diff --git a/backend/app/api/ai_analysis.py b/backend/app/api/ai_analysis.py index 03c4c6d4..945d7615 100644 --- a/backend/app/api/ai_analysis.py +++ b/backend/app/api/ai_analysis.py @@ -8,7 +8,7 @@ from app.deps import get_entity_id from app.auth_middleware import require_auth, require_role from app.models import KPIDefinition, KPIValue, KPIAlert, StrategicMap, User, ActionPlan, BudgetPlan, AISuggestion from app.utils.cache import get as cache_get, set as cache_set -import json, hashlib, httpx, os +import json, hashlib, httpx, os, urllib.request from datetime import datetime, date router = APIRouter(prefix="/api/cma/ai", tags=["AI分析"], dependencies=[Depends(require_role("ceo", "finance", "business", "it"))], @@ -25,6 +25,8 @@ def _sug_dict(s: AISuggestion) -> dict: "source": s.source, "suggestion_type": s.suggestion_type, "target_type": s.target_type, + "category": s.category or "decision", + "pushed": s.pushed or 0, "target_id": s.target_id, "title": s.title, "content": s.content, @@ -76,6 +78,7 @@ def generate_rule_suggestions(db: Session, entity_id: int, source=source, suggestion_type=suggestion_type, target_type=target_type, + category="alert" if target_type == "alert" else "decision", target_id=tid, title=title, content=content, @@ -170,9 +173,51 @@ def generate_rule_suggestions(db: Session, entity_id: int, db.commit() for s in created: db.refresh(s) + # R1触达修复(2026-08-31): 只对新建的决策类建议推送企微（预警类不推防噪音） + # 防轰炸: 同 title 建议幂等不重建 + pushed 标记只推一次；存量不推（只推新建） + for s in created: + if s.category == "decision" and not s.pushed: + ok = _push_decision_suggestion(s) + if ok: + s.pushed = 1 + db.commit() return created +_TYPE_LABELS = {"kpi_target": "KPI目标", "budget_adjust": "预算调整", "action_plan": "行动方案"} + + +def _push_decision_suggestion(s: AISuggestion) -> bool: + """决策类建议推送到企微（8800 relay，与 lead.py 同款已验证） + + 仅 decision 类；预警类不进推送流。失败不影响主流程（try/except）。 + """ + if getattr(s, "category", "decision") != "decision": + return False + type_label = _TYPE_LABELS.get(s.suggestion_type, s.suggestion_type) + content = ( + f"## 📌 AI决策建议\n" + f"**{s.title}**\n" + f"{str(s.content or '')[:120]}\n" + f"类型标签: {type_label}\n" + f"---\n" + f"⏰ {datetime.now().strftime('%Y-%m-%d %H:%M')}" + ) + msg = {"msgtype": "markdown", "markdown": {"content": content}} + try: + data = json.dumps(msg, ensure_ascii=False).encode("utf-8") + req = urllib.request.Request( + "http://127.0.0.1:8800/send", + data=data, + headers={"Content-Type": "application/json"}, + method="POST", + ) + urllib.request.urlopen(req, timeout=5) + return True + except Exception: + return False + + def _unapplied_suggestions(db: Session, entity_id: int, limit: int = 20) -> list: items = db.query(AISuggestion).filter( AISuggestion.entity_id == entity_id, diff --git a/backend/app/api/ai_suggestions.py b/backend/app/api/ai_suggestions.py index e5e018c4..9bcb6d50 100644 --- a/backend/app/api/ai_suggestions.py +++ b/backend/app/api/ai_suggestions.py @@ -27,6 +27,8 @@ def _sug_dict(s: AISuggestion) -> dict: "source": s.source, "suggestion_type": s.suggestion_type, "target_type": s.target_type, + "category": s.category or "decision", + "pushed": s.pushed or 0, "target_id": s.target_id, "title": s.title, "content": s.content, @@ -62,6 +64,7 @@ def create_suggestion( source=data.get("source", "manual"), suggestion_type=suggestion_type, target_type=data.get("target_type", "kpi"), + category="alert" if data.get("target_type") == "alert" else data.get("category", "decision"), target_id=data.get("target_id"), title=title, content=data.get("content"), @@ -78,6 +81,7 @@ def create_suggestion( def list_suggestions( status: Optional[str] = Query(None, description="unapplied/applied/dismissed"), suggestion_type: Optional[str] = Query(None), + category: Optional[str] = Query(None, description="decision/alert 建议分类过滤"), entity_id: int = Depends(get_entity_id), db: Session = Depends(get_db), ): @@ -87,6 +91,8 @@ def list_suggestions( query = query.filter(AISuggestion.status == status) if suggestion_type: query = query.filter(AISuggestion.suggestion_type == suggestion_type) + if category: + query = query.filter(AISuggestion.category == category) items = query.order_by(AISuggestion.created_at.desc()).limit(200).all() return {"data": [_sug_dict(s) for s in items], "total": len(items)} @@ -275,6 +281,60 @@ _APPLYERS = { } +@router.get("/{suggestion_id}/preview") +def preview_suggestion(suggestion_id: int, db: Session = Depends(get_db), + entity_id: int = Depends(get_entity_id)): + """应用前预览：将变更什么（当前值 → 新值），建立信任 (R1触达修复 2026-08-31) + + - kpi_target: {kpi_name, current_target, new_target} + - budget_adjust:{kpi_name, period, current_budget, new_budget} + - action_plan: {kpi_name, plan_title, assignee, priority, due_date} + """ + sug = db.query(AISuggestion).filter(AISuggestion.id == suggestion_id).first() + if not sug: + raise HTTPException(404, "建议不存在") + sd = sug.suggestion_data or {} + kpi = None + kpi_id = sd.get("kpi_id") or sug.target_id + if kpi_id: + kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first() + + if sug.suggestion_type == "kpi_target": + return {"data": { + "type": "kpi_target", + "kpi_name": kpi.kpi_name if kpi else "KPI#" + str(kpi_id), + "current_target": kpi.target_value if kpi else None, + "new_target": sd.get("target_value"), + }} + if sug.suggestion_type == "budget_adjust": + period = sd.get("period") or sug.target_type + current_budget = None + if kpi and period: + bp = db.query(BudgetPlan).filter( + BudgetPlan.entity_id == sug.entity_id, + BudgetPlan.kpi_id == kpi.id, + BudgetPlan.period == period, + BudgetPlan.status == "active", + ).order_by(BudgetPlan.id.desc()).first() + current_budget = bp.budget_value if bp else None + return {"data": { + "type": "budget_adjust", + "kpi_name": kpi.kpi_name if kpi else "KPI#" + str(kpi_id), + "period": period, + "current_budget": current_budget, + "new_budget": sd.get("budget_value"), + }} + # action_plan + return {"data": { + "type": "action_plan", + "kpi_name": kpi.kpi_name if kpi else "KPI#" + str(kpi_id), + "plan_title": sd.get("title") or sug.title, + "assignee": sd.get("assignee") or "", + "priority": sd.get("priority") or "medium", + "due_date": sd.get("due_date") or "", + }} + + @router.post("/{suggestion_id}/apply") def apply_suggestion( suggestion_id: int, diff --git a/backend/app/models/__init__.py b/backend/app/models/__init__.py index d13351ed..3742cf83 100644 --- a/backend/app/models/__init__.py +++ b/backend/app/models/__init__.py @@ -922,6 +922,8 @@ class AISuggestion(Base): source = Column(String(30), default="dashboard", comment="来源: dashboard/kpi/budget/manual/rule") suggestion_type = Column(String(30), nullable=False, comment="kpi_target/budget_adjust/action_plan") target_type = Column(String(30), nullable=False, comment="kpi/budget/action_plan") + category = Column(String(20), default="decision", comment="分类: decision决策类 / alert预警类（预警类不推送）") + pushed = Column(Integer, default=0, comment="决策类建议是否已推送企微 0/1（防轰炸）") target_id = Column(Integer, nullable=True, comment="目标ID (KPI ID/预算KPI ID等)") title = Column(String(300), nullable=False, comment="建议标题") content = Column(Text, nullable=True, comment="建议内容/理由") diff --git a/backend/tests/conftest.py b/backend/tests/conftest.py index a8370e99..c0d0195e 100644 --- a/backend/tests/conftest.py +++ b/backend/tests/conftest.py @@ -90,6 +90,17 @@ def setup_db(): cache_util.delete("ai") +@pytest.fixture(autouse=True) +def _disable_ai_suggestion_push(monkeypatch): + """R1触达修复(2026-08-31): 测试库把企微推送替换为 no-op，防测试建议推真实企微群 + + 生产环境真实推送（8800 relay）；测试只验证推送逻辑（决策类推/预警不推/幂等）不打真实企微。 + 测试类如需断言推送内容，可自行 monkeypatch.setattr 覆盖本 no-op。 + """ + from app.api import ai_analysis + monkeypatch.setattr(ai_analysis, "_push_decision_suggestion", lambda s: True) + + @pytest.fixture def db() -> Generator[Session, None, None]: """提供数据库 session""" diff --git a/backend/tests/test_ai_suggestions.py b/backend/tests/test_ai_suggestions.py index d6908516..ac8db3e8 100644 --- a/backend/tests/test_ai_suggestions.py +++ b/backend/tests/test_ai_suggestions.py @@ -240,3 +240,269 @@ class TestRuleSuggestions: assert resp.status_code == 200 s = db.query(AISuggestion).filter(AISuggestion.suggestion_type == "budget_adjust").all() assert len(s) >= 1 + + +class TestSuggestionCategoryPreview: + """R1触达修复(2026-08-31)：建议分级(alert/decision) + 列表过滤 + 应用前预览 + 推送开关""" + + def test_create_marks_category(self, client, db): + """手动创建：target_type=alert → category=alert；其余 → decision""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db) + + r_alert = _create_suggestion(client, token, kpi.id, target_type="alert", + suggestion_type="action_plan", title="预警类建议") + assert r_alert.json()["data"]["category"] == "alert" + + r_decision = _create_suggestion(client, token, kpi.id, title="决策类建议") + assert r_decision.json()["data"]["category"] == "decision" + + def test_category_filter(self, client, db): + """列表接口 category 过滤""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db) + _create_suggestion(client, token, kpi.id, target_type="alert", + suggestion_type="action_plan", title="预警A") + _create_suggestion(client, token, kpi.id, title="决策B") + + lst_alert = client.get("/api/cma/ai/suggestions", params={"category": "alert"}, + headers=auth_header(token)).json() + assert lst_alert["total"] == 1 + assert all(x["category"] == "alert" for x in lst_alert["data"]) + + lst_decision = client.get("/api/cma/ai/suggestions", params={"category": "decision"}, + headers=auth_header(token)).json() + assert lst_decision["total"] == 1 + assert all(x["category"] == "decision" for x in lst_decision["data"]) + + def test_generate_marks_decision(self, client, db): + """规则生成：执行率<70%建议（target_type=kpi）→ category=decision""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db, target_value=100.0) + db.add(KPIValue(kpi_id=kpi.id, period="2026-06", actual_value=50.0)) + db.commit() + + client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token)) + sug = db.query(AISuggestion).filter(AISuggestion.target_id == kpi.id).first() + assert sug is not None + assert sug.category == "decision" + + def test_push_disabled_in_test_env(self, client, db): + """conftest no-op 推送（monkeypatch）→ 生成决策建议不真推企微，pushed 标记置 1""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db, target_value=100.0) + db.add(KPIValue(kpi_id=kpi.id, period="2026-06", actual_value=50.0)) + db.commit() + + client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token)) + sug = db.query(AISuggestion).filter(AISuggestion.target_id == kpi.id).first() + assert sug is not None + assert sug.pushed == 1 + + def test_preview_kpi_target(self, client, db): + """preview：kpi_target 返回 当前目标 → 新目标""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db, target_value=100.0) + r = _create_suggestion(client, token, kpi.id, + suggestion_data={"kpi_id": kpi.id, "target_value": 150.0}) + sug_id = r.json()["data"]["id"] + + pv = client.get(f"/api/cma/ai/suggestions/{sug_id}/preview", headers=auth_header(token)) + assert pv.status_code == 200, pv.text + data = pv.json()["data"] + assert data["type"] == "kpi_target" + assert data["kpi_name"] == "测试KPI" + assert data["current_target"] == 100.0 + assert data["new_target"] == 150.0 + + def test_preview_budget_adjust(self, client, db): + """preview：budget_adjust 返回 当前预算 → 新预算""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db) + db.add(BudgetPlan(entity_id=1, kpi_id=kpi.id, period="2026-09", budget_value=8000.0, + budget_year=2026, budget_month=9, status="active")) + db.commit() + r = _create_suggestion(client, token, kpi.id, suggestion_type="budget_adjust", + title="调预算预览", suggestion_data={"kpi_id": kpi.id, "period": "2026-09", + "budget_value": 9999.0}) + sug_id = r.json()["data"]["id"] + + pv = client.get(f"/api/cma/ai/suggestions/{sug_id}/preview", headers=auth_header(token)) + assert pv.status_code == 200, pv.text + data = pv.json()["data"] + assert data["type"] == "budget_adjust" + assert data["period"] == "2026-09" + assert data["current_budget"] == 8000.0 + assert data["new_budget"] == 9999.0 + + def test_preview_action_plan(self, client, db): + """preview：action_plan 返回计划信息""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db) + r = _create_suggestion(client, token, kpi.id, suggestion_type="action_plan", + title="建行动方案预览", suggestion_data={"kpi_id": kpi.id, + "title": "专项改善", "priority": "high", + "due_date": "2026-09-30"}) + sug_id = r.json()["data"]["id"] + + pv = client.get(f"/api/cma/ai/suggestions/{sug_id}/preview", headers=auth_header(token)) + assert pv.status_code == 200, pv.text + data = pv.json()["data"] + assert data["type"] == "action_plan" + assert data["plan_title"] == "专项改善" + assert data["priority"] == "high" + assert data["due_date"] == "2026-09-30" + + +class TestCategoryAndPreview: + """R1触达修复(2026-08-31)：建议分级 + 应用前预览""" + + def _generate(self, client, db, kpi_id, actual, target=100.0): + """造一条KPI数据并触发 dashboard-analysis 规则生成（避开缓存）""" + db.add(KPIValue(kpi_id=kpi_id, period="2026-07", actual_value=actual)) + db.commit() + from app.utils.cache import delete as cache_delete + cache_delete("ai", f"dashboard_analysis:ceo:{kpi_id}") + resp = client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(get_token_for_user(client))) + assert resp.status_code == 200 + return resp.json() + + def test_generate_marks_category(self, client, db, monkeypatch): + """生成建议时: target_type=alert → category=alert；其余 → decision""" + from app.api import ai_analysis + pushed = [] + ai_analysis._push_decision_suggestion = lambda s: pushed.append(s) or True + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db, target_value=100.0) + db.add(KPIValue(kpi_id=kpi.id, period="2026-06", actual_value=50.0)) + db.commit() + + client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token)) + + kpi_sugs = db.query(AISuggestion).filter(AISuggestion.target_id == kpi.id).all() + assert len(kpi_sugs) >= 1 + for s in kpi_sugs: + assert s.category == "decision", f"KPI建议应决策类: {s.title}" + + # 建一条预警 → 规则4生成 alert 类建议 + from app.models import KPIAlert + db.add(KPIAlert(kpi_id=kpi.id, alert_level="yellow", alert_message="测试预警", + alert_type="threshold", status="pending")) + db.commit() + client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token)) + alert_sugs = db.query(AISuggestion).filter(AISuggestion.target_type == "alert").all() + assert len(alert_sugs) >= 1 + for s in alert_sugs: + assert s.category == "alert", f"预警建议应alert类: {s.title}" + + def test_alert_not_pushed_decision_pushed(self, client, db, monkeypatch): + """推送只发决策类：预警类不推，决策类推且只推一次(pushed=1)""" + from app.api import ai_analysis + pushed = [] + ai_analysis._push_decision_suggestion = lambda s: pushed.append(s) or True + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db, target_value=100.0) + db.add(KPIValue(kpi_id=kpi.id, period="2026-06", actual_value=50.0)) + db.commit() + client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token)) + + kpi_sugs = db.query(AISuggestion).filter(AISuggestion.target_id == kpi.id).all() + assert len(pushed) >= 1 + assert all(s.category == "decision" for s in pushed) + for s in pushed: + assert s.pushed == 1 + + # 预警类建议不在推送流 + from app.models import KPIAlert + db.add(KPIAlert(kpi_id=kpi.id, alert_level="red", alert_message="测试预警2", + alert_type="threshold", status="pending")) + db.commit() + before = len(pushed) + client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token)) + alert_sugs = db.query(AISuggestion).filter(AISuggestion.target_type == "alert").all() + assert len(alert_sugs) >= 1 + assert len(pushed) == before, "预警类不应触发推送" + + # 幂等：重复生成不重推（同title建议不重建） + client.get("/api/cma/ai/dashboard-analysis", headers=auth_header(token)) + assert len(pushed) == before + + def test_list_category_filter(self, client, db): + """列表接口 category 过滤""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db) + _create_suggestion(client, token, kpi.id, title="决策类A") + _create_suggestion(client, token, kpi.id, title="决策类B") + _create_suggestion(client, token, kpi.id, title="预警类C", target_type="alert") + + lst = client.get("/api/cma/ai/suggestions?category=decision", headers=auth_header(token)).json() + assert lst["total"] == 2 + assert all(x["category"] == "decision" for x in lst["data"]) + lst2 = client.get("/api/cma/ai/suggestions?category=alert", headers=auth_header(token)).json() + assert lst2["total"] == 1 + assert lst2["data"][0]["category"] == "alert" + + def test_preview_kpi_target(self, client, db): + """preview: kpi_target 返回 current_target → new_target""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db, target_value=100.0) + r = _create_suggestion(client, token, kpi.id, suggestion_data={"kpi_id": kpi.id, "target_value": 150.0}) + sug_id = r.json()["data"]["id"] + + pv = client.get(f"/api/cma/ai/suggestions/{sug_id}/preview", headers=auth_header(token)).json()["data"] + assert pv["type"] == "kpi_target" + assert pv["kpi_name"] == kpi.kpi_name + assert pv["current_target"] == 100.0 + assert pv["new_target"] == 150.0 + + def test_preview_budget_adjust(self, client, db): + """preview: budget_adjust 返回 current_budget → new_budget""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db) + db.add(BudgetPlan(entity_id=1, kpi_id=kpi.id, period="2026-09", budget_value=5000.0, + budget_year=2026, budget_month=9, status="active")) + db.commit() + r = _create_suggestion(client, token, kpi.id, suggestion_type="budget_adjust", + title="调预算", suggestion_data={"kpi_id": kpi.id, "period": "2026-09", "budget_value": 8888.0}) + sug_id = r.json()["data"]["id"] + + pv = client.get(f"/api/cma/ai/suggestions/{sug_id}/preview", headers=auth_header(token)).json()["data"] + assert pv["type"] == "budget_adjust" + assert pv["current_budget"] == 5000.0 + assert pv["new_budget"] == 8888.0 + assert pv["period"] == "2026-09" + + def test_preview_action_plan(self, client, db): + """preview: action_plan 返回计划参数""" + create_test_user(db) + token = get_token_for_user(client) + kpi = create_test_kpi(db) + r = _create_suggestion(client, token, kpi.id, suggestion_type="action_plan", + title="建行动方案", suggestion_data={"kpi_id": kpi.id, "title": "改善专项", + "assignee": "李四", "priority": "high", "due_date": "2026-10-01"}) + sug_id = r.json()["data"]["id"] + + pv = client.get(f"/api/cma/ai/suggestions/{sug_id}/preview", headers=auth_header(token)).json()["data"] + assert pv["type"] == "action_plan" + assert pv["plan_title"] == "改善专项" + assert pv["assignee"] == "李四" + assert pv["priority"] == "high" + assert pv["due_date"] == "2026-10-01" + + def test_preview_not_found(self, client, db): + create_test_user(db) + token = get_token_for_user(client) + r = client.get("/api/cma/ai/suggestions/99999/preview", headers=auth_header(token)) + assert r.status_code == 404 diff --git a/frontend/src/api/index.ts b/frontend/src/api/index.ts index ac5be6fe..a768f681 100644 --- a/frontend/src/api/index.ts +++ b/frontend/src/api/index.ts @@ -472,6 +472,7 @@ export const aiSuggestionApi = { create: (data: any) => api.post('/ai/suggestions', data), apply: (id: number, data: any) => api.post(`/ai/suggestions/${id}/apply`, data), dismiss: (id: number) => api.post(`/ai/suggestions/${id}/dismiss`), + preview: (id: number) => api.get(`/ai/suggestions/${id}/preview`), } export default api diff --git a/frontend/src/views/SuggestionCenter.vue b/frontend/src/views/SuggestionCenter.vue index 54eb7220..e9f111b8 100644 --- a/frontend/src/views/SuggestionCenter.vue +++ b/frontend/src/views/SuggestionCenter.vue @@ -18,6 +18,7 @@
{{ sugTypeLabel(s.suggestion_type) }} + {{ s.category === 'alert' ? '预警' : '决策' }} {{ statusLabel(s.status) }} 来源: {{ sourceLabel(s.source) }}
@@ -45,6 +46,27 @@ +
预览加载中...
+
+
📋 将变更什么
+ + + +
确认后将写入系统并留痕，请核对后操作
+