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wecom_it_smart_desk/backend/app/api/byod.py
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# =============================================================================
# IT智能服务台 — 自备电脑补贴(BYOD)资格查询 API
# =============================================================================
# 说明:提供自备电脑补贴资格的意图检测和资格检查功能
# - 意图检测:关键词预过滤 → Dify → 关键词兜底(复用审批系统三级模式)
# - 资格检查:通过企微通讯录API获取员工岗位 → 与资格清单匹配 → 返回结果
# - 岗位匹配支持精确匹配和模糊匹配(如"高级前端开发岗"匹配"前端开发岗"
# =============================================================================
import json
import logging
from typing import Optional
import httpx
from fastapi import APIRouter, Depends
from pydantic import BaseModel
import redis.asyncio as aioredis
from app.config import settings
from app.services.wecom_service import WecomService
from app.utils.response import success_response
logger = logging.getLogger(__name__)
router = APIRouter()
# Redis客户端(依赖注入)
async def get_redis() -> aioredis.Redis:
"""获取Redis客户端依赖"""
from app.main import redis_client
return redis_client
# =============================================================================
# BYOD 资格岗位清单(静态配置 — 13个岗位,4大类)
# 注:需求文档标注14个岗位,但实际清单列出13个岗位,以清单为准
# =============================================================================
# 数据来源:data/byod_eligible_positions.json
# 结构:序列 → 类别 → 岗位列表
BYOD_ELIGIBLE_POSITIONS: dict[str, dict[str, list[str]]] = {
"技术序列": {
"开发类": [
"算法岗",
"前端开发岗",
"后端开发岗",
"客户端开发岗",
"运维开发岗",
"移动端开发岗",
],
"数据类": [
"数据分析岗",
"大数据开发岗",
],
"测试类": [
"测试开发岗",
"业务测试岗",
],
},
"产品序列": {
"产品策划与设计类": [
"创意设计岗",
"用户体验设计岗",
"产品经理",
],
},
}
# =============================================================================
# 岗位模糊匹配关键词
# =============================================================================
# 从每个资格岗位提取核心关键词,用于模糊匹配。
# 企微通讯录返回的 position 可能包含额外描述(如"高级前端开发岗"),
# 只要 position 包含核心关键词即视为匹配。
# 关键词按长度降序排列,优先匹配更精确的关键词,避免误匹配。
# 例:"运维开发岗" 的关键词为 ["运维开发", "运维"]
# 先匹配"运维开发"(精确),不中再匹配"运维"(宽泛)。
BYOD_POSITION_MATCH_KEYWORDS: dict[str, list[str]] = {
"算法岗": ["算法"],
"前端开发岗": ["前端开发", "前端"],
"后端开发岗": ["后端开发", "后端"],
"客户端开发岗": ["客户端开发", "客户端"],
"运维开发岗": ["运维开发", "运维"],
"移动端开发岗": ["移动端开发", "移动端", "移动开发"],
"数据分析岗": ["数据分析"],
"大数据开发岗": ["大数据开发", "大数据"],
"测试开发岗": ["测试开发"],
"业务测试岗": ["业务测试"],
"创意设计岗": ["创意设计"],
"用户体验设计岗": ["用户体验设计", "用户体验", "UX设计", "UE设计", "交互设计"],
"产品经理": ["产品经理"],
}
# =============================================================================
# BYOD 预过滤关键词
# =============================================================================
# 用于快速过滤非 BYOD 相关消息,避免每条消息都调 Dify。
BYOD_PREFILTER_KEYWORDS: list[str] = [
"自备电脑",
"电脑补贴",
"BYOD",
"byod",
"自带电脑",
"个人电脑补贴",
"补贴资格",
"电脑补贴资格",
"自备电脑补贴",
"自带设备",
]
# =============================================================================
# 申请链接 & 注意事项
# =============================================================================
BYOD_APPLICATION_URL: str = (
"https://ehr.servyou.com.cn/HRAPP/FlowMobile/InitiateIns.aspx"
"?flowid=7747&desc=自备电脑使用申请"
)
BYOD_NOTES: list[str] = [
"补贴按月发放,需提供个人电脑的购买凭证",
"领取补贴期间不得再领用公司电脑",
"如已领用公司电脑,需先退还后方可申请补贴",
"补贴金额和发放规则以公司最新政策为准",
"申请提交后由部门审批,审批进度可在eHR系统查看",
]
# 登记注意事项(非补贴岗位 — 仅登记无补贴)
BYOD_REGISTER_NOTES: list[str] = [
"自备电脑登记不享受电脑补贴",
"登记后仍需遵守公司信息安全管理规定",
"如已领用公司电脑,需先退还后方可登记自备电脑",
"自备电脑需满足公司办公基本配置要求",
"申请提交后由部门审批,审批进度可在eHR系统查看",
]
# =============================================================================
# Schema 定义
# =============================================================================
class ByodEligibilityRequest(BaseModel):
"""BYOD 意图检测请求
Attributes:
text: 用户消息文本
employee_id: 员工ID(可选,传给 Dify 作为用户标识)
"""
text: str
employee_id: Optional[str] = None
class ByodCheckEligibilityRequest(BaseModel):
"""BYOD 资格检查请求
Attributes:
employee_id: 员工的企微 UserID
"""
employee_id: str
class ByodEligibilityResponse(BaseModel):
"""BYOD 资格查询响应
Attributes:
is_byod_intent: 是否为自备电脑补贴意图
eligible: 是否有资格申请补贴(语义同 has_subsidy,保留兼容)
has_subsidy: 是否有补贴(True=有补贴, False=仅登记无补贴)
position: 员工岗位(企微通讯录返回的 position 字段)
matched_category: 匹配到的资格类别(如"技术序列 - 开发类"),未匹配时为空
application_url: 申请/登记链接(所有岗位都返回,获取失败除外)
notes: 注意事项列表(有补贴=补贴须知, 无补贴=登记须知)
reason: 提示信息(无补贴时说明"可登记但无补贴"
source: 结果来源 — dify(Dify识别) / keyword_prefilter(关键词预过滤未命中) / fallback(降级兜底) / wecom(企微通讯录查询)
"""
is_byod_intent: bool
eligible: bool
has_subsidy: bool = False
position: str = ""
matched_category: str = ""
application_url: str = ""
notes: list[str] = []
reason: str = ""
source: str
# =============================================================================
# 岗位匹配逻辑
# =============================================================================
def _match_position(position: str) -> tuple[bool, str, str]:
"""将员工岗位与资格清单进行匹配。
匹配策略(按优先级):
1. 精确匹配 — 员工岗位与资格岗位完全一致
2. 包含匹配 — 资格岗位是员工岗位的子串(如"前端开发岗""高级前端开发岗"中)
3. 关键词匹配 — 员工岗位包含资格岗位的核心关键词(如"前端""高级前端开发岗"中)
Args:
position: 企微通讯录返回的员工岗位字符串
Returns:
tuple: (是否匹配, 匹配到的资格岗位名称, 匹配到的类别)
类别格式为"序列 - 类别"(如"技术序列 - 开发类"),未匹配时为空字符串
"""
if not position:
return False, "", ""
position_stripped = position.strip()
for sequence, categories in BYOD_ELIGIBLE_POSITIONS.items():
for category, positions in categories.items():
for eligible_pos in positions:
# 1. 精确匹配
if position_stripped == eligible_pos:
return True, eligible_pos, f"{sequence} - {category}"
# 2. 包含匹配(资格岗位是员工岗位的子串)
if eligible_pos in position_stripped:
return True, eligible_pos, f"{sequence} - {category}"
# 3. 核心关键词匹配
keywords = BYOD_POSITION_MATCH_KEYWORDS.get(eligible_pos, [])
for keyword in keywords:
if keyword in position_stripped:
return True, eligible_pos, f"{sequence} - {category}"
return False, "", ""
# =============================================================================
# Dify 意图识别(复用审批意图识别 Dify 应用)
# =============================================================================
# 说明:BYOD 意图识别复用审批系统的 Dify 应用(同一个 approval_dify_base_url /
# approval_dify_api_key),Dify 后台的 System Prompt 已更新为同时支持
# 审批意图和 BYOD 意图识别。Dify 返回的 JSON 中包含 is_byod_intent 字段。
async def _call_dify_byod_intent(text: str, employee_id: str = "") -> dict:
"""调用 Dify 意图识别应用,检测 BYOD 意图。
复用审批意图识别的 Dify 应用(approval_dify_base_url / approval_dify_api_key),
Dify 的 System Prompt 已更新为同时返回 is_byod_intent 字段。
Dify 原生 API 调用方式与 approval.py 中的 _call_dify_approval_intent 一致:
POST {base_url}/v1/chat-messagesblocking 模式。
Args:
text: 用户消息文本
employee_id: 员工 ID(可选,传给 Dify 的 user 字段)
Returns:
dict: {
"is_byod_intent": bool,
"confidence": float,
}
Raises:
Exception: Dify 调用失败或响应解析失败
"""
base_url = settings.approval_dify_base_url
api_key = settings.approval_dify_api_key
timeout = settings.approval_dify_timeout
if not base_url or not api_key:
raise ValueError(
"Dify 意图识别应用未配置(APPROVAL_DIFY_BASE_URL / APPROVAL_DIFY_API_KEY"
)
# 构建请求 URLbase_url + /v1/chat-messagesDify 原生 API
url = f"{base_url.rstrip('/')}/v1/chat-messages"
body = {
"inputs": {},
"query": text,
"response_mode": "blocking",
"user": employee_id or "byod_detection",
}
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
}
async with httpx.AsyncClient(timeout=httpx.Timeout(timeout)) as client:
response = await client.post(url, json=body, headers=headers)
response.raise_for_status()
data = response.json()
# 解析 Dify 原生响应:answer 字段包含 AI 返回的文本(JSON 字符串)
answer = data.get("answer", "")
parsed = json.loads(answer)
return {
"is_byod_intent": bool(parsed.get("is_byod_intent", False)),
"confidence": float(parsed.get("confidence", 0.0)),
}
# =============================================================================
# 关键词预过滤 & 降级兜底
# =============================================================================
def _byod_keyword_prefilter(text: str) -> bool:
"""BYOD 关键词预过滤:检查文本是否包含自备电脑补贴相关关键词。
只要命中 BYOD_PREFILTER_KEYWORDS 中的任意一个关键词即返回 True,
未命中返回 False。用于避免每条消息都调 Dify。
Args:
text: 用户消息文本
Returns:
bool: 是否包含 BYOD 相关关键词
"""
if not text:
return False
lower_text = text.lower()
return any(kw.lower() in lower_text for kw in BYOD_PREFILTER_KEYWORDS)
def _byod_fallback_detect(text: str) -> tuple[bool, float]:
"""BYOD 关键词兜底:Dify 不可用时通过关键词匹配判断 BYOD 意图。
遍历 BYOD_PREFILTER_KEYWORDS,命中任意一个即认为有 BYOD 意图。
置信度取 0.6(预过滤已通过说明有 BYOD 相关关键词)。
Args:
text: 用户消息文本
Returns:
tuple: (is_byod_intent, confidence)
"""
lower_text = (text or "").lower()
for kw in BYOD_PREFILTER_KEYWORDS:
if kw.lower() in lower_text:
return True, 0.6
return False, 0.0
# =============================================================================
# API 端点
# =============================================================================
@router.post("/byod/detect-intent")
async def detect_byod_intent(request: ByodEligibilityRequest):
"""BYOD 意图检测端点。
流程(复用审批系统三级模式):
1. 关键词预过滤 — 未命中 BYOD 关键词直接返回 false(避免每条消息都调 Dify)
2. 命中关键词 → 调用 Dify 意图识别应用(复用审批 Dify 应用)
3. Dify 调用失败 → 降级为关键词匹配(兜底)
Args:
request: 包含 text(用户消息)和可选的 employee_id
Returns:
ByodEligibilityResponse: 检测结果(仅 is_byod_intent 和 source 字段有效)
"""
text = request.text or ""
# 1. 关键词预过滤
if not _byod_keyword_prefilter(text):
return success_response(data=ByodEligibilityResponse(
is_byod_intent=False,
eligible=False,
source="keyword_prefilter",
))
# 2. 调用 Dify 意图识别
try:
result = await _call_dify_byod_intent(text, request.employee_id or "")
threshold = settings.approval_confidence_threshold
is_byod = result["is_byod_intent"] and result["confidence"] >= threshold
logger.info(
f"BYOD意图检测(Dify): is_byod={is_byod}, "
f"confidence={result['confidence']}"
)
return success_response(data=ByodEligibilityResponse(
is_byod_intent=is_byod,
eligible=False,
source="dify",
))
except Exception as e:
logger.warning(f"Dify BYOD 意图识别失败,降级为关键词匹配: {e}")
# 3. 降级为关键词匹配
is_byod, confidence = _byod_fallback_detect(text)
logger.info(
f"BYOD意图检测(兜底): is_byod={is_byod}, confidence={confidence}"
)
return success_response(data=ByodEligibilityResponse(
is_byod_intent=is_byod,
eligible=False,
source="fallback",
))
@router.post("/byod/check-eligibility")
async def check_byod_eligibility(
request: ByodCheckEligibilityRequest,
redis: aioredis.Redis = Depends(get_redis),
):
"""BYOD 资格检查端点。
流程:
1. 通过企微通讯录 API 获取员工岗位(position
2. 将岗位与资格清单进行匹配(支持精确匹配和模糊匹配)
3. 返回判定结果:
- 可申请 → 返回申请链接 + 注意事项
- 不可申请 → 返回原因
限制性条件(已领公司电脑等)当前版本作为注意事项提示,
暂不接入资产系统自动查询。
Args:
request: 包含 employee_id(员工企微 UserID
redis: Redis 客户端(依赖注入,用于 WecomService 的 token 缓存)
Returns:
ByodEligibilityResponse: 资格检查结果
"""
employee_id = request.employee_id
if not employee_id:
return success_response(data=ByodEligibilityResponse(
is_byod_intent=True,
eligible=False,
reason="缺少员工ID,无法查询岗位信息",
source="wecom",
))
# 1. 通过企微通讯录 API 获取员工信息
wecom_service = WecomService(redis_client=redis)
try:
user_info = await wecom_service.get_user_info(employee_id)
except Exception as e:
logger.error(f"获取员工信息失败: employee_id={employee_id}, error={e}")
return success_response(data=ByodEligibilityResponse(
is_byod_intent=True,
eligible=False,
reason=f"获取员工信息失败:{e}",
source="wecom",
))
finally:
await wecom_service.close()
# 2. 提取岗位信息
position = user_info.get("position", "")
employee_name = user_info.get("name", "")
if not position:
logger.warning(f"员工岗位为空: employee_id={employee_id}, name={employee_name}")
return success_response(data=ByodEligibilityResponse(
is_byod_intent=True,
eligible=False,
position="",
reason="未能获取到您的岗位信息,请联系IT服务台人工核实",
source="wecom",
))
# 3. 岗位匹配
matched, matched_position, matched_category = _match_position(position)
if matched:
logger.info(
f"BYOD资格检查通过: employee_id={employee_id}, name={employee_name}, "
f"position={position}, matched={matched_position}, category={matched_category}"
)
return success_response(data=ByodEligibilityResponse(
is_byod_intent=True,
eligible=True,
has_subsidy=True,
position=position,
matched_category=matched_category,
application_url=BYOD_APPLICATION_URL,
notes=BYOD_NOTES,
source="wecom",
))
else:
logger.info(
f"BYOD资格检查未通过: employee_id={employee_id}, name={employee_name}, "
f"position={position}, 无匹配的资格岗位"
)
return success_response(data=ByodEligibilityResponse(
is_byod_intent=True,
eligible=False,
has_subsidy=False,
position=position,
application_url=BYOD_APPLICATION_URL, # 非补贴也提供登记链接
notes=BYOD_REGISTER_NOTES, # 登记注意事项(非补贴)
reason=f"您的岗位「{position}」不在自备电脑补贴资格清单中,但仍可进行自备电脑登记(无补贴)",
source="wecom",
))
# =============================================================================
# 辅助端点:获取资格岗位清单(供前端展示或调试用)
# =============================================================================
@router.get("/byod/eligible-positions")
async def get_byod_eligible_positions():
"""获取自备电脑补贴资格岗位清单。
返回所有有资格申请自备电脑补贴的岗位,按序列和类别分组。
Returns:
资格岗位清单字典
"""
return success_response(data={
"positions": BYOD_ELIGIBLE_POSITIONS,
"total_count": sum(
len(positions)
for categories in BYOD_ELIGIBLE_POSITIONS.values()
for positions in categories.values()
),
"application_url": BYOD_APPLICATION_URL,
"notes": BYOD_NOTES,
})