Initial travel knowledge graph release

app/api/simulation_panel.py

@@ -0,0 +1,98 @@
+"""STEP 02 — Simulation Panel CRUD + multi-source question intake.
+
+Question bank for the AI quality audit. Sources:
+  manual    手工添加
+  imported  批量导入的真实用户问题
+  resolved  从"已答好"的 question_traces 采纳的回归用例
+  ai_gen    AI 生成的覆盖性问题
+"""
+from fastapi import APIRouter, HTTPException
+
+from app.auth import CurrentUser
+from app.config import settings
+from app.contracts import SimulationQuestion, SimulationQuestionUpdate
+from app.db import (
+    list_simulation_questions,
+    create_simulation_question,
+    update_simulation_question,
+    delete_simulation_question,
+    bulk_create_simulation_questions,
+    adopt_hit_question_traces,
+)
+
+router = APIRouter()
+_T = settings.default_tenant
+_P = settings.default_project
+
+
+@router.get("/simulation-panel")
+async def _list(_user: CurrentUser = None):
+    return await list_simulation_questions(_T, _P)
+
+
+@router.post("/simulation-panel")
+async def _create(body: SimulationQuestion, _user: CurrentUser):
+    data = body.model_dump()
+    data["tenant_id"] = _T
+    data["project_id"] = _P
+    data["source"] = "manual"
+    return await create_simulation_question(data)
+
+
+@router.post("/simulation-panel/import")
+async def _import(body: dict, _user: CurrentUser):
+    """Bulk import real user questions — one per line, or a list."""
+    raw = body.get("text") or body.get("questions") or ""
+    texts = raw if isinstance(raw, list) else str(raw).splitlines()
+    added = await bulk_create_simulation_questions(_T, _P, texts, "imported")
+    return {"added": added}
+
+
+@router.post("/simulation-panel/adopt-hits")
+async def _adopt_hits(_user: CurrentUser):
+    """Adopt well-answered questions as regression cases (source=resolved)."""
+    added = await adopt_hit_question_traces(_T, _P)
+    return {"added": added}
+
+
+@router.post("/simulation-panel/ai-generate")
+async def _ai_generate(body: dict, _user: CurrentUser):
+    """Let the LLM propose representative coverage questions."""
+    from app.llm_client import LlmClient
+
+    llm = LlmClient.from_settings() if settings.llm_api_key else None
+    if not llm or not llm.available():
+        raise HTTPException(400, "未配置 LLM（Agent 设置里填好 API Key 后可用）")
+
+    count = max(1, min(int(body.get("count", 10)), 30))
+    topic = (body.get("topic") or "城市本地生活知识图谱（地点、区域、路线、夜间体验、标签）").strip()
+    try:
+        out = llm.chat_json(
+            system=(
+                "你是知识图谱质量稽查助手。请基于给定主题，生成有代表性、"
+                "覆盖不同场景的真实用户中文问题，用于检验知识图谱数据的完善度。"
+                '严格返回 JSON：{"questions": ["...", "..."]}'
+            ),
+            user=f"主题：{topic}。生成 {count} 个不同角度、不重复的问题。",
+        )
+        qs = out.get("questions") or []
+        qs = [str(q).strip() for q in qs if str(q).strip()][:count]
+    except Exception as e:
+        raise HTTPException(400, f"AI 生成失败：{str(e)[:160]}")
+
+    added = await bulk_create_simulation_questions(_T, _P, qs, "ai_gen")
+    return {"added": added, "generated": len(qs)}
+
+
+@router.patch("/simulation-panel/{q_id}")
+async def _update(q_id: int, body: SimulationQuestionUpdate, _user: CurrentUser):
+    row = await update_simulation_question(q_id, body.model_dump(exclude_none=True))
+    if not row:
+        raise HTTPException(404, "Simulation question not found")
+    return row
+
+
+@router.delete("/simulation-panel/{q_id}")
+async def _delete(q_id: int, _user: CurrentUser):
+    await delete_simulation_question(q_id)
+    return {"ok": True}