chore(align): sync Git with running container as authoritative source

Phase 0 SSE 流式聊天 landed in the running container and captured in Git so
the three sources (container := image := Git) agree.

Phase 0 — SSE 流式聊天（Web 端，IM bot 路径保持不变、共用引擎）:
- app/api/chat.py: 新增独立 SSE 端点
  POST /app/api/chat/conversations/{conv_id}/messages/stream
  基于 asyncio.Queue + create_task 将 _send_message_core 桥接为
  text/event-stream 生成器，吐出 delta / reasoning / done / error 事件
- app/api/chat_service.py: _send_message_core 增加 stream + on_event 参数；
  普通（无工具）聊天 round-0 主调用走 achat_complete(stream=True) 流式；
  done 事件携带 message_id / content / process_steps / used_skills /
  used_mcp / generating
- app/core/llm_client.py: 修复 _create_kwargs 硬编码 stream=False 的根因 bug
  （流式调用传 stream=True 导致 TypeError: multiple values for keyword），
  现 _create_kwargs(request_body, stream=True) 字段随参数变化
- frontend/src/pages/front/ChatPage.tsx + ChatPage.css + types/index.ts:
  发消息改为 fetch SSE 消费，实时增量渲染 AI 回复文本与思考链(reasoning)，
  done 事件用 message_id 定稿并渲染过程步骤；网络/流式失败自动回退非流式

Alignment performed 2026-07-24 16:28:19. No deletions; secrets/venv/node_modules/
caches were not touched (tracked-source-only copy).

backend/python/app/core/llm_client.py

@@ -45,11 +45,11 @@ def build_openai_client(api_url, api_key, *, proxy=None, timeout=120) -> AsyncOp
     )
 
 
-def _create_kwargs(request_body: dict) -> dict:
+def _create_kwargs(request_body: dict, stream: bool = False) -> dict:
     kw = {
         "model": request_body.get("model"),
         "messages": request_body.get("messages", []),
-        "stream": False,
+        "stream": stream,
     }
     if request_body.get("temperature") is not None:
         kw["temperature"] = request_body["temperature"]
@@ -92,7 +92,7 @@ async def achat_complete(api_url, api_key, request_body, *, proxy=None, timeout=
             client = build_openai_client(api_url, api_key, proxy=proxy, timeout=timeout)
             try:
                 gen = await client.chat.completions.create(
-                    **_create_kwargs(request_body), stream=True
+                    **_create_kwargs(request_body, stream=True)
                 )
                 async for chunk in gen:
                     if not chunk.choices:
@@ -179,3 +179,4 @@ def embed(api_url, api_key, input, model, *, proxy=None, timeout=60) -> list:
     with client:
         resp = client.embeddings.create(**_embed_kwargs(input, model))
         return [d.embedding for d in resp.data]
+

frontend/src/pages/front/ChatPage.css

@@ -1759,3 +1759,23 @@ html.dark .ai-sending-timeout {
 .ai-cancel-btn:hover {
   background: color-mix(in srgb, #e74c3c 15%, var(--color-bg-tertiary)) !important;
 }
+
+/* ===== Phase 0 SSE 流式：思考链实时渲染 ===== */
+/* 思考链文本保留模型原始换行（deepseek 原生 reasoning 含多段换行） */
+.ai-process-thinking .ai-process-text {
+  white-space: pre-wrap;
+}
+
+/* 流式生成中提示 */
+.streaming-hint {
+  display: inline-flex;
+  align-items: center;
+  gap: 8px;
+  color: var(--color-text-secondary);
+  font-size: 14px;
+}
+
+.streaming-hint svg {
+  width: 16px;
+  height: 16px;
+}

frontend/src/pages/front/ChatPage.tsx

@@ -559,6 +559,8 @@ const ChatPage: React.FC = () => {
   const [sending, setSending] = useState(false);
   const [sendingTimeout, setSendingTimeout] = useState(false);
   const sendingTimerRef = useRef<ReturnType<typeof setTimeout> | null>(null);
+  // 正在 SSE 流式渲染的助手消息 id；非空时隐藏"思考中"占位气泡
+  const [streamingId, setStreamingId] = useState<string | null>(null);
   const [conversations, setConversations] = useState<Conversation[]>([]);
   const [messages, setMessages] = useState<Message[]>([]);
   const [loadingConversations, setLoadingConversations] = useState(true);
@@ -933,43 +935,12 @@ const ChatPage: React.FC = () => {
     }
   };
 
-  // Handle send message - CALLS REAL API
+  // 非流式兜底发送（与历史行为一致）——供 SSE 连接/流式失败时回退
-  // 抽出公共发送逻辑，供输入框发送与「模糊创作意图」方向选择复用
+  const sendLegacy = async (
-  const sendText = async (content: string) => {
+    payload: any,
-    if (!content.trim() || sending || !selectedConversation) return;
+    tempUserMsg: Message,
-    setSending(true);
+  ) => {
-    setSendingTimeout(false);
+    const res = await chatAPI.sendMessage(selectedConversation!.id, payload);
-    // 60s 超时警告
-    if (sendingTimerRef.current) clearTimeout(sendingTimerRef.current);
-    sendingTimerRef.current = setTimeout(() => {
-      setSendingTimeout(true);
-    }, 60000);
-
-    // Add user message optimistically
-    const tempUserMsg: Message = {
-      id: `temp_${Date.now()}`,
-      conversationId: selectedConversation?.id || '',
-      role: 'user',
-      content,
-      tokenUsed: 0,
-      createdAt: new Date().toISOString(),
-    };
-    setMessages(prev => [...prev, tempUserMsg]);
-
-    try {
-      const res = await chatAPI.sendMessage(selectedConversation!.id, {
-        content,
-        model_id: selectedModelId || undefined,
-        agent_ids: selectedAgentIds.length > 0 ? selectedAgentIds : undefined,
-        skill_ids: selectedSkillIds.length > 0 ? selectedSkillIds : undefined,
-        knowledge_base_ids: selectedKbIds.length > 0 ? selectedKbIds : undefined,
-        mcp_ids: selectedMcpIds.length > 0 ? selectedMcpIds : undefined,
-        attachments: attachments.length > 0 ? attachments.map(a => ({
-          name: a.name, file_type: a.file_type, content: a.content || '',
-        })) : undefined,
-        use_tools: selectedSkillIds.length > 0 || selectedAgentIds.length > 0 || selectedMcpIds.length > 0,
-      });
-
     const data = unwrapData(res);
 
     // Replace temporary user message and add assistant response
@@ -1028,11 +999,158 @@ const ChatPage: React.FC = () => {
         messages: recentMsgs,
       }).catch(() => {});
     }
+  };
+
+  // SSE 流式发送（Phase 0）——实时增量渲染 AI 回复文本与思考链(reasoning)
+  const streamSend = async (
+    convId: string,
+    payload: any,
+    tempUserMsg: Message,
+    assistantId: string,
+  ): Promise<void> => {
+    const token = localStorage.getItem('aiflow_token');
+    const resp = await fetch(`/app/api/chat/conversations/${convId}/messages/stream`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+        ...(token ? { Authorization: `Bearer ${token}` } : {}),
+      },
+      body: JSON.stringify(payload),
+    });
+    if (!resp.ok || !resp.body) {
+      throw new Error(`SSE 连接失败 (${resp.status})`);
+    }
+
+    const reader = resp.body.getReader();
+    const decoder = new TextDecoder();
+    let buffer = '';
+    let accReasoning = '';
+    let gotDone = false;
+
+    const patchAssistant = (patch: Partial<Message>) => {
+      setMessages(prev => prev.map(m => (m.id === assistantId ? { ...m, ...patch } : m)));
+    };
+
+    while (true) {
+      const { value, done } = await reader.read();
+      if (done) break;
+      buffer += decoder.decode(value, { stream: true });
+      let sep: number;
+      while ((sep = buffer.indexOf('\n\n')) >= 0) {
+        const raw = buffer.slice(0, sep);
+        buffer = buffer.slice(sep + 2);
+        const dataLine = raw.split('\n').find(l => l.startsWith('data: '));
+        if (!dataLine) continue;
+        let evt: any;
+        try { evt = JSON.parse(dataLine.slice(6)); } catch { continue; }
+        if (evt.type === 'delta') {
+          const piece = evt.content || '';
+          setMessages(prev => prev.map(m => (m.id === assistantId ? { ...m, content: (m.content || '') + piece } : m)));
+        } else if (evt.type === 'reasoning') {
+          accReasoning += evt.content || '';
+          patchAssistant({ reasoning: accReasoning } as any);
+        } else if (evt.type === 'done') {
+          gotDone = true;
+          const finalId = evt.message_id || assistantId;
+          setMessages(prev => prev.map(m => {
+            if (m.id !== assistantId) return m;
+            return {
+              ...m,
+              id: finalId,
+              content: evt.content ?? m.content,
+              process_steps: evt.process_steps || [],
+              used_skills: evt.used_skills || [],
+              used_mcp: evt.used_mcp || [],
+              generating: !!evt.generating,
+            };
+          }));
+          setStreamingId(null);
+          if (evt.generating) startMediaPolling(convId, finalId);
+          setFreshMsgIds(prev => new Set(prev).add(finalId));
+          loadConversations();
+          setAttachments([]);
+          if (convId && evt.content) {
+            evolutionAPI.submitTrajectory({
+              conversation_id: convId,
+              messages: [
+                { role: 'user', content: tempUserMsg.content, tokens: 0 },
+                { role: 'assistant', content: evt.content, tokens: 0 },
+              ],
+            }).catch(() => {});
+          }
+        } else if (evt.type === 'error') {
+          throw new Error(evt.message || '生成失败');
+        }
+      }
+    }
+    if (!gotDone) {
+      // 流结束但未收到 done：已累积的 delta 仍可展示，但视为异常兜底
+      setStreamingId(null);
+      throw new Error('流式响应未正常结束');
+    }
+  };
+
+  // Handle send message - CALLS REAL API（Phase 0：默认 SSE 流式，失败回退非流式）
+  // 抽出公共发送逻辑，供输入框发送与「模糊创作意图」方向选择复用
+  const sendText = async (content: string) => {
+    if (!content.trim() || sending || !selectedConversation) return;
+    setSending(true);
+    setSendingTimeout(false);
+    // 60s 超时警告
+    if (sendingTimerRef.current) clearTimeout(sendingTimerRef.current);
+    sendingTimerRef.current = setTimeout(() => {
+      setSendingTimeout(true);
+    }, 60000);
+
+    // Add user message optimistically
+    const tempUserMsg: Message = {
+      id: `temp_${Date.now()}`,
+      conversationId: selectedConversation?.id || '',
+      role: 'user',
+      content,
+      tokenUsed: 0,
+      createdAt: new Date().toISOString(),
+    };
+    setMessages(prev => [...prev, tempUserMsg]);
+
+    const payload = {
+      content,
+      model_id: selectedModelId || undefined,
+      agent_ids: selectedAgentIds.length > 0 ? selectedAgentIds : undefined,
+      skill_ids: selectedSkillIds.length > 0 ? selectedSkillIds : undefined,
+      knowledge_base_ids: selectedKbIds.length > 0 ? selectedKbIds : undefined,
+      mcp_ids: selectedMcpIds.length > 0 ? selectedMcpIds : undefined,
+      attachments: attachments.length > 0 ? attachments.map(a => ({
+        name: a.name, file_type: a.file_type, content: a.content || '',
+      })) : undefined,
+      use_tools: selectedSkillIds.length > 0 || selectedAgentIds.length > 0 || selectedMcpIds.length > 0,
+    };
+
+    // 先放一个空的助手消息占位，用于 SSE 流式增量渲染
+    const assistantId = `temp_assistant_${Date.now()}`;
+    setMessages(prev => [...prev, {
+      id: assistantId,
+      conversationId: selectedConversation!.id,
+      role: 'assistant',
+      content: '',
+      tokenUsed: 0,
+      createdAt: new Date().toISOString(),
+      reasoning: '',
+    } as Message]);
+    setStreamingId(assistantId);
+
+    try {
+      await streamSend(selectedConversation!.id, payload, tempUserMsg, assistantId);
     } catch (err: any) {
-      if (sendingTimerRef.current) { clearTimeout(sendingTimerRef.current); sendingTimerRef.current = null; }
+      // 移除流式占位，回退非流式重新发送
-      // Remove optimistic message on error
+      setMessages(prev => prev.filter(m => m.id !== assistantId && m.id !== tempUserMsg.id));
+      setStreamingId(null);
+      try {
+        await sendLegacy(payload, tempUserMsg);
+      } catch (e2: any) {
         setMessages(prev => prev.filter(m => m.id !== tempUserMsg.id));
-      alert('发送失败: ' + (err.message || err.detail || '未知错误'));
+        alert('发送失败: ' + (e2?.message || e2?.detail || '未知错误'));
+      }
     } finally {
       if (sendingTimerRef.current) { clearTimeout(sendingTimerRef.current); sendingTimerRef.current = null; }
       setSending(false);
@@ -1286,6 +1404,22 @@ const ChatPage: React.FC = () => {
                   {msg.role === 'assistant' && steps.length > 0 && (
                     <AiProcessBlock steps={steps} autoExpand={freshMsgIds.has(msg.id)} />
                   )}
+                  {msg.role === 'assistant' && (msg as any).reasoning && (
+                    <details className="ai-process ai-process-reasoning" open>
+                      <summary className="ai-process-summary">
+                        <span className="ai-process-badge">🤔</span>
+                        AI 思考过程（实时）
+                      </summary>
+                      <div className="ai-process-list">
+                        <div className="ai-process-item ai-process-thinking">
+                          <span className="ai-process-ico">💡</span>
+                          <div className="ai-process-body">
+                            <p className="ai-process-text">{(msg as any).reasoning}</p>
+                          </div>
+                        </div>
+                      </div>
+                    </details>
+                  )}
                   <div className={`message-bubble ${msg.role}`}>
                     {clarify ? (
                       <ClarifyCard
@@ -1306,7 +1440,7 @@ const ChatPage: React.FC = () => {
                         }}>🔄 重试</button>
                       </div>
                     ) : msg.role === 'assistant' ? (
-                      <MarkdownContent content={msg.content} />
+                      msg.content ? <MarkdownContent content={msg.content} /> : (streamingId === msg.id ? <span className="streaming-hint"><IconSpinner /> 生成中…</span> : null)
                     ) : (
                       <span>{msg.content}</span>
                     )}
@@ -1370,7 +1504,7 @@ const ChatPage: React.FC = () => {
                   );
                 })
               )}
-              {sending && (
+              {sending && !streamingId && (
                 <div className="message-row assistant">
                   <div className={`message-bubble assistant${sendingTimeout ? ' ai-sending-timeout' : ''}`} style={{ display: 'flex', alignItems: 'center', gap: 8 }}>
                     <IconSpinner />

frontend/src/types/index.ts

@@ -60,6 +60,7 @@ export interface Message {
   content: string;
   tokenUsed: number;
   createdAt: string;
+  reasoning?: string;
   used_skills?: string[];
   used_mcp?: string[];
   process_steps?: Array<{