Simon
ead5f83bee
dependencies.py 拆分为 dependencies/ 包; 新增 vision/ragflow_ingestion/neo4j 客户端与 h5_ai_task; alembic 045 图置信度迁移; 响应契约统一收尾。
217 lines
7.6 KiB
Python
217 lines
7.6 KiB
Python
# =============================================================================
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# 企微IT智能服务台 — RAGFlow 文档摄入 API（Tier1 新增 / P1-5 / 通道 C）
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# =============================================================================
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# 说明：RAGFlow 文档摄入接口，训练师上传非标准格式文档，
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# 经 RAGFlow ETL 整理/结构化后生成 KnowledgeSuggestion 进审批队列。
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#
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# 1. POST /api/ragflow/ingest — 上传文档触发 RAGFlow 处理
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# 2. GET /api/ragflow/tasks/{task_id} — 查询处理任务状态
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#
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# P1-5 硬约束：
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# - 触发方式：训练师手动上传（非定时扫描）
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# - 支持格式：.docx/.pdf/.txt/.png/.jpg
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# - source_type=document_ragflow, audience=engineer_workguide
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# - 产出走 D7 审批流
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# =============================================================================
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import logging
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import uuid
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from typing import Optional
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from fastapi import APIRouter, Depends, File, Form, Query, UploadFile
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.database import get_db
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from app.dependencies import get_current_user, require_admin, UserInfo
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from app.models.knowledge_suggestion import KnowledgeSuggestion
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from app.schemas.enums import (
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AudienceEnum,
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GraphSyncStatusEnum,
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SourceTypeEnum,
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SuggestionStatusEnum,
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)
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from app.services.ragflow_ingestion_service import RagflowIngestionService
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logger = logging.getLogger(__name__)
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router = APIRouter()
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# 支持的文件格式
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ALLOWED_EXTENSIONS = {".docx", ".pdf", ".txt", ".png", ".jpg", ".jpeg"}
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ALLOWED_MIME_TYPES = {
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"application/vnd.openxmlformats-officedocument.wordprocessingml.document", # .docx
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"application/pdf", # .pdf
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"text/plain", # .txt
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"image/png", # .png
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"image/jpeg", # .jpg/.jpeg
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}
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# 文件大小上限（20MB）
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MAX_FILE_SIZE = 20 * 1024 * 1024
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# 内存中的任务状态缓存（生产环境应迁移到 Redis）
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_task_cache: dict = {}
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# -----------------------------------------------------------------------------
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# 上传文档触发 RAGFlow 处理（Tier1 新增）
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# -----------------------------------------------------------------------------
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# POST /api/ragflow/ingest
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@router.post("/ingest")
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@require_admin
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async def ingest_document(
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file: UploadFile = File(..., description="文档文件（.docx/.pdf/.txt/.png/.jpg）"),
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category_hint: str = Form(
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default="其他",
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description="分类提示（可选，帮助RAGFlow归类）：硬件/软件/网络/安全/账号/其他",
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),
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current_user: UserInfo = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""上传非标准格式文档到 RAGFlow 进行 ETL 处理。
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训练师上传文档后，RAGFlow 自动整理/筛选/结构化内容，
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生成 KnowledgeSuggestion 提案进入 D7 审批队列。
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**请求格式**: multipart/form-data
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**字段说明**:
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- **file**: 文档文件（必填，支持 .docx/.pdf/.txt/.png/.jpg）
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- **category_hint**: 分类提示（可选，默认"其他"）
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**文件大小限制**: 最大 20MB
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**处理时间**: 最长等待 5 分钟，超时返回 pending 状态
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**需要管理员权限。**
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"""
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# 校验文件扩展名
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file_name = file.filename or "unknown"
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ext = "." + file_name.rsplit(".", 1)[-1].lower() if "." in file_name else ""
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if ext not in ALLOWED_EXTENSIONS:
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return {
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"code": 400,
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"message": f"不支持的文件格式: {ext}，仅支持 {', '.join(ALLOWED_EXTENSIONS)}",
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"data": None,
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}
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# 校验 MIME 类型（如可获取）
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if file.content_type and file.content_type not in ALLOWED_MIME_TYPES:
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logger.warning(
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f"文件 MIME 类型不在白名单中: {file.content_type}，仍允许上传"
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)
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# 读取文件内容
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file_data = await file.read()
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# 校验文件大小
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if len(file_data) > MAX_FILE_SIZE:
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return {
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"code": 400,
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"message": f"文件过大（{len(file_data) / 1024 / 1024:.1f}MB），最大支持 20MB",
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"data": None,
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}
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if len(file_data) == 0:
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return {
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"code": 400,
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"message": "文件内容为空",
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"data": None,
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}
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# 调用 RAGFlow Ingestion 服务
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service = RagflowIngestionService()
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logger.info(
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f"管理员 {current_user.name} 上传文档到 RAGFlow: "
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f"file_name={file_name}, category_hint={category_hint}, size={len(file_data)}"
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)
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result = await service.upload_and_process(file_data, file_name, category_hint)
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# 将生成的 suggestions 写入数据库（pending 状态）
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saved_suggestions = []
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if result.get("suggestions"):
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for sug_data in result["suggestions"]:
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suggestion = KnowledgeSuggestion(
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suggestion_type=sug_data.get("suggestion_type", "new_faq"),
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status=SuggestionStatusEnum.pending.value,
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title=sug_data.get("title", ""),
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content=sug_data.get("content", ""),
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category=sug_data.get("category", category_hint),
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tags=sug_data.get("tags", []),
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source_type=SourceTypeEnum.document_ragflow.value,
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source_data=sug_data.get("source_data", []),
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reason=sug_data.get("reason", ""),
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confidence=sug_data.get("confidence", 0.85),
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audience=AudienceEnum.engineer_workguide.value, # 通道 C 默认
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issue=sug_data.get("issue", ""),
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action=sug_data.get("action", ""),
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relation_type=sug_data.get("relation_type", "LEADS_TO"),
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parent_issue=sug_data.get("parent_issue", ""),
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graph_meta=sug_data.get("graph_meta", {}),
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graph_sync_status=GraphSyncStatusEnum.pending.value,
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source_failed=sug_data.get("source_failed", False),
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)
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db.add(suggestion)
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saved_suggestions.append({
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"title": suggestion.title,
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"category": suggestion.category,
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"confidence": suggestion.confidence,
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})
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await db.commit()
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logger.info(f"RAGFlow 生成 {len(saved_suggestions)} 条 KnowledgeSuggestion 待审批")
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# 缓存任务状态
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task_id = result["task_id"]
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_task_cache[task_id] = {
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"task_id": task_id,
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"status": result["status"],
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"file_name": file_name,
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"created_at": __import__("datetime").datetime.now().isoformat(),
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"suggestions_count": len(saved_suggestions),
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}
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return {
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"code": 0,
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"message": "文档已提交 RAGFlow 处理",
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"data": {
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"task_id": task_id,
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"status": result["status"],
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"file_name": file_name,
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"suggestions_count": len(saved_suggestions),
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"suggestions": saved_suggestions,
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},
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}
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# -----------------------------------------------------------------------------
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# 查询处理任务状态（Tier1 新增）
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# -----------------------------------------------------------------------------
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# GET /api/ragflow/tasks/{task_id}
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@router.get("/tasks/{task_id}")
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@require_admin
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async def get_ingestion_task_status(
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task_id: str,
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current_user: UserInfo = Depends(get_current_user),
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):
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"""查询 RAGFlow 文档处理任务状态。
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- **task_id**: 任务ID（来自 ingest 接口返回值）
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**需要管理员权限。**
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"""
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task = _task_cache.get(task_id)
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if not task:
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return {
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"code": 404,
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"message": "任务不存在或已过期",
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"data": None,
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}
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return {
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"code": 0,
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"message": "success",
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"data": task,
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}
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