v1.1.0 管理后台+对话增强：/admin全数据CRUD与站点配置；快捷语句点击自动提交；Markdown回答渲染；参考资讯折叠链接；实体识别标记与快速查看卡片(entity_linker)

chat.py

@@ -57,9 +57,14 @@ def _grounding_context(user_msg):
 
 
 def chat_once(user_msg, history=None):
-    """单轮对话。返回 (reply, sources, used_tools)
-    sources: 供前端展示的信息来源卡片
+    """单轮对话。返回 (reply, sources, used_tools, news_refs)
+    sources : 供前端展示的信息来源卡片
+    news_refs : 本次回答用到的新闻/百科资讯列表（前端折叠展示为链接）
     """
+    return _chat_impl(user_msg, history)
+
+
+def _chat_impl(user_msg, history=None):
     history = history or []
     messages = [{"role": "system", "content": SYSTEM_PROMPT}]
     for h in history[-10:]:
@@ -68,7 +73,7 @@ def chat_once(user_msg, history=None):
             messages.append({"role": "assistant", "content": h["assistant"]})
     messages.append({"role": "user", "content": user_msg})
 
-    used_tools, sources = [], []
+    used_tools, sources, news_refs = [], [], []
 
     # ---- 第 1 轮：带工具
     try:
@@ -79,9 +84,9 @@ def chat_once(user_msg, history=None):
         msgs = messages + ([{"role": "system", "content": f"以下是数据库检索到的可能相关信息（未直接命中时勿强行引用）：\n{ctx}"}] if ctx else [])
         try:
             resp2 = llm.chat(msgs)
-            return llm.parse_content(resp2), _mk_sources(ctx), [t for t in ("grounding",) if ctx]
+            return llm.parse_content(resp2), _mk_sources(ctx), [t for t in ("grounding",) if ctx], []
         except Exception as e2:
-            return (f"抱歉，大模型服务暂时不可用（{e2}）。你可以稍后再试，或直接浏览下方数据页面。", [], [])
+            return (f"抱歉，大模型服务暂时不可用（{e2}）。你可以稍后再试，或直接浏览下方数据页面。", [], [], [])
 
     # ---- 工具执行（单轮）+ 实体覆盖补全 → 最终无工具作答
     all_executed = []
@@ -89,7 +94,7 @@ def chat_once(user_msg, history=None):
     if not calls:
         calls = _parse_text_tool_calls(llm.parse_content(resp), user_msg)
     if not calls:
-        return llm.parse_content(resp) or "（模型未返回内容）", [], []
+        return llm.parse_content(resp) or "（模型未返回内容）", [], [], []
 
     executed = []
     for c in calls:
@@ -102,6 +107,14 @@ def chat_once(user_msg, history=None):
         used_tools.append(c["name"])
         if result.get("results"):
             sources.append({"tool": c["name"], "items": result["results"][:3]})
+            if c["name"] == "search_news":
+                for it in result["results"][:5]:
+                    if it.get("id"):
+                        news_refs.append({"id": it["id"], "title": it.get("title", ""),
+                                          "source": it.get("source", ""),
+                                          "publish_time": it.get("publish_time", "")})
+        elif c["name"] == "get_game_detail" and isinstance(result, dict) and result.get("id"):
+            sources.append({"tool": "get_game_detail", "items": [result]})
     all_executed += executed
 
     # 覆盖补全：用户问题里提到的其他实体（多球员/多球队对比）自动补查，避免模型漏调
@@ -126,6 +139,14 @@ def chat_once(user_msg, history=None):
                         sources.append({"tool": "search_players" if key == "name" else "search_teams", "items": r["results"][:3]})
                     break
 
+    # 新闻引用去重（按 id）
+    seen_nid, news_refs_u = set(), []
+    for n in news_refs:
+        if n["id"] not in seen_nid:
+            seen_nid.add(n["id"])
+            news_refs_u.append(n)
+    news_refs = news_refs_u
+
     messages.append({"role": "assistant", "content": None,
                      "reasoning_content": llm.extract_reasoning(resp),
                      "tool_calls": [
@@ -139,13 +160,13 @@ def chat_once(user_msg, history=None):
         resp = llm.chat(messages)   # 最终轮：不带工具，让模型基于数据作答
     except Exception as e:
         log.warning("LLM 最终轮失败(%s)，返回工具结果摘要", e)
-        return _finalize(all_executed, user_msg, messages, sources, used_tools), sources, used_tools
+        return _finalize(all_executed, user_msg, messages, sources, used_tools), sources, used_tools, news_refs
 
     reply = llm.parse_content(resp) or ""
     if not reply or "<tool_calls>" in reply or "search_" in reply:
         # 模型又输出工具调用文本 → 注入上下文再答一次
-        return _finalize(all_executed, user_msg, messages, sources, used_tools), sources, used_tools
-    return reply, sources, used_tools
+        return _finalize(all_executed, user_msg, messages, sources, used_tools), sources, used_tools, news_refs
+    return reply, sources, used_tools, news_refs
 
 
 def _finalize(executed, user_msg, messages, sources, used_tools):
@@ -210,16 +231,44 @@ def _mk_sources(ctx):
 
 
 def suggest_questions():
-    """快捷问题（前端展示用）"""
-    return [
-        "最近一场比赛结果",
-        "湖人本赛季战绩怎么样",
-        "库里本赛季场均数据",
-        "2026年总决赛谁赢了",
-        "SGA拿了什么荣誉",
-        "NBA工资帽是什么",
-        "介绍一下波波维奇",
-        "今天有什么新闻",
-        "西部排名",
-        "雷霆和凯尔特人总决赛G6数据",
-    ]
+    """快捷问题（前端展示用，从站点配置读取，管理后台可编辑）"""
+    try:
+        from admin import get_config
+        raw = get_config().get("suggestions") or ""
+        arr = json.loads(raw)
+        if isinstance(arr, list) and arr:
+            return [str(x).strip() for x in arr if str(x).strip()]
+    except Exception:
+        pass
+    return DEFAULT_SUGGESTIONS
+
+
+DEFAULT_SUGGESTIONS = [
+    "最近一场比赛结果",
+    "湖人本赛季战绩怎么样",
+    "库里本赛季场均数据",
+    "2026年总决赛谁赢了",
+    "SGA拿了什么荣誉",
+    "NBA工资帽是什么",
+    "介绍一下波波维奇",
+    "今天有什么新闻",
+    "西部排名",
+    "雷霆和凯尔特人总决赛G6数据",
+]
+
+
+def boot_info():
+    """对话界面启动信息：开场白 + 快捷问题（均可后台配置）"""
+    try:
+        from admin import get_config
+        cfg = get_config()
+    except Exception:
+        cfg = {}
+    return {
+        "site_name": cfg.get("site_name", "NBA球迷大全"),
+        "site_subtitle": cfg.get("site_subtitle", "比赛 · 球员 · 球队 · 资讯 · 人物 · 百科"),
+        "welcome_text": cfg.get("welcome_text", "你好，我是**NBA球迷大全**助手！可以问我任何关于比赛、球员、球队、新闻、人物的问题，我会基于数据库给你准确答案～"),
+        "welcome_hint": cfg.get("welcome_hint", "试试："),
+        "suggestions": suggest_questions(),
+        "footer_text": cfg.get("footer_text", "NBA球迷大全 · 数据为模拟演示数据（2025-26 赛季）"),
+    }