {"statusCode": 404, "msg": "消息不存在"}
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+
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+ prompt = (message.content or "").strip()
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+ if data.regenerate_reason:
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+ prompt = f"{prompt}\n\n请根据以下要求重新生成：{data.regenerate_reason}"
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+
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+ if not prompt:
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+ return {"statusCode": 400, "msg": "缺少生成内容"}
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+
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+ try:
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+ new_question = await qwen_service.chat([
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+ {"role": "user", "content": prompt}
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+ ])
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+ except Exception as e:
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+ return {"statusCode": 500, "msg": f"AI生成失败: {str(e)}"}
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+
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return {
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"statusCode": 200,
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"msg": "success",
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"data": {
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"ai_conversation_id": data.ai_conversation_id,
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- "new_question": new_question
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+ "new_question": new_question,
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+ "reply": new_question,
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+ "content": new_question,
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+ "message": new_question
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}
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}
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