Upload app.py

app.py

@@ -868,16 +868,17 @@ with st.sidebar:
     # --- 模型设置 ---
     with st.expander("⚙️ 模型设置"):
         selected_display_name = st.selectbox(
-            "模型", list(model_mapping.keys()), index=0, label_visibility="collapsed"
+            "模型", list(model_mapping.keys()), index=0, label_visibility="collapsed",
+            key="sel_model"
         )
 
-        web_on = st.toggle("🌐 联网增强", value=False)
+        web_on = st.toggle("🌐 联网增强", value=False, key="sel_web")
 
         c1, c2 = st.columns(2)
         with c1:
-            ui_top_k = st.number_input("Top-K", 1, 15, 5)
+            ui_top_k = st.number_input("Top-K", 1, 15, 5, key="sel_topk")
         with c2:
-            ui_threshold = st.number_input("阈值", 0.0, 1.0, 0.25, step=0.05)
+            ui_threshold = st.number_input("阈值", 0.0, 1.0, 0.25, step=0.05, key="sel_threshold")
 
     # --- 修改密码 ---
     with st.expander("🔐 修改密码"):
@@ -1125,7 +1126,7 @@ def llm_answer(query, context_docs, selected_display_name, web_enabled):
 
 
 # =========================
-# 10. 聊天渲染
+# 10. 聊天渲染（使用 @st.fragment 避免整页刷新）
 # =========================
 if "messages" not in st.session_state:
     # 首次加载时从数据库恢复最近对话
@@ -1136,40 +1137,53 @@ if "messages" not in st.session_state:
         for m in saved
     ]
 
-for m in st.session_state.messages:
-    with st.chat_message(m["role"]):
-        st.markdown(m["content"])
-        if "meta" in m:
-            st.caption(m["meta"])
-
-if q := st.chat_input("输入问题...", key="chat_input_v3"):
-    st.session_state.messages.append({"role": "user", "content": q})
-    _save_chat_message(CURRENT_USER, "user", q)
-    with st.chat_message("user"):
-        st.markdown(q)
-
-    with st.chat_message("assistant"):
-        container = st.empty()
-        container.markdown("*🔍 正在搜索知识库...*")
-        relevant_docs = search_local(q, ui_top_k, ui_threshold)
-        container.markdown("*🤔 正在组织语言...*")
-
-        if web_on:
-            with st.status("🌐 正在抓取实时网络数据...", expanded=False) as s:
-                time.sleep(0.1)
-                s.update(label="✅ 网络资料已就绪", state="complete")
 
-        try:
-            full_response = container.write_stream(
-                llm_answer(q, relevant_docs, selected_display_name, web_on)
-            )
-            meta_info = st.session_state.get("last_meta", "")
-            st.caption(meta_info)
-            st.session_state.messages.append(
-                {"role": "assistant", "content": full_response, "meta": meta_info}
-            )
-            _save_chat_message(CURRENT_USER, "assistant", full_response, meta_info)
-        except Exception as e:
-            logger.error(f"模型调用异常: {e}")
-            container.error(f"❌ 抱歉，连接模型时出错了: {str(e)}")
+@st.fragment
+def _chat_fragment():
+    """聊天区域独立 fragment，提交消息时只刷新此区域，不刷新整个页面。"""
+    # 从 session_state 读取侧边栏设置（fragment 内部无法直接访问外部局部变量）
+    _model_name = st.session_state.get("sel_model", list(model_mapping.keys())[0])
+    _web_on = st.session_state.get("sel_web", False)
+    _top_k = st.session_state.get("sel_topk", 5)
+    _threshold = st.session_state.get("sel_threshold", 0.25)
+
+    for m in st.session_state.messages:
+        with st.chat_message(m["role"]):
+            st.markdown(m["content"])
+            if "meta" in m:
+                st.caption(m["meta"])
+
+    if q := st.chat_input("输入问题...", key="chat_input_v3"):
+        st.session_state.messages.append({"role": "user", "content": q})
+        _save_chat_message(CURRENT_USER, "user", q)
+        with st.chat_message("user"):
+            st.markdown(q)
+
+        with st.chat_message("assistant"):
+            container = st.empty()
+            container.markdown("*🔍 正在搜索知识库...*")
+            relevant_docs = search_local(q, _top_k, _threshold)
+            container.markdown("*🤔 正在组织语言...*")
+
+            if _web_on:
+                with st.status("🌐 正在抓取实时网络数据...", expanded=False) as s:
+                    time.sleep(0.1)
+                    s.update(label="✅ 网络资料已就绪", state="complete")
+
+            try:
+                full_response = container.write_stream(
+                    llm_answer(q, relevant_docs, _model_name, _web_on)
+                )
+                meta_info = st.session_state.get("last_meta", "")
+                st.caption(meta_info)
+                st.session_state.messages.append(
+                    {"role": "assistant", "content": full_response, "meta": meta_info}
+                )
+                _save_chat_message(CURRENT_USER, "assistant", full_response, meta_info)
+            except Exception as e:
+                logger.error(f"模型调用异常: {e}")
+                container.error(f"❌ 抱歉，连接模型时��错了: {str(e)}")
+
+
+_chat_fragment()