hg-agents/backend/modules/monitor/router.py

import uuid
import json
from datetime import datetime
from fastapi import APIRouter, Depends, HTTPException, Request
from sqlalchemy import select, func
from sqlalchemy.ext.asyncio import AsyncSession
from database import get_db
from models import User, ChatSession, ChatMessage
from modules.org.router import _get_subordinate_ids, _user_to_out
from schemas import EmployeeAnalysis, UserOut

router = APIRouter(prefix="/api/monitor", tags=["monitor"])


@router.get("/employees", response_model=list[UserOut])
async def get_monitor_employees(request: Request, db: AsyncSession = Depends(get_db)):
    user_ctx = request.state.user
    cur_id = uuid.UUID(user_ctx["id"])

    if user_ctx["data_scope"] == "all":
        result = await db.execute(select(User).where(User.status == "active"))
        return [await _user_to_out(db, u) for u in result.scalars().all()]

    elif user_ctx["data_scope"] == "subordinate_only":
        sub_ids = await _get_subordinate_ids(db, cur_id)
        sub_ids.add(cur_id)
        result = await db.execute(select(User).where(User.id.in_(sub_ids)))
        return [await _user_to_out(db, u) for u in result.scalars().all()]

    else:
        result = await db.execute(select(User).where(User.id == cur_id))
        return [await _user_to_out(db, u) for u in result.scalars().all()]


@router.get("/employee/{emp_id}/dashboard")
async def get_employee_dashboard(
    emp_id: uuid.UUID, request: Request, db: AsyncSession = Depends(get_db)
):
    user_ctx = request.state.user
    cur_id = uuid.UUID(user_ctx["id"])

    if user_ctx["data_scope"] != "all":
        if user_ctx["data_scope"] == "self_only" and str(emp_id) != user_ctx["id"]:
            raise HTTPException(403, "无权查看此员工数据")
        elif user_ctx["data_scope"] == "subordinate_only":
            sub_ids = await _get_subordinate_ids(db, cur_id)
            sub_ids.add(cur_id)
            if emp_id not in sub_ids:
                raise HTTPException(403, "无权查看此员工数据")

    emp_result = await db.execute(select(User).where(User.id == emp_id))
    emp = emp_result.scalar_one_or_none()
    if not emp:
        raise HTTPException(404, "员工不存在")

    total_msgs_result = await db.execute(
        select(func.count(ChatMessage.id)).where(ChatMessage.user_id == emp_id)
    )
    total_messages = total_msgs_result.scalar() or 0

    session_result = await db.execute(
        select(func.count(ChatSession.id)).where(ChatSession.user_id == emp_id)
    )
    total_sessions = session_result.scalar() or 0

    recent_msgs_result = await db.execute(
        select(ChatMessage)
        .where(ChatMessage.user_id == emp_id)
        .order_by(ChatMessage.created_at.desc())
        .limit(50)
    )
    recent = recent_msgs_result.scalars().all()

    topics = {}
    active_days = set()
    for msg in recent:
        if msg.created_at:
            active_days.add(msg.created_at.strftime("%Y-%m-%d"))
        role = msg.role
        topics[role] = topics.get(role, 0) + 1

    return {
        "code": 200,
        "data": {
            "employee": {
                "id": str(emp.id),
                "name": emp.display_name,
                "department": str(emp.department_id) if emp.department_id else "",
                "position": emp.position or "",
            },
            "stats": {
                "total_messages": total_messages,
                "total_sessions": total_sessions,
                "active_days": len(active_days),
                "message_breakdown": topics,
                "recent_interactions": [
                    {"role": m.role, "content": m.content[:200], "created_at": str(m.created_at)}
                    for m in recent[:10]
                ],
            },
        },
    }


@router.get("/employee/{emp_id}/analysis", response_model=EmployeeAnalysis)
async def get_employee_analysis(
    emp_id: uuid.UUID, request: Request, db: AsyncSession = Depends(get_db)
):
    user_ctx = request.state.user
    cur_id = uuid.UUID(user_ctx["id"])

    if user_ctx["data_scope"] != "all":
        if user_ctx["data_scope"] == "self_only" and str(emp_id) != user_ctx["id"]:
            raise HTTPException(403, "无权查看此员工数据")
        elif user_ctx["data_scope"] == "subordinate_only":
            sub_ids = await _get_subordinate_ids(db, cur_id)
            sub_ids.add(cur_id)
            if emp_id not in sub_ids:
                raise HTTPException(403, "无权查看此员工数据")

    emp_result = await db.execute(select(User).where(User.id == emp_id))
    emp = emp_result.scalar_one_or_none()
    if not emp:
        raise HTTPException(404, "员工不存在")

    from config import settings
    from agentscope.model import OpenAIChatModel
    from agentscope.formatter import OpenAIChatFormatter
    from agentscope.message import Msg

    msgs_result = await db.execute(
        select(ChatMessage)
        .where(ChatMessage.user_id == emp_id)
        .order_by(ChatMessage.created_at.desc())
        .limit(100)
    )
    messages = msgs_result.scalars().all()

    interaction_log = "\n".join([
        f"[{m.role}] {m.content[:300]}" for m in messages
    ])

    model = OpenAIChatModel(
        config_name="analysis_model",
        model_name=settings.LLM_MODEL,
        api_key=settings.LLM_API_KEY,
        api_base=settings.LLM_API_BASE,
    )
    formatter = OpenAIChatFormatter()

    prompt = formatter.format([
        Msg("system", f"""你是一个企业管理者分析助手。请根据员工与AI的交互记录，生成一个JSON格式的分析报告。

要求:
1. 分析员工的task_completion_rate (0-1的浮点数)
2. 统计active_days和total_interactions
3. 提取main_topics (最多5个关键词)
4. 评估efficiency_trend ("提升" / "稳定" / "下降")
5. 给出efficiency_detail (一句话说明)
6. 列出strengths (2-3个优点)
7. 给出growth_suggestions (2-3条建议)
8. 总结personality_traits (一句话)

输出严格JSON格式，不要包含markdown代码块标记。""", "system"),
        Msg("user", f"员工姓名: {emp.display_name}\n交互记录:\n{interaction_log}", "user"),
    ])

    try:
        res = await model(prompt)
        res_text = ""
        if isinstance(res, list):
            res_text = res[0].get_text_content() if hasattr(res[0], 'get_text_content') else str(res[0])
        elif hasattr(res, 'get_text_content'):
            res_text = res.get_text_content()
        else:
            res_text = str(res)
        analysis_data = json.loads(res_text)
    except Exception:
        analysis_data = {
            "task_completion_rate": 0.7,
            "active_days": 0,
            "total_interactions": len(messages),
            "main_topics": [],
            "efficiency_trend": "稳定",
            "efficiency_detail": "暂无足够数据",
            "strengths": [],
            "growth_suggestions": [],
            "personality_traits": "暂未收集足够人格特征数据",
        }

    return EmployeeAnalysis(
        employee_name=emp.display_name,
        department=str(emp.department_id) if emp.department_id else "",
        period=f"最近数据",
        **analysis_data
    )