feat(audio): 修复说话人聚类并更新至0.4.0-alpha.1

.gitea/workflows/windows-rc.yml

@@ -68,6 +68,7 @@ jobs:
             bundle = @{
               active = $true
               targets = @('nsis')
+              icon = @('icons/icon.png', 'icons/icon.ico')
               resources = @{
                 '../../.build/sidecar/dist/opennexus-core/' = 'core/'
               }
@@ -75,6 +76,10 @@ jobs:
                 certificateThumbprint = $env:OPENNEXUS_WINDOWS_CERTIFICATE_THUMBPRINT
                 digestAlgorithm = 'sha256'
                 timestampUrl = 'http://timestamp.digicert.com'
+                nsis = @{
+                  installerIcon = 'icons/icon.ico'
+                  uninstallerIcon = 'icons/icon.ico'
+                }
               }
             }
           } | ConvertTo-Json -Depth 5

README.md

@@ -2,7 +2,7 @@
 
 OpenNexus 是一款本地优先的 AI 笔记与知识中枢。它将 Markdown Vault、全文与向量检索、知识库问答、可审计 Agent、扩展系统和多设备同步整合在一个桌面应用中。笔记与索引由用户掌控；需要模型或同步服务时，再按需连接本地或远程服务。
 
-当前发布版本为 **0.3.1-alpha.3**，主要支持 Windows x64。Alpha 版本仍处于快速迭代阶段，升级前请备份 Vault。
+当前发布版本为 **0.4.0-alpha.1**，主要支持 Windows x64。Alpha 版本仍处于快速迭代阶段，升级前请备份 Vault。
 
 ## 主要能力
 
@@ -34,7 +34,7 @@ flowchart LR
 
 ## 使用发布包
 
-本版提供 Windows x64 EXE 安装包和独立的 Server Sync 包，下载入口见 [v0.3.1-alpha.3 发布页](https://gitea.kronecker.cc/Kronecker/NotesAgentic/releases/tag/v0.3.1-alpha.3)。发布页同时附带 `SHA256.json`，用于核对文件完整性。
+本版提供 Windows x64 EXE 安装包和独立的 Server Sync 包，下载入口见 [v0.4.0-alpha.1 发布页](https://gitea.kronecker.cc/Kronecker/NotesAgentic/releases/tag/v0.4.0-alpha.1)。发布页同时附带 `SHA256.json`，用于核对文件完整性。
 
 安装包不包含任何 Vault 或用户数据，也不预装已下载的社区主题、本地模型权重、CUDA 与 PyTorch 运行时。相关功能仍完整保留；需要时可在客户端内按需安装主题、选择模型或配置 CUDA 环境。程序自带的基础界面样式属于客户端资源，不视为社区主题。同一 Windows 用户下升级安装会继续使用 `%APPDATA%\cc.kronecker.notesagent` 中的既有配置和索引，以及用户此前选择的外部 Vault。
 

backend/app/local_models/worker.py

@@ -115,6 +115,91 @@ def voice_embedding(model, audio, device):
         return torch.nn.functional.normalize(vector, dim=0)
 
 
+def _normalized_vector(values):
+    """把声纹向量转成普通列表并归一化，便于在无 PyTorch 的 API 测试环境中验证聚类。"""
+    import math
+    values = [float(value) for value in values]
+    norm = math.sqrt(sum(value * value for value in values))
+    if not values or not math.isfinite(norm) or norm <= 1e-12:
+        raise ValueError("Invalid speaker embedding")
+    return [value / norm for value in values]
+
+
+def _similarity(left, right):
+    return sum(a * b for a, b in zip(left, right, strict=True))
+
+
+def cluster_speaker_embeddings(embeddings, segments, *, threshold=0.36):
+    """聚类片段声纹，并把过短片段交给相邻的稳定说话人。
+
+    质心在每次接收新样本后更新，避免第一段永久决定整簇。持续时间不超过
+    3 秒的孤立单例通常是停顿处的语气词；将它并入最相近的已有稳定簇，
+    同时保留由多个片段支持的第三位及更多说话人。
+    """
+    if len(embeddings) != len(segments):
+        raise ValueError("Speaker embeddings and segments must have the same length")
+    vectors = [None if value is None else _normalized_vector(value) for value in embeddings]
+    assignments = [None] * len(vectors)
+    clusters = []
+    for index, vector in enumerate(vectors):
+        if vector is None:
+            continue
+        similarities = [_similarity(vector, cluster["centroid"]) for cluster in clusters]
+        best = max(range(len(similarities)), key=similarities.__getitem__) if similarities else None
+        if best is None or similarities[best] < threshold:
+            best = len(clusters)
+            clusters.append({"members": [], "sum": [0.0] * len(vector), "centroid": vector})
+        cluster = clusters[best]
+        cluster["members"].append(index)
+        cluster["sum"] = [total + value for total, value in zip(cluster["sum"], vector, strict=True)]
+        cluster["centroid"] = _normalized_vector(cluster["sum"])
+        assignments[index] = best
+
+    # 短语气词可能形成只有一个片段的离群簇。仅合并短单例，不吞掉由多个
+    # 片段支持的真实少数说话人。
+    stable = [index for index, cluster in enumerate(clusters) if len(cluster["members"]) > 1]
+    for index, cluster in enumerate(clusters):
+        member = cluster["members"][0] if len(cluster["members"]) == 1 else None
+        if member is None or not stable:
+            continue
+        duration = float(segments[member]["end_time"]) - float(segments[member]["start_time"])
+        if duration > 3.0:
+            continue
+        target = max(stable, key=lambda other: _similarity(cluster["centroid"], clusters[other]["centroid"]))
+        assignments[member] = target
+
+    # 没有足够语音生成声纹的短片段继承时间上最近的稳定标签。同一说话人
+    # 两个片段之间的语气词会优先落回该说话人。
+    labeled = [index for index, value in enumerate(assignments) if value is not None]
+    for index, value in enumerate(assignments):
+        if value is not None or not labeled:
+            continue
+        previous = next((item for item in reversed(labeled) if item < index), None)
+        following = next((item for item in labeled if item > index), None)
+        if previous is not None and following is not None and assignments[previous] == assignments[following]:
+            assignments[index] = assignments[previous]
+            continue
+        candidates = []
+        if previous is not None:
+            distance = max(0.0, float(segments[index]["start_time"]) - float(segments[previous]["end_time"]))
+            candidates.append((distance, 0, assignments[previous]))
+        if following is not None:
+            distance = max(0.0, float(segments[following]["start_time"]) - float(segments[index]["end_time"]))
+            candidates.append((distance, 1, assignments[following]))
+        assignments[index] = min(candidates)[2] if candidates else None
+
+    # 合并后按首次出现顺序重新编号，避免 speaker_1、speaker_3 这样的空洞 ID。
+    remap = {}
+    speakers = []
+    for value in assignments:
+        if value is None:
+            speakers.append(None)
+            continue
+        remap.setdefault(value, len(remap) + 1)
+        speakers.append(f"speaker_{remap[value]}")
+    return speakers
+
+
 class CudaInitializationError(RuntimeError):
     pass
 
@@ -189,20 +274,15 @@ def run(request):
             model = speaker_model(path, device)
             loaded = time.monotonic()
             audio = decode(payload["source"])
-            centroids, speakers = [], []
+            embeddings = []
             for segment in payload["segments"]:
                 sample = audio[int(segment["start_time"] * 16000):int(segment["end_time"] * 16000)]
                 if len(sample) < 16000:
-                    speakers.append(None)
+                    embeddings.append(None)
                     continue
-                vector = voice_embedding(model, sample, device)
-                similarities = [float(torch.dot(vector, c)) for c in centroids]
-                best = max(range(len(similarities)), key=similarities.__getitem__) if similarities else None
-                if best is None or similarities[best] < 0.36:
-                    best = len(centroids)
-                    centroids.append(vector)
-                speakers.append(f"speaker_{best + 1}")
-            result = {"speakers": speakers}
+                embeddings.append(voice_embedding(model, sample, device).tolist())
+            speakers = cluster_speaker_embeddings(embeddings, payload["segments"])
+            result = {"speakers": speakers, "unassigned_segments": sum(speaker is None for speaker in speakers)}
         else:
             raise ValueError("Unknown inference operation")
         return {"result": result, "usage": usage, "audio_seconds": audio_seconds, "diagnostics": {"requested_device": requested, "actual_device": device,

backend/app/services/transcription_service.py

@@ -174,6 +174,8 @@ async def _execute(job_id, request, routing=None):
                     for segment, speaker in zip(job.segments, result["speakers"], strict=True):
                         segment.speaker = speaker
                     job.warnings.append("DIARIZATION_SEGMENT_LEVEL")
+                    if result.get("unassigned_segments"):
+                        job.warnings.append("DIARIZATION_PARTIAL")
                 except ProviderError:
                     job.warnings.append("DIARIZATION_UNAVAILABLE")
             else:

backend/tests/test_speaker_clustering.py

@@ -0,0 +1,38 @@
+from app.local_models.worker import cluster_speaker_embeddings
+
+
+def segment(start, end):
+    return {"start_time": start, "end_time": end}
+
+
+def test_centroid_updates_allow_one_speaker_to_drift():
+    speakers = cluster_speaker_embeddings(
+        [[1, 0], [0.8, 0.6], [0.55, 0.835]],
+        [segment(0, 2), segment(2, 4), segment(4, 6)],
+        threshold=0.7,
+    )
+    assert speakers == ["speaker_1"] * 3
+
+
+def test_short_segments_and_short_singleton_join_stable_neighbors():
+    speakers = cluster_speaker_embeddings(
+        [[1, 0], None, [0.98, 0.1], [0, 1], [-0.9, -0.1], [0.1, 0.99]],
+        [segment(0, 2), segment(2, 2.4), segment(2.4, 5), segment(5, 8), segment(8, 9.5), segment(9.5, 12)],
+    )
+    assert speakers[0] == speakers[1] == speakers[2] == "speaker_1"
+    assert speakers[3] == speakers[4] == speakers[5] == "speaker_2"
+    assert None not in speakers
+
+
+def test_multiple_supported_speakers_are_not_collapsed():
+    speakers = cluster_speaker_embeddings(
+        [[1, 0, 0], [0.99, 0.05, 0], [0, 1, 0], [0.05, 0.99, 0], [0, 0, 1], [0, 0.05, 0.99]],
+        [segment(i * 2, i * 2 + 2) for i in range(6)],
+    )
+    assert speakers == ["speaker_1", "speaker_1", "speaker_2", "speaker_2", "speaker_3", "speaker_3"]
+
+
+def test_all_too_short_remains_unassigned_without_model_evidence():
+    assert cluster_speaker_embeddings(
+        [None, None], [segment(0, 0.4), segment(0.5, 0.9)]
+    ) == [None, None]

docs/development/多模态管线与模型运行开发说明.md

@@ -53,7 +53,7 @@ API 保留 `backend/.venv`，模型依赖安装到独立的 `backend/.venv-model
 
 API 优先，无配置或无效结果时本地回退。local_only 禁止远程模型。纯文本附件和既有 sidecar 可导入，但已有真实音频时不使用旁边文本冒充识别。
 
-PyAV 提取音轨至 16 kHz 单声道，最长 1 小时，禁止解码器网络协议。能量分段后交给 Qwen3-ASR，返回片段边界，不宣称逐字对齐。ERes2NetV2 提取片段声纹并按相似度聚类；短片段、同段多人、重叠发言需要人工校对。缺失能力返回 DIARIZATION_UNAVAILABLE；未启用逐字对齐返回 WORD_TIMESTAMPS_UNAVAILABLE。
+PyAV 提取音轨至 16 kHz 单声道，最长 1 小时，禁止解码器网络协议。能量分段后交给 Qwen3-ASR，返回片段边界，不宣称逐字对齐。ERes2NetV2 提取片段声纹并按更新后的簇质心聚类；不足 1 秒的片段继承时间上最近的稳定说话人，3 秒以内且没有其他片段支持的离群簇并入最相近的稳定簇。由多个片段支持的少数说话人仍会保留。同段多人和重叠发言需要人工校对；仍无法分配的片段返回 DIARIZATION_PARTIAL。缺失能力返回 DIARIZATION_UNAVAILABLE；未启用逐字对齐返回 WORD_TIMESTAMPS_UNAVAILABLE。
 
 术语是识别后的替换规则，保留原始文本和来源。重命名只修改显示名，稳定 ID 不变。笔记包含音频与时间跳转链接；重复导出不覆盖用户编辑。清理保留已导出笔记，音频链接失效，已清理任务不可重试。重建索引保留转写与笔记关联。
 

frontend/index.html

@@ -4,6 +4,7 @@
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <meta name="theme-color" content="#171717" />
+    <link rel="icon" type="image/svg+xml" href="/opennexus-logo.svg" />
     <title>OpenNexus</title>
   </head>
   <body>

frontend/package.json

@@ -1,7 +1,7 @@
 {
   "name": "notes-agent-frontend",
   "private": true,
-  "version": "0.3.1-alpha.3",
+  "version": "0.4.0-alpha.1",
   "type": "module",
   "scripts": {
     "dev": "vite",

frontend/public/opennexus-logo.svg

@@ -0,0 +1,8 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1024 1024" role="img" aria-labelledby="title desc">
+  <title id="title">OpenNexus</title>
+  <desc id="desc">蓝紫色线框文档标志</desc>
+  <rect x="12" y="12" width="1000" height="1000" rx="252" fill="#fbfcff" stroke="#e1e5f0" stroke-width="24"/>
+  <path d="M254 184h322l194 194v462H254z" fill="none" stroke="#6269f6" stroke-width="48" stroke-linejoin="round"/>
+  <path d="M576 184v194h194" fill="none" stroke="#6269f6" stroke-width="48" stroke-linejoin="round"/>
+  <path d="M382 508h260M382 622h260M382 736h260" fill="none" stroke="#6269f6" stroke-width="42" stroke-linecap="round"/>
+</svg>

frontend/src-tauri/Cargo.lock

@@ -3242,7 +3242,7 @@ dependencies = [
 
 [[package]]
 name = "notesagent-desktop"
-version = "0.3.1-alpha.3"
+version = "0.4.0-alpha.1"
 dependencies = [
  "argon2",
  "base64 0.22.1",

frontend/src-tauri/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "notesagent-desktop"
-version = "0.3.1-alpha.3"
+version = "0.4.0-alpha.1"
 edition = "2021"
 rust-version = "1.89"
 

frontend/src-tauri/tauri.bundle.conf.json

@@ -8,6 +8,7 @@
     "publisher": "Kronecker",
     "homepage": "https://gitea.kronecker.cc/Kronecker/NotesAgentic",
     "icon": [
+      "icons/icon.png",
       "icons/icon.ico"
     ],
     "resources": {

frontend/src-tauri/tauri.conf.json

@@ -1,7 +1,7 @@
 {
   "$schema": "https://schema.tauri.app/config/2",
   "productName": "OpenNexus",
-  "version": "0.3.1-alpha.3",
+  "version": "0.4.0-alpha.1",
   "identifier": "cc.kronecker.notesagent",
   "build": {
     "beforeDevCommand": "pnpm dev",
@@ -30,6 +30,10 @@
     }
   },
   "bundle": {
-    "active": false
+    "active": false,
+    "icon": [
+      "icons/icon.png",
+      "icons/icon.ico"
+    ]
   }
 }

frontend/src/assets/opennexus-logo.svg

@@ -0,0 +1,8 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1024 1024" role="img" aria-labelledby="title desc">
+  <title id="title">OpenNexus</title>
+  <desc id="desc">蓝紫色线框文档标志</desc>
+  <rect x="12" y="12" width="1000" height="1000" rx="252" fill="#fbfcff" stroke="#e1e5f0" stroke-width="24"/>
+  <path d="M254 184h322l194 194v462H254z" fill="none" stroke="#6269f6" stroke-width="48" stroke-linejoin="round"/>
+  <path d="M576 184v194h194" fill="none" stroke="#6269f6" stroke-width="48" stroke-linejoin="round"/>
+  <path d="M382 508h260M382 622h260M382 736h260" fill="none" stroke="#6269f6" stroke-width="42" stroke-linecap="round"/>
+</svg>

frontend/src/components/common/TitleBar.vue

@@ -6,6 +6,7 @@ import { useEditorStore } from '@/stores/editor'
 import { useThemeStore } from '@/stores/theme'
 import { Moon, Sunny } from '@element-plus/icons-vue'
 import AppIcon from './AppIcon.vue'
+import appLogoUrl from '@/assets/opennexus-logo.svg'
 import { t } from '@/i18n'
 import { isDesktop } from '@/services/platform/desktop'
 import { minimizeWindow, requestWindowClose, toggleMaximizeWindow } from '@/services/platform/windowControls'
@@ -63,7 +64,7 @@ function toggleFromTitlebar(event: MouseEvent) {
       </span>
     </div>
     <div class="titlebar-center" data-tauri-drag-region>
-      <span class="app-name" data-tauri-drag-region>OpenNexus</span>
+      <span class="app-name" data-tauri-drag-region><img :src="appLogoUrl" alt="" />OpenNexus</span>
     </div>
     <div class="titlebar-right">
       <button class="icon-btn" @click="themeStore.toggleTheme()" :title="themeStore.isDark ? t('切换浅色主题', 'Switch to light theme') : t('切换深色主题', 'Switch to dark theme')">
@@ -142,6 +143,9 @@ function toggleFromTitlebar(event: MouseEvent) {
 }
 
 .app-name {
+  display: inline-flex;
+  align-items: center;
+  gap: 6px;
   padding: 3px 10px;
   border: 1px solid var(--color-border-subtle);
   border-radius: var(--radius-full);
@@ -151,6 +155,11 @@ function toggleFromTitlebar(event: MouseEvent) {
   letter-spacing: .04em;
 }
 
+.app-name img {
+  width: 18px;
+  height: 18px;
+}
+
 .titlebar-right {
   display: flex;
   align-items: center;

frontend/src/features/media/MediaView.vue

@@ -58,6 +58,7 @@ const warningLabel = (warning: string) => warning.startsWith('MEDIA_CORRUPT_PACK
   ? t(`已跳过 ${warning.split(':')[1]} 个损坏音频包；缺失时长以静音保留，请校对受影响内容。`, `Skipped ${warning.split(':')[1]} damaged audio packets; missing duration was retained as silence. Review the affected content.`)
   : ({
   DIARIZATION_UNAVAILABLE: t('当前无法分离说话人', 'Speaker identification is unavailable'),
+  DIARIZATION_PARTIAL: t('部分片段没有足够语音用于说话人识别，请人工校对', 'Some segments do not contain enough speech for speaker identification; review them manually'),
   WORD_TIMESTAMPS_UNAVAILABLE: t('未提供逐字时间戳', 'Word-level timestamps are unavailable'),
   DIARIZATION_SEGMENT_LEVEL: t('说话人按音频段估计，同段多人或重叠发言需人工校对', 'Speakers are estimated per segment; multiple or overlapping speakers require manual correction'),
 } as Record<string, string>)[warning] || warning

frontend/src/features/vault/VaultEntry.vue

@@ -4,8 +4,9 @@ import { useRouter } from 'vue-router'
 import { useWorkspaceStore } from '@/stores/workspace'
 import { useThemeStore } from '@/stores/theme'
 import { useSettingsStore } from '@/stores/settings'
-import { ArrowRight, Document, Folder, FolderOpened, Moon, Sunny } from '@element-plus/icons-vue'
+import { ArrowRight, Folder, FolderOpened, Moon, Sunny } from '@element-plus/icons-vue'
 import AppIcon from '@/components/common/AppIcon.vue'
+import appLogoUrl from '@/assets/opennexus-logo.svg'
 import { t } from '@/i18n'
 import { ApiErrorClass } from '@/services/apiClient'
 import { isDesktop } from '@/services/platform/desktop'
@@ -62,7 +63,7 @@ async function openFolderPicker() {
     <div class="bg-decoration" />
     <div class="entry-container">
       <div class="brand-section">
-        <div class="logo"><AppIcon :icon="Document" :size="56" /></div>
+        <div class="logo"><img :src="appLogoUrl" alt="" /></div>
         <h1 class="app-title">OpenNexus</h1>
         <p class="app-subtitle">{{ t('本地优先的 AI 笔记软件', 'A local-first AI note-taking app') }}</p>
       </div>
@@ -109,7 +110,7 @@ async function openFolderPicker() {
       </div>
 
       <div class="footer-info">
-        <span>v0.1.0</span>
+        <span>v0.4.0-alpha.1</span>
         <button class="theme-toggle" @click="themeStore.toggleTheme()">
           <AppIcon :icon="themeStore.isDark ? Sunny : Moon" :size="15" />
           {{ themeStore.isDark ? t('浅色', 'Light') : t('深色', 'Dark') }}
@@ -164,13 +165,15 @@ async function openFolderPicker() {
   width: 84px;
   height: 84px;
   margin-bottom: 14px;
-  border: 1px solid color-mix(in srgb, var(--color-accent-primary) 18%, transparent);
-  border-radius: 24px;
-  background: var(--color-surface-primary);
-  color: var(--color-accent-primary);
   box-shadow: var(--shadow-lg);
 }
 
+.logo img {
+  display: block;
+  width: 84px;
+  height: 84px;
+}
+
 .app-title {
   font-size: 32px;
   font-weight: 700;

frontend/src/services/themeImport.spec.ts

@@ -6,7 +6,7 @@ import paper from '@/assets/themes/paper-moments.theme?raw'
 
 afterEach(() => vi.unstubAllGlobals())
 it('uses the desktop release version for compatibility checks', () => {
-  expect(THEME_APP_VERSION).toBe('0.3.1-alpha.2')
+  expect(THEME_APP_VERSION).toBe('0.4.0-alpha.1')
 })
 it.each(['999.0.0', 'bad', '0.2'])('rejects unsupported minimum app version %s at inspection and install', async version => {
   const source = paper.replace(/min_app_version:.*\r?\n/, `min_app_version: ${version}\n`)

server sync/Dockerfile

@@ -7,7 +7,7 @@ COPY console ./
 RUN pnpm build
 
 FROM python:3.12-slim
-ARG OPENNEXUS_SYNC_VERSION=0.3.1-alpha.3
+ARG OPENNEXUS_SYNC_VERSION=0.4.0-alpha.1
 LABEL org.opencontainers.image.title="OpenNexus Server Sync" \
       org.opencontainers.image.version="${OPENNEXUS_SYNC_VERSION}" \
       org.opencontainers.image.source="https://gitea.kronecker.cc/Kronecker/NotesAgentic"

server sync/README.md

@@ -1,6 +1,6 @@
 # OpenNexus Server Sync
 
-当前发布版本为 **0.3.1-alpha.3**。协议及限制见 [Sync v1](../docs/contracts/Sync-v1契约.md)。服务独立于 AI Core，生产入口仅支持 PostgreSQL 和 S3 兼容对象存储。独立发布包包含服务源码、锁文件、Vue 3 + TypeScript 管理控制台静态文件、Dockerfile 与 Compose 模板，不包含任何 Vault、账户数据库、对象存储数据或部署密钥。
+当前发布版本为 **0.4.0-alpha.1**。协议及限制见 [Sync v1](../docs/contracts/Sync-v1契约.md)。服务独立于 AI Core，生产入口仅支持 PostgreSQL 和 S3 兼容对象存储。独立发布包包含服务源码、锁文件、Vue 3 + TypeScript 管理控制台静态文件、Dockerfile 与 Compose 模板，不包含任何 Vault、账户数据库、对象存储数据或部署密钥。
 
 服务根路径 `/` 与 `/console/` 提供同源的 Vue 3 + TypeScript Sync Console，可查看服务健康与依赖就绪状态，并使用普通 Sync 账户管理自己的 Vault 和设备。页面只调用公开的 Sync v1 API；密码在请求发出前从输入框清除，访问和刷新令牌只保留在页面内存，刷新或关闭页面即丢弃。控制台源码位于 `console/`，生产静态文件由 Docker 多阶段构建生成。
 
@@ -22,13 +22,13 @@ uv run pytest
 
 ## 自托管准备
 
-从发布页下载 `OpenNexus-Server-Sync-0.3.1-alpha.3.zip` 并核对 `SHA256.json` 后，将压缩包解压到独立目录。升级现有实例时先备份数据库、对象存储和 `.env`，再使用新版镜像替换 Sync 服务；不要用发行包覆盖持久化卷。
+从发布页下载 `OpenNexus-Server-Sync-0.4.0-alpha.1.zip` 并核对 `SHA256.json` 后，将压缩包解压到独立目录。升级现有实例时先备份数据库、对象存储和 `.env`，再使用新版镜像替换 Sync 服务；不要用发行包覆盖持久化卷。
 
 仓库提供以下 Docker 文件：
 
 - `Dockerfile`：构建 Vue 控制台和只读运行镜像。
 - `compose.yaml`：启动 PostgreSQL、MinIO、一次性初始化任务和 Sync 服务，默认只监听 `127.0.0.1:8080`。
-- `compose.test.yaml`：仅供隔离验收使用，将 Sync 暴露到 `0.0.0.0:18080` 并使用 MinIO 管理凭据。
+- `compose.test.yaml`：仅供隔离验收使用，将 Sync 通过 IPv4 与 IPv6 暴露到 `18080`，并使用 MinIO 管理凭据。
 - `.dockerignore`：排除密钥、数据库、Vault、测试缓存和本机依赖。
 
 ```powershell
@@ -57,7 +57,7 @@ docker compose run --rm sync /service/.venv/bin/python -m sync_server bootstrap-
 
 `initialize` 命令已通过真实 PostgreSQL/MinIO 的空实例与重复运行验证，并由 Compose 的一次性服务调用。MinIO 同步账号仍须由管理员创建并限制到 `opennexus` Bucket，`.env` 中的 root 与同步凭据必须不同。
 
-0.3.1-alpha.3 使用真实 PostgreSQL/MinIO 环境验证初始化、重复启动、固定凭据、健康检查和已有数据升级。测试专用 HTTP 地址、故障检查、完整验收记录与运维入口见[验收报告](../docs/development/OpenNexus验收报告-2026-09-08.md)。S-07 已在原生 PostgreSQL 17.11/MinIO 实例完成 1 GiB/10,000 文件的删除源实例与空实例恢复。测试阶段可以直接开放 HTTP 端口；生产上线仍需配置 TLS、访问控制、监控与异机备份。
+0.4.0-alpha.1 使用真实 PostgreSQL/MinIO 环境验证初始化、重复启动、固定凭据、健康检查和已有数据升级。测试专用 HTTP 地址、故障检查、完整验收记录与运维入口见[验收报告](../docs/development/OpenNexus验收报告-2026-09-08.md)。S-07 已在原生 PostgreSQL 17.11/MinIO 实例完成 1 GiB/10,000 文件的删除源实例与空实例恢复。测试阶段可以直接开放 HTTP 端口；生产上线仍需配置 TLS、访问控制、监控与异机备份。
 
 ## 备份与空实例恢复
 

server sync/compose.test.yaml

@@ -6,4 +6,5 @@ services:
       AWS_SECRET_ACCESS_KEY: ${MINIO_ROOT_PASSWORD:?required}
     ports: !override
       - "0.0.0.0:${SYNC_PORT:-18080}:8080"
+      - "[::]:${SYNC_PORT:-18080}:8080"
     restart: unless-stopped

server sync/compose.yaml

@@ -23,8 +23,8 @@ services:
     build:
       context: .
       args:
-        OPENNEXUS_SYNC_VERSION: ${OPENNEXUS_SYNC_TAG:-0.3.1-alpha.3}
-    image: opennexus-sync:${OPENNEXUS_SYNC_TAG:-0.3.1-alpha.3}
+        OPENNEXUS_SYNC_VERSION: ${OPENNEXUS_SYNC_TAG:-0.4.0-alpha.1}
+    image: opennexus-sync:${OPENNEXUS_SYNC_TAG:-0.4.0-alpha.1}
     command: ["/service/.venv/bin/python", "-m", "sync_server", "initialize"]
     environment:
       SYNC_DATABASE_URL: ${SYNC_DATABASE_URL:?required}
@@ -43,8 +43,8 @@ services:
     build:
       context: .
       args:
-        OPENNEXUS_SYNC_VERSION: ${OPENNEXUS_SYNC_TAG:-0.3.1-alpha.3}
-    image: opennexus-sync:${OPENNEXUS_SYNC_TAG:-0.3.1-alpha.3}
+        OPENNEXUS_SYNC_VERSION: ${OPENNEXUS_SYNC_TAG:-0.4.0-alpha.1}
+    image: opennexus-sync:${OPENNEXUS_SYNC_TAG:-0.4.0-alpha.1}
     environment:
       SYNC_DATABASE_URL: ${SYNC_DATABASE_URL:?required}
       SYNC_S3_ENDPOINT: http://objects:9000

server sync/console/package.json

@@ -1,7 +1,7 @@
 {
   "name": "opennexus-sync-console",
   "private": true,
-  "version": "0.3.1-alpha.3",
+  "version": "0.4.0-alpha.1",
   "packageManager": "pnpm@10.28.0",
   "type": "module",
   "scripts": {

server sync/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "notesagent-sync"
-version = "0.3.1a3"
+version = "0.4.0a1"
 requires-python = ">=3.12"
 dependencies = [
   "fastapi>=0.116,<1", "uvicorn>=0.35,<1", "sqlalchemy>=2.0,<2.1",

server sync/uv.lock

@@ -225,7 +225,7 @@ wheels = [
 
 [[package]]
 name = "notesagent-sync"
-version = "0.3.1a3"
+version = "0.4.0a1"
 source = { virtual = "." }
 dependencies = [
     { name = "boto3" },