release: OpenNexus 0.5.0

合并已完成验证的 Windows EXE 安装包和 Server Sync Docker 部署配置。

.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 **0.5.0**，主要支持 Windows x64。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 [v0.5.0 发布页](https://gitea.kronecker.cc/Kronecker/NotesAgentic/releases/tag/v0.5.0)。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/config.py

@@ -33,7 +33,7 @@ def get_settings() -> Settings:
     data_dir = Path(os.getenv("APP_DATA_DIR", str(BACKEND_DIR / "data")))
     return Settings(
         name=os.getenv("APP_NAME", "OpenNexus AI Core"),
-        version=os.getenv("APP_VERSION", "0.1.0"),
+        version=os.getenv("APP_VERSION", "0.5.0"),
         environment=os.getenv("APP_ENVIRONMENT", "development"),
         host=os.getenv("APP_HOST", "127.0.0.1"),
         port=int(os.getenv("APP_PORT", "8000")),

backend/app/contracts.py

@@ -1250,6 +1250,12 @@ class TranscriptNoteRequest(Contract):
     include_speakers: bool = True
 
 
+class TranscriptArtifactsRequest(TranscriptNoteRequest):
+    provider_id: str = Field(min_length=1, max_length=128)
+    model: str = Field(min_length=1, max_length=256)
+    knowledge_title: str | None = Field(default=None, min_length=1, max_length=200)
+
+
 class IndexStatus(Contract):
     running_jobs: int = 0
     active_searches: int = 0

backend/app/local_models/components.py

@@ -5,11 +5,14 @@ import os
 import shutil
 import subprocess
 
-from app.config import BACKEND_DIR
+from app.config import BACKEND_DIR, get_settings
 from app.errors import ApiError
 from app.local_models.process import ThreadedProcess
 
-ROOT = BACKEND_DIR / '.venv-models-cuda'
+# 模型运行环境会在安装与升级时写入大量文件，必须位于应用数据目录，
+# 不能写入受完整性清单保护的 Core 发布目录。
+DEFAULT_ROOT = get_settings().data_dir / 'model-runtime'
+ROOT = DEFAULT_ROOT
 state = {'status': 'unchecked', 'stage': '', 'cuda_available': None}
 task = None
 

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/media_routes.py

@@ -11,7 +11,7 @@ from uuid import uuid4
 from fastapi import APIRouter, Header, Query, Request
 from fastapi.responses import FileResponse, StreamingResponse
 
-from app.contracts import TranscriptEditRequest, TranscriptNoteRequest, TranscriptionJob
+from app.contracts import TranscriptArtifactsRequest, TranscriptEditRequest, TranscriptNoteRequest, TranscriptionJob
 from app.database.db import connect, transaction
 from app.errors import ApiError
 from app.services import transcription_service as jobs
@@ -160,6 +160,12 @@ async def create_note(job_id: str, request: TranscriptNoteRequest):
     return await create_transcript_note(job_id, request)
 
 
+@router.post("/transcriptions/{job_id}/artifacts", status_code=201)
+async def create_artifacts(job_id: str, request: TranscriptArtifactsRequest):
+    from app.services.media_notes import create_transcript_artifacts
+    return await create_transcript_artifacts(job_id, request)
+
+
 @router.get("/attachments/{attachment_id}/cleanup-impact")
 async def cleanup_impact(attachment_id: str):
     attachment_path(attachment_id)

backend/app/services/chat_agents.py

@@ -41,7 +41,7 @@ async def execute(call, request):
         run = await container.agent.create_run(AgentRunCreateRequest(
             input=task, provider_id=request.provider_id, model=request.model,
             skill_id=skill_id,
-            allowed_tools=ALLOWED_TOOLS, max_steps=10, token_budget=16000,
+            allowed_tools=ALLOWED_TOOLS, max_steps=10, token_budget=None,
             allow_network=False, metadata={'source': 'chat', 'conversation_id': request.conversation_id},
         ))
     elif call.name == 'agent.status':

backend/app/services/media_notes.py

@@ -4,8 +4,11 @@ import hashlib
 from contextlib import closing
 
 from app.config import get_settings
+from app.contracts import Message, MessageRole, ModelRequest, TranscriptNoteRequest
 from app.database.db import connect, transaction
 from app.errors import ApiError
+from app.providers.base import ProviderError
+from app.providers.registry import ProviderNotFoundError
 from app.services import note_service
 from app.services.transcription_service import require_job
 
@@ -66,6 +69,136 @@ async def create_transcript_note(job_id, options):
         return note
 
 
+def _transcript_text(job) -> str:
+    if job.segments:
+        rows = []
+        for segment in job.segments:
+            speaker = job.speaker_names.get(segment.speaker, segment.speaker) if segment.speaker else ""
+            stamp = f"{int(segment.start_time // 60):02}:{int(segment.start_time % 60):02}"
+            rows.append(f"[{stamp}] {speaker}：{segment.text}" if speaker else f"[{stamp}] {segment.text}")
+        return "\n".join(rows)
+    return job.text or ""
+
+
+def _chunks(text: str, limit: int = 12000) -> list[str]:
+    """按段落切分长转录，避免在中间截断句子。"""
+    paragraphs = [part.strip() for part in text.splitlines() if part.strip()]
+    if not paragraphs:
+        return []
+    chunks: list[str] = []
+    current: list[str] = []
+    size = 0
+    for paragraph in paragraphs:
+        if current and size + len(paragraph) + 1 > limit:
+            chunks.append("\n".join(current))
+            current, size = [], 0
+        if len(paragraph) > limit:
+            if current:
+                chunks.append("\n".join(current))
+                current, size = [], 0
+            chunks.extend(paragraph[index:index + limit] for index in range(0, len(paragraph), limit))
+            continue
+        current.append(paragraph)
+        size += len(paragraph) + 1
+    if current:
+        chunks.append("\n".join(current))
+    return chunks
+
+
+async def _complete(provider_id: str, model: str, system: str, content: str) -> str:
+    from app.container import container
+    try:
+        provider = container.providers.get(provider_id).adapter
+    except ProviderNotFoundError as exc:
+        raise ApiError(404, "PROVIDER_NOT_FOUND", "所选模型提供商不存在或未启用。",
+                       {"provider_id": provider_id}) from exc
+    try:
+        turn = await provider.complete(ModelRequest(
+            provider_id=provider_id,
+            model=model,
+            system=system,
+            messages=[Message(role=MessageRole.user, content=content)],
+            temperature=0.2,
+        ))
+    except ProviderError as exc:
+        raise ApiError(502, exc.code, exc.message, {"provider_id": provider_id}) from exc
+    if not turn.text or not turn.text.strip():
+        raise ApiError(502, "KNOWLEDGE_NOTE_EMPTY", "模型没有返回知识点笔记。")
+    return turn.text.strip().removeprefix("```markdown").removeprefix("```").removesuffix("```").strip()
+
+
+async def _knowledge_markdown(job, provider_id: str, model: str, title: str) -> str:
+    transcript = _transcript_text(job)
+    if not transcript.strip():
+        raise ApiError(409, "TRANSCRIPT_EMPTY", "转录内容为空，无法提取知识点。")
+    system = (
+        "你是一名严谨的课程笔记整理助手。只能依据提供的转录内容整理，不补写未出现的事实。"
+        "输出中文 Markdown 正文，使用清晰的二级、三级标题；包含课程主题、核心概念、关键论证或步骤、"
+        "重要例子、待复习问题。合并口语重复，保留专业术语和必要条件。不要使用代码围栏，也不要写处理说明。"
+    )
+    parts = _chunks(transcript)
+    summaries: list[str] = []
+    for index, part in enumerate(parts, 1):
+        summaries.append(await _complete(
+            provider_id, model, system,
+            f"这是课程转录的第 {index}/{len(parts)} 部分。请提取可供最终整合的知识点：\n\n{part}",
+        ))
+    if len(summaries) == 1:
+        body = summaries[0]
+    else:
+        body = await _complete(
+            provider_id, model, system,
+            "请将以下分段知识点合并成一篇完整课程笔记，消除重复并保持逻辑顺序：\n\n"
+            + "\n\n".join(f"### 分段 {index}\n{summary}" for index, summary in enumerate(summaries, 1)),
+        )
+    return "\n".join([
+        f"<!-- knowledge-note:{job.job_id}:{job.revision}:{provider_id}:{model} -->",
+        f"# {title}", "", f"[查看完整转录稿](/#/media?job={job.job_id})", "", body,
+    ])
+
+
+async def create_transcript_artifacts(job_id, options):
+    """为完成的转录生成可回听的全文和模型整理的知识点笔记。"""
+    transcript_options = TranscriptNoteRequest(
+        title=options.title,
+        folder=options.folder,
+        update_existing=options.update_existing,
+        include_timestamps=options.include_timestamps,
+        include_speakers=options.include_speakers,
+    )
+    transcript_note = await create_transcript_note(job_id, transcript_options)
+    job = require_job(job_id)
+    knowledge_title = options.knowledge_title or f"{options.title} · 知识点"
+    identity = (str(get_settings().db_path), job_id, "knowledge")
+    lock = _locks.setdefault(identity, asyncio.Lock())
+    async with lock:
+        signature = "knowledge:" + hashlib.sha256(options.model_copy(update={
+            "update_existing": False,
+            "knowledge_title": knowledge_title,
+        }).model_dump_json(exclude={"update_existing"}).encode()).hexdigest()
+        with closing(connect()) as conn:
+            row = conn.execute(
+                "SELECT note_id FROM media_notes WHERE job_id=? AND revision=? AND options_hash=?",
+                (job_id, job.revision, signature),
+            ).fetchone()
+        if row:
+            knowledge_note = await note_service.get_note(row[0])
+            if knowledge_note is not None:
+                return {"transcript": transcript_note, "knowledge_note": knowledge_note}
+        markdown = await _knowledge_markdown(job, options.provider_id, options.model, knowledge_title)
+        note_title = f"{knowledge_title} · {job_id[-8:]}-r{job.revision}-{signature[-6:]}"
+        knowledge_note = await note_service.create_note(
+            title=note_title,
+            markdown=markdown,
+            folder=options.folder,
+            tags=["课程笔记", "知识点"],
+        )
+        with closing(connect()) as conn, transaction(conn):
+            conn.execute("INSERT OR IGNORE INTO media_notes VALUES (?,?,?,?)",
+                         (job_id, job.revision, signature, knowledge_note.note_id))
+        return {"transcript": transcript_note, "knowledge_note": knowledge_note}
+
+
 async def _create_note(title, markdown, options, marker):
     try:
         note = await note_service.create_note(title=title, markdown=markdown, folder=options.folder, tags=["转写"])

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/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "notes-agent-backend"
-version = "0.1.0"
+version = "0.5.0"
 description = "Notes Agent 的 FastAPI 基础壳子"
 readme = "README.md"
 requires-python = ">=3.11"

backend/tests/test_media_jobs.py

@@ -96,6 +96,18 @@ def test_terminology_export_and_privacy_cleanup():
         first = client.post(f'/api/media/transcriptions/{job_id}/notes', json={'title':'课程'}).json()
         again = client.post(f'/api/media/transcriptions/{job_id}/notes', json={'title':'课程'}).json()
         assert first['note_id'] == again['note_id']
+        artifacts = client.post(f'/api/media/transcriptions/{job_id}/artifacts', json={
+            'title': '课程', 'knowledge_title': '课程知识点',
+            'provider_id': 'mock', 'model': 'mock-1',
+        })
+        assert artifacts.status_code == 201
+        assert artifacts.json()['transcript']['note_id'] == first['note_id']
+        assert artifacts.json()['knowledge_note']['note_id'] != first['note_id']
+        repeated = client.post(f'/api/media/transcriptions/{job_id}/artifacts', json={
+            'title': '课程', 'knowledge_title': '课程知识点',
+            'provider_id': 'mock', 'model': 'mock-1',
+        })
+        assert repeated.json()['knowledge_note']['note_id'] == artifacts.json()['knowledge_note']['note_id']
         response = client.delete('/api/media/attachments/lecture.txt')
         assert first['note_id'] in response.json()['retained_note_ids']
         cleaned = client.get(f'/api/media/transcriptions/{job_id}').json()

backend/tests/test_runtime_components.py

@@ -13,8 +13,6 @@ def isolate(monkeypatch, tmp_path):
     monkeypatch.setattr(components, 'ROOT', tmp_path / 'cuda')
     monkeypatch.setattr(components, 'state', {'status': 'unchecked', 'stage': '', 'cuda_available': None})
     monkeypatch.setattr(components, 'task', None)
-
-
 def test_status_checks_without_installing_and_detects_existing_cuda(monkeypatch):
     python = components.ROOT / 'Scripts/python.exe'
     python.parent.mkdir(parents=True)

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]

backend/uv.lock

@@ -1108,7 +1108,7 @@ wheels = [
 
 [[package]]
 name = "notes-agent-backend"
-version = "0.1.0"
+version = "0.5.0"
 source = { virtual = "." }
 dependencies = [
     { name = "cryptography" },

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": "0.5.0",
   "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 = "0.5.0"
 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 = "0.5.0"
 edition = "2021"
 rust-version = "1.89"
 
@@ -48,7 +48,7 @@ cap-fs-ext = "4.0.2"
 jsonschema = { version = "0.55", default-features = false }
 
 [target.'cfg(windows)'.dependencies]
-windows-sys = { version = "0.61", features = ["Win32_Foundation", "Win32_Security", "Win32_Security_Isolation", "Win32_Security_Authorization", "Win32_System_Com", "Win32_System_JobObjects", "Win32_System_Threading", "Win32_System_Pipes", "Win32_System_IO", "Win32_System_SystemInformation", "Win32_Storage_FileSystem", "Win32_System_RemoteDesktop", "Win32_UI_WindowsAndMessaging", "Win32_Graphics_Gdi", "Win32_System_LibraryLoader"] }
+windows-sys = { version = "0.61", features = ["Win32_Foundation", "Win32_Security", "Win32_Security_Cryptography", "Win32_Security_Isolation", "Win32_Security_Authorization", "Win32_System_Com", "Win32_System_JobObjects", "Win32_System_Threading", "Win32_System_Pipes", "Win32_System_IO", "Win32_System_SystemInformation", "Win32_Storage_FileSystem", "Win32_System_RemoteDesktop", "Win32_UI_WindowsAndMessaging", "Win32_Graphics_Gdi", "Win32_System_LibraryLoader"] }
 
 [build-dependencies]
 tauri-build = { version = "2", optional = true , features = [] }

frontend/src-tauri/examples/migrate_auto_unlock.rs

@@ -0,0 +1,44 @@
+use notesagent_host::credentials::CredentialBroker;
+use std::path::PathBuf;
+
+fn main() -> Result<(), String> {
+    let mut arguments = std::env::args_os().skip(1);
+    let vault = PathBuf::from(arguments.next().ok_or("TARGET_REQUIRED")?);
+    let legacy = PathBuf::from(arguments.next().ok_or("LEGACY_REQUIRED")?);
+    if arguments.next().is_some() {
+        return Err("ARGUMENTS_INVALID".into());
+    }
+    let parent = vault.parent().ok_or("TARGET_INVALID")?;
+    let backup = parent.join("stronghold.pre-0.5.0.onxcred");
+    let auto_key = parent.join("auto-unlock.dpapi");
+    if auto_key.exists() {
+        return Err("AUTO_UNLOCK_ALREADY_CONFIGURED".into());
+    }
+    if backup.exists() {
+        return Err("BACKUP_ALREADY_EXISTS".into());
+    }
+    if vault.exists() {
+        std::fs::rename(&vault, &backup).map_err(|_| "BACKUP_FAILED")?;
+    }
+    let migrated = (|| {
+        let mut broker = CredentialBroker::new(vault.clone());
+        if !broker.ensure_system_unlock()? {
+            return Err("AUTO_UNLOCK_INITIALIZATION_FAILED".into());
+        }
+        broker.import_fernet(&legacy, None)
+    })();
+    match migrated {
+        Ok(count) => {
+            println!("Migrated {count} credential(s) to Windows automatic unlock.");
+            Ok(())
+        }
+        Err(error) => {
+            let _ = std::fs::remove_file(&vault);
+            let _ = std::fs::remove_file(&auto_key);
+            if backup.exists() {
+                let _ = std::fs::rename(&backup, &vault);
+            }
+            Err(error)
+        }
+    }
+}

frontend/src-tauri/src/credential_autounlock.rs

@@ -0,0 +1,109 @@
+//! Windows DPAPI-backed storage for the random Stronghold unlock secret.
+use std::fs;
+use std::io::Write;
+use std::path::Path;
+use windows_sys::Win32::Foundation::LocalFree;
+use windows_sys::Win32::Security::Cryptography::{
+    CryptProtectData, CryptUnprotectData, CRYPTPROTECT_UI_FORBIDDEN, CRYPT_INTEGER_BLOB,
+};
+use zeroize::Zeroizing;
+
+type Result<T> = std::result::Result<T, String>;
+const MAGIC: &[u8] = b"ONXDPAPI1";
+const ENTROPY: &[u8] = b"OpenNexus credential auto-unlock v1";
+
+fn transform(data: &[u8], protect: bool) -> Result<Zeroizing<Vec<u8>>> {
+    let input = CRYPT_INTEGER_BLOB {
+        cbData: u32::try_from(data.len()).map_err(|_| "CREDENTIAL_AUTO_UNLOCK_FAILED")?,
+        pbData: data.as_ptr() as *mut u8,
+    };
+    let entropy = CRYPT_INTEGER_BLOB {
+        cbData: ENTROPY.len() as u32,
+        pbData: ENTROPY.as_ptr() as *mut u8,
+    };
+    let mut output = CRYPT_INTEGER_BLOB::default();
+    let ok = unsafe {
+        if protect {
+            CryptProtectData(
+                &input,
+                std::ptr::null(),
+                &entropy,
+                std::ptr::null(),
+                std::ptr::null(),
+                CRYPTPROTECT_UI_FORBIDDEN,
+                &mut output,
+            )
+        } else {
+            CryptUnprotectData(
+                &input,
+                std::ptr::null_mut(),
+                &entropy,
+                std::ptr::null(),
+                std::ptr::null(),
+                CRYPTPROTECT_UI_FORBIDDEN,
+                &mut output,
+            )
+        }
+    };
+    if ok == 0 || output.pbData.is_null() || output.cbData == 0 {
+        return Err("CREDENTIAL_AUTO_UNLOCK_FAILED".into());
+    }
+    let result = unsafe {
+        Zeroizing::new(std::slice::from_raw_parts(output.pbData, output.cbData as usize).to_vec())
+    };
+    if !protect {
+        unsafe { std::ptr::write_bytes(output.pbData, 0, output.cbData as usize) };
+    }
+    unsafe { LocalFree(output.pbData as *mut core::ffi::c_void) };
+    Ok(result)
+}
+
+pub fn load(path: &Path) -> Result<Option<Zeroizing<Vec<u8>>>> {
+    if !path.exists() {
+        return Ok(None);
+    }
+    let metadata = fs::symlink_metadata(path).map_err(|_| "CREDENTIAL_AUTO_UNLOCK_FAILED")?;
+    if !metadata.is_file() || metadata.file_type().is_symlink() || metadata.len() > 64 * 1024 {
+        return Err("CREDENTIAL_AUTO_UNLOCK_FAILED".into());
+    }
+    let bytes = fs::read(path).map_err(|_| "CREDENTIAL_AUTO_UNLOCK_FAILED")?;
+    if !bytes.starts_with(MAGIC) || bytes.len() == MAGIC.len() {
+        return Err("CREDENTIAL_AUTO_UNLOCK_FAILED".into());
+    }
+    transform(&bytes[MAGIC.len()..], false).map(Some)
+}
+
+pub fn save(path: &Path, secret: &[u8]) -> Result<()> {
+    let protected = transform(secret, true)?;
+    let parent = path.parent().ok_or("CREDENTIAL_AUTO_UNLOCK_FAILED")?;
+    fs::create_dir_all(parent).map_err(|_| "CREDENTIAL_AUTO_UNLOCK_FAILED")?;
+    let mut target =
+        tempfile::NamedTempFile::new_in(parent).map_err(|_| "CREDENTIAL_AUTO_UNLOCK_FAILED")?;
+    target
+        .write_all(MAGIC)
+        .and_then(|_| target.write_all(&protected))
+        .and_then(|_| target.as_file().sync_all())
+        .map_err(|_| "CREDENTIAL_AUTO_UNLOCK_FAILED")?;
+    target
+        .persist(path)
+        .map_err(|_| "CREDENTIAL_AUTO_UNLOCK_FAILED")?;
+    Ok(())
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn dpapi_round_trip_never_persists_plaintext() {
+        let temp = tempfile::tempdir().unwrap();
+        let path = temp.path().join("auto-unlock.dpapi");
+        let secret = b"test-system-secret-123456789";
+        save(&path, secret).unwrap();
+        assert!(!fs::read(&path)
+            .unwrap()
+            .windows(secret.len())
+            .any(|part| part == secret));
+        assert_eq!(load(&path).unwrap().unwrap().as_slice(), secret);
+    }
+}

frontend/src-tauri/src/credentials.rs

@@ -354,6 +354,52 @@ pub struct CredentialBroker {
 }
 
 impl CredentialBroker {
+    #[cfg(windows)]
+    fn auto_unlock_path(&self) -> Result<PathBuf> {
+        Ok(self
+            .path
+            .parent()
+            .ok_or("CREDENTIAL_PATH_INVALID")?
+            .join("auto-unlock.dpapi"))
+    }
+
+    /// Unlocks with a random secret protected by Windows DPAPI. A new vault is initialized
+    /// automatically; an existing password vault is never overwritten implicitly.
+    #[cfg(windows)]
+    pub fn ensure_system_unlock(&mut self) -> Result<bool> {
+        let key_path = self.auto_unlock_path()?;
+        if let Some(secret) = crate::credential_autounlock::load(&key_path)? {
+            self.unlock(secret)?;
+            return Ok(true);
+        }
+        if self.path.exists() {
+            return Ok(false);
+        }
+        let mut secret = Zeroizing::new(vec![0u8; 32]);
+        rand::rngs::OsRng
+            .try_fill_bytes(&mut secret)
+            .map_err(|_| "CREDENTIAL_ENTROPY_FAILED")?;
+        crate::credential_autounlock::save(&key_path, &secret)?;
+        self.unlock(secret)?;
+        Ok(true)
+    }
+
+    #[cfg(windows)]
+    pub fn enable_system_unlock(&self, password: &[u8]) -> Result<()> {
+        self.session()?;
+        crate::credential_autounlock::save(&self.auto_unlock_path()?, password)
+    }
+
+    #[cfg(windows)]
+    pub fn has_system_unlock(&self) -> bool {
+        self.auto_unlock_path().is_ok_and(|path| path.is_file())
+    }
+
+    #[cfg(not(windows))]
+    pub fn has_system_unlock(&self) -> bool {
+        false
+    }
+
     /// 源来自本机文件选择器，而不是原始 WebView 路径。导入是幂等的；冲突的 ID 会停止整个事务。
     pub fn import_fernet(
         &mut self,
@@ -1041,6 +1087,34 @@ mod tests {
     fn password() -> Zeroizing<Vec<u8>> {
         Zeroizing::new(b"test-only-password-123".to_vec())
     }
+
+    #[cfg(windows)]
+    #[test]
+    fn system_unlock_survives_broker_restart() {
+        let temp = tempfile::tempdir().unwrap();
+        let path = temp.path().join("credentials/stronghold.v1");
+        let id = CredentialId {
+            scope: Scope::Provider,
+            id: "provider-restart".into(),
+        };
+        {
+            let mut broker = CredentialBroker::new(path.clone());
+            assert!(broker.ensure_system_unlock().unwrap());
+            broker
+                .put(&id, Zeroizing::new(b"restart-secret".to_vec()))
+                .unwrap();
+        }
+        let mut restarted = CredentialBroker::new(path);
+        assert!(restarted.ensure_system_unlock().unwrap());
+        assert_eq!(
+            restarted
+                .resolve(&Scope::Provider, &id)
+                .unwrap()
+                .unwrap()
+                .as_slice(),
+            b"restart-secret"
+        );
+    }
     fn b04_fixture() -> (Vec<u8>, String, BTreeMap<String, String>) {
         let fixture: serde_json::Value =
             serde_json::from_str(include_str!("../tests/fixtures/fernet-python.json")).unwrap();

frontend/src-tauri/src/lib.rs

@@ -2,6 +2,8 @@
 
 pub mod core;
 pub mod core_update;
+#[cfg(windows)]
+mod credential_autounlock;
 pub mod credentials;
 mod payloads;
 mod preference_records;

frontend/src-tauri/src/main.rs

@@ -561,7 +561,10 @@ fn credentials_status(host: State<'_, Host>) -> Result<serde_json::Value, String
         .try_lock()
         .map_err(|_| "CREDENTIALS_BUSY")?;
     let broker = broker.as_ref().ok_or("HOST_NOT_READY")?;
-    Ok(serde_json::json!({"locked":broker.is_locked()}))
+    Ok(serde_json::json!({
+        "locked": broker.is_locked(),
+        "automatic": if cfg!(windows) { broker.has_system_unlock() } else { false }
+    }))
 }
 
 #[tauri::command]
@@ -578,12 +581,13 @@ async fn credentials_unlock(host: State<'_, Host>, password: String) -> Result<(
     let broker = host.credentials.clone();
     let password = Zeroizing::new(password.into_bytes());
     tauri::async_runtime::spawn_blocking(move || {
-        broker
-            .lock()
-            .map_err(|_| "HOST_BUSY")?
-            .as_mut()
-            .ok_or("HOST_NOT_READY")?
-            .unlock(password)
+        let mut guard = broker.lock().map_err(|_| "HOST_BUSY")?;
+        let broker = guard.as_mut().ok_or("HOST_NOT_READY")?;
+        let retained = Zeroizing::new(password.to_vec());
+        broker.unlock(password)?;
+        #[cfg(windows)]
+        broker.enable_system_unlock(&retained)?;
+        Ok(())
     })
     .await
     .map_err(|_| "HOST_BUSY")?
@@ -705,12 +709,13 @@ async fn credentials_change_password(
     let broker = host.credentials.clone();
     let password = Zeroizing::new(password.into_bytes());
     tauri::async_runtime::spawn_blocking(move || {
-        broker
-            .lock()
-            .map_err(|_| "HOST_BUSY")?
-            .as_mut()
-            .ok_or("HOST_NOT_READY")?
-            .change_password(password)
+        let mut guard = broker.lock().map_err(|_| "HOST_BUSY")?;
+        let broker = guard.as_mut().ok_or("HOST_NOT_READY")?;
+        let retained = Zeroizing::new(password.to_vec());
+        broker.change_password(password)?;
+        #[cfg(windows)]
+        broker.enable_system_unlock(&retained)?;
+        Ok(())
     })
     .await
     .map_err(|_| "HOST_BUSY")?
@@ -948,11 +953,15 @@ fn main() {
                 .lock()
                 .map_err(|_| std::io::Error::other("HOST_BUSY"))? = Some(extension_store);
             let credential_state = app.state::<Host>().credentials.clone();
+            let mut broker =
+                CredentialBroker::new(app.path().app_data_dir()?.join("credentials/stronghold.v1"));
+            #[cfg(windows)]
+            broker
+                .ensure_system_unlock()
+                .map_err(std::io::Error::other)?;
             *credential_state
                 .lock()
-                .map_err(|_| std::io::Error::other("HOST_BUSY"))? = Some(CredentialBroker::new(
-                app.path().app_data_dir()?.join("credentials/stronghold.v1"),
-            ));
+                .map_err(|_| std::io::Error::other("HOST_BUSY"))? = Some(broker);
             let signal = credential_state
                 .lock()
                 .map_err(|_| std::io::Error::other("HOST_BUSY"))?

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": "0.5.0",
   "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/agent/AgentView.vue

@@ -21,7 +21,7 @@ const { openCitation } = useCitationNavigation()
 const pageError = ref('')
 const form = reactive({
   input: '', provider_id: '', model: '', skill_id: '', max_steps: 10,
-  tool_timeout_seconds: 30, run_timeout_seconds: 300, token_budget: 8000,
+  tool_timeout_seconds: 30, run_timeout_seconds: 300, limit_token_budget: false, token_budget: 8000,
   allow_network: false, max_concurrent_tools: 1, allowed_tools: [] as string[],
 })
 
@@ -61,7 +61,7 @@ async function createRun() {
       input: form.input, provider_id: form.provider_id, model: form.model,
       skill_id: form.skill_id || undefined, allowed_tools: form.allowed_tools,
       max_steps: form.max_steps, tool_timeout_seconds: form.tool_timeout_seconds,
-      run_timeout_seconds: form.run_timeout_seconds, token_budget: form.token_budget,
+      run_timeout_seconds: form.run_timeout_seconds, token_budget: form.limit_token_budget ? form.token_budget : null,
       allow_network: form.allow_network, max_concurrent_tools: form.max_concurrent_tools,
     })
     await router.replace({ name: 'agent', params: { runId: run.run_id } })
@@ -101,7 +101,7 @@ async function handleOpenCitation(data: Record<string, unknown>) {
         <div class="field"><label>{{ t('最大步骤', 'Maximum steps') }}</label><input v-model.number="form.max_steps" class="input" type="number" min="1" max="100" /></div>
         <div class="field"><label>{{ t('工具超时（秒）', 'Tool timeout (seconds)') }}</label><input v-model.number="form.tool_timeout_seconds" class="input" type="number" min="1" /></div>
         <div class="field"><label>{{ t('运行超时（秒）', 'Run timeout (seconds)') }}</label><input v-model.number="form.run_timeout_seconds" class="input" type="number" min="1" /></div>
-        <div class="field"><label>{{ t('令牌预算', 'Token budget') }}</label><input v-model.number="form.token_budget" class="input" type="number" min="1" /></div>
+        <div class="field budget-field"><label><input v-model="form.limit_token_budget" type="checkbox" />{{ t('限制令牌消耗', 'Limit token usage') }}</label><input v-if="form.limit_token_budget" v-model.number="form.token_budget" class="input" type="number" min="1" :aria-label="t('令牌上限', 'Token limit')" /><small v-else class="subtle">{{ t('默认不限制；仍可随时取消运行。', 'Unlimited by default; the run can still be cancelled at any time.') }}</small></div>
         <div class="field"><label>{{ t('最大并发工具', 'Maximum concurrent tools') }}</label><input v-model.number="form.max_concurrent_tools" class="input" type="number" min="1" /></div>
       </div>
       <div class="field"><label>{{ t('允许使用的工具', 'Allowed tools') }}</label><div class="tool-grid"><ToolOption v-for="tool in agentStore.tools" :key="tool.name" :name="tool.name" :description="tool.description" :selected="form.allowed_tools.includes(tool.name)" @toggle="toggleTool" /></div></div>
@@ -150,6 +150,16 @@ async function handleOpenCitation(data: Record<string, unknown>) {
 <style scoped>
 .agent-page > * { width: min(100%, 1080px); margin-inline: auto; }
 .run-form { display: grid; gap: var(--space-xl); }
+.budget-field {
+  min-height: 78px;
+  align-content: center;
+  padding: var(--space-sm) var(--space-md);
+  border: 1px solid var(--color-border-default);
+  border-radius: var(--radius-md);
+  background: var(--color-surface-secondary);
+}
+.budget-field > label { color: var(--color-text-primary); }
+.budget-field > .input { background: var(--color-surface-primary); }
 .tool-grid { display: grid; align-items: start; grid-template-columns: repeat(auto-fit, minmax(230px, 1fr)); gap: var(--space-sm); }
 .network { display: flex; gap: var(--space-sm); }
 .trace-layout { display: grid; gap: var(--space-lg); }

frontend/src/features/media/MediaView.vue

@@ -9,8 +9,10 @@ import { useRoute } from 'vue-router'
 import { mediaService, createMediaSubmission, type MediaJob } from '@/services/mediaService'
 import { localeTag, t } from '@/i18n'
 import FilePicker from '@/components/common/FilePicker.vue'
+import { useProviderStore } from '@/stores/provider'
 
 const route = useRoute()
+const providerStore = useProviderStore()
 const maxUploadMiB = isDesktop() ? 64 : 128
 const submission = createMediaSubmission()
 const updateExisting = ref(false)
@@ -44,6 +46,10 @@ const error = ref('')
 const notice = ref('')
 const dirty = ref(false)
 const title = ref(t('课堂转写', 'Class transcript'))
+const knowledgeTitle = ref(t('课堂知识点笔记', 'Class knowledge notes'))
+const providerId = ref('')
+const model = ref('')
+const models = computed(() => providerStore.modelsByProvider[providerId.value] ?? [])
 const player = ref<HTMLAudioElement | null>(null)
 const position = ref(0)
 const speed = ref(1)
@@ -58,6 +64,7 @@ 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 ${warning.split(':')[1]} damaged audio packets; missing duration was retained as silence. Review the affected content.`)
   : ({
   DIARIZATION_UNAVAILABLE: t('当前无法分离说话人', 'Speaker identification is unavailable'),
+  DIARIZATION_PARTIAL: t('部分片段没有足够语音用于说话人识别，请人工校对', 'Some segments do not contain enough speech for speaker identification; review them manually'),
   WORD_TIMESTAMPS_UNAVAILABLE: t('未提供逐字时间戳', 'Word-level timestamps are unavailable'),
   DIARIZATION_SEGMENT_LEVEL: t('说话人按音频段估计，同段多人或重叠发言需人工校对', 'Speakers are estimated per segment; multiple or overlapping speakers require manual correction'),
 } as Record<string, string>)[warning] || warning
@@ -120,23 +127,40 @@ async function compareSpeaker() {
     }
   })
 }
+async function createArtifacts() {
+  if (!selected.value || !providerId.value || !model.value.trim()) return
+  await action(async () => {
+    const result = await mediaService.artifacts(selected.value!.job_id, {
+      title: title.value,
+      knowledge_title: knowledgeTitle.value,
+      provider_id: providerId.value,
+      model: model.value,
+      update_existing: updateExisting.value,
+    })
+    notice.value = t(
+      `已生成完整转录稿“${result.transcript.title}”和知识点笔记“${result.knowledge_note.title}”。`,
+      `Created transcript “${result.transcript.title}” and knowledge notes “${result.knowledge_note.title}”.`,
+    )
+  })
+}
 function loaded() { if (player.value) player.value.playbackRate = speed.value; const seconds = Number(route.query.time || 0); if (Number.isFinite(seconds) && seconds >= 0) seek(seconds) }
 onMounted(async () => {
-  await refresh()
+  await Promise.all([refresh(), providerStore.loadProviders()])
+  providerId.value = providerStore.defaultProviderId
   if (typeof route.query.job === 'string') {
     try { selected.value = await mediaService.get(route.query.job) } catch (e) { error.value = (e as Error).message }
   }
 })
+watch(providerId, async (value) => {
+  model.value = providerStore.providers.find(item => item.provider_id === value)?.default_model ?? ''
+  if (!value) return
+  try { await providerStore.loadModels(value) } catch { /* 允许手动填写模型 ID。 */ }
+})
 onUnmounted(() => { stopped = true; clearTimeout(timer) })
 </script>
 
 <template>
   <section class="media-page">
-    <details class="ui-disclosure">
-      <summary>{{ t('当前转写能力与验收范围', 'Transcription capabilities and validation') }}</summary>
-      <p>{{ t('本地转写提供片段级时间戳与说话人聚类，不提供逐字强制对齐或重叠语音分离。聚类编号不代表已确认的真实人数。', 'Local transcription provides segment timestamps and speaker clusters, without forced word alignment or overlapping speech separation. Cluster IDs are not verified speaker counts.') }}</p>
-      <p>{{ t('无参考转写或说话人标注时，只能验证功能与耗时，不能据此判断准确率。请通过播放与人工校对确认内容。', 'Without reference transcripts or speaker labels, runs validate functionality and timing, not accuracy. Review the audio and correct the transcript.') }}</p>
-    </details>
     <ActionDialog v-if="actionDialog" v-bind="actionDialog" @resolve="resolveAction" />
     <header class="feature-header"><div><h1>{{ t('音视频转写', 'Media Transcription') }}</h1><p class="subtle">{{ t(`上传音频或视频音轨，转写、校对后保存到知识库。最多 ${maxUploadMiB} MiB；超过 25 MiB 请启用仅本地处理。音轨最长 1 小时。`, `Upload audio or a video soundtrack, transcribe and correct it, then save it to the knowledge base. Up to ${maxUploadMiB} MiB; enable local-only processing above 25 MiB. Audio duration is limited to one hour.`) }}</p></div></header>
     <div v-if="error" class="error-banner" role="alert">{{ error }}</div><p v-if="notice" role="status">{{ notice }}</p>
@@ -180,7 +204,16 @@ onUnmounted(() => { stopped = true; clearTimeout(timer) })
             <button class="button-secondary" @click="action(async () => { history = (await mediaService.revisions(selected!.job_id)).items })">{{ t('修订历史', 'Revision history') }}</button></div>
           <details class="ui-disclosure"><summary>{{ t('原始识别文本', 'Original recognition text') }}</summary><pre>{{ selected.original_text }}</pre></details>
           <details v-for="revision in history" :key="revision.revision" class="ui-disclosure"><summary>{{ t('修订', 'Revision') }} {{ revision.revision }}</summary><pre>{{ revision.text }}</pre></details>
-          <div class="inline-actions"><label><input v-model="updateExisting" type="checkbox" />{{ t('更新上次导出的笔记（已手动修改则拒绝）', 'Update the previously exported note (refuse if manually edited)') }}</label><input v-model="title" class="input" :aria-label="t('笔记标题', 'Note title')" /><button class="button-primary" :disabled="busy || dirty || !title.trim()" @click="action(async () => { const note = await mediaService.note(selected!.job_id, title, updateExisting); notice = `${t('已保存笔记：', 'Saved note: ')}${note.title}` })">{{ t('保存为笔记', 'Save as note') }}</button></div>
+          <section class="artifact-panel">
+            <div><h3>{{ t('生成课程材料', 'Create course materials') }}</h3><p class="subtle">{{ t('一次生成两份内容：带时间戳的完整转录稿，以及由所选模型提取的知识点笔记。', 'Create two outputs: a timestamped full transcript and knowledge notes extracted by the selected model.') }}</p></div>
+            <div class="artifact-grid">
+              <label>{{ t('转录稿标题', 'Transcript title') }}<input v-model="title" class="input" /></label>
+              <label>{{ t('知识点笔记标题', 'Knowledge-note title') }}<input v-model="knowledgeTitle" class="input" /></label>
+              <label>{{ t('模型提供商', 'Model provider') }}<select v-model="providerId" class="select"><option value="">{{ t('请选择', 'Select') }}</option><option v-for="item in providerStore.enabledProviders" :key="item.provider_id" :value="item.provider_id">{{ item.name }}</option></select></label>
+              <label>{{ t('知识提取模型', 'Knowledge extraction model') }}<input v-model="model" class="input" list="media-models" :placeholder="t('填写模型 ID', 'Enter model ID')" /><datalist id="media-models"><option v-for="item in models" :key="item.model_id" :value="item.model_id">{{ item.name }}</option></datalist></label>
+            </div>
+            <div class="inline-actions"><label><input v-model="updateExisting" type="checkbox" />{{ t('安全更新上次导出的转录稿', 'Safely update the last exported transcript') }}</label><button class="button-primary" :disabled="busy || dirty || !title.trim() || !knowledgeTitle.trim() || !providerId || !model.trim()" @click="createArtifacts">{{ busy ? t('生成中…', 'Creating…') : t('生成转录稿与知识点笔记', 'Create transcript and knowledge notes') }}</button></div>
+          </section>
         </template>
       </article>
       <div v-else class="panel subtle">{{ t('选择任务查看转写结果。', 'Select a job to view its transcript.') }}</div>
@@ -190,5 +223,5 @@ onUnmounted(() => { stopped = true; clearTimeout(timer) })
 
 <style scoped>
 .media-page > :is(.feature-header, .panel, .media-columns, .error-banner) { width: 100%; max-width: 1180px; margin-inline: auto; }
-.media-page{padding:28px;overflow:auto;height:100%;display:flex;flex-direction:column;gap:20px}.upload{display:grid;gap:12px;padding:20px}.upload-options{display:flex;flex-wrap:wrap;gap:16px}.upload-actions{justify-content:flex-end}.media-columns{display:grid;grid-template-columns:260px minmax(0,1fr);gap:20px}.panel{padding:20px}.job-row{display:flex;flex-direction:column;gap:6px;width:100%;text-align:left;padding:12px;background:transparent;border:1px solid var(--color-border-default);border-radius:10px;margin-bottom:8px;cursor:pointer;color:inherit}.job-row small{overflow:hidden;text-overflow:ellipsis;max-width:100%}.selected,.current{background:var(--color-background-hover);outline:1px solid var(--color-accent-primary)}.transcript{display:flex;flex-direction:column;gap:16px}.transcript header,.segment{display:flex;gap:12px;align-items:center}.transcript>.button-danger{align-self:flex-start}.transcript>label{white-space:nowrap}.transcript>label select{width:160px}.segment textarea{flex:1}.speaker-names{display:flex;flex-wrap:wrap;gap:10px}audio{width:100%;border-radius:var(--radius-md);accent-color:var(--color-accent-primary)}pre{white-space:pre-wrap;word-break:break-word}label{display:flex;gap:8px;align-items:center}@media(max-width:850px){.media-columns{grid-template-columns:1fr}.segment{flex-wrap:wrap}}@media(max-width:560px){.upload-actions>*{flex:1}.upload-options{flex-direction:column}}
+.media-page{padding:28px;overflow:auto;height:100%;display:flex;flex-direction:column;gap:20px}.upload{display:grid;gap:12px;padding:20px}.upload-options{display:flex;flex-wrap:wrap;gap:16px}.upload-actions{justify-content:flex-end}.media-columns{display:grid;grid-template-columns:260px minmax(0,1fr);gap:20px}.panel{padding:20px}.job-row{display:flex;flex-direction:column;gap:6px;width:100%;text-align:left;padding:12px;background:transparent;border:1px solid var(--color-border-default);border-radius:10px;margin-bottom:8px;cursor:pointer;color:inherit}.job-row small{overflow:hidden;text-overflow:ellipsis;max-width:100%}.selected,.current{background:var(--color-background-hover);outline:1px solid var(--color-accent-primary)}.transcript{display:flex;flex-direction:column;gap:16px}.transcript header,.segment{display:flex;gap:12px;align-items:center}.transcript>.button-danger{align-self:flex-start}.transcript>label{white-space:nowrap}.transcript>label select{width:160px}.segment textarea{flex:1}.speaker-names{display:flex;flex-wrap:wrap;gap:10px}.artifact-panel{display:grid;gap:14px;padding:18px;border:1px solid var(--color-border-default);border-radius:var(--radius-lg);background:var(--color-surface-secondary)}.artifact-panel h3,.artifact-panel p{margin:0}.artifact-grid{display:grid;grid-template-columns:repeat(2,minmax(0,1fr));gap:12px}.artifact-grid label{align-items:stretch;flex-direction:column;color:var(--color-text-secondary)}.artifact-grid :is(.input,.select){background:var(--color-surface-primary);color:var(--color-text-primary)}audio{width:100%;border-radius:var(--radius-md);accent-color:var(--color-accent-primary)}pre{white-space:pre-wrap;word-break:break-word}label{display:flex;gap:8px;align-items:center}@media(max-width:850px){.media-columns{grid-template-columns:1fr}.segment{flex-wrap:wrap}}@media(max-width:620px){.artifact-grid{grid-template-columns:1fr}}@media(max-width:560px){.upload-actions>*{flex:1}.upload-options{flex-direction:column}}
 </style>

frontend/src/features/settings/CredentialVaultSettings.vue

@@ -4,6 +4,7 @@ import { hostInvoke } from '@/services/platform/desktop'
 import { t } from '@/i18n'
 
 const locked = ref(true)
+const automatic = ref(false)
 const busy = ref(false)
 const password = ref('')
 const confirmation = ref('')
@@ -15,8 +16,9 @@ function failureMessage(error: unknown, fallback: string) {
     : code
 }
 async function refresh() {
-  const state = await hostInvoke<{ locked: boolean }>('credentials_status')
+  const state = await hostInvoke<{ locked: boolean; automatic?: boolean }>('credentials_status')
   locked.value = state.locked
+  automatic.value = state.automatic === true
 }
 async function importLegacy() {
   busy.value = true; message.value = ''
@@ -81,8 +83,8 @@ onUnmounted(() => clearInterval(statusTimer))
 <template>
   <section class="panel settings-section credential-vault" aria-labelledby="credential-vault-title">
     <h2 id="credential-vault-title">{{ t('设备凭据保险库', 'Device credential vault') }}</h2>
-    <p>{{ locked ? t('已锁定：使用模型密钥前请解锁。首次解锁将创建本机保险库。', 'Locked: unlock before using provider credentials. The first unlock creates this device’s vault.') : t('已解锁：密钥仅由本机受控调用使用。', 'Unlocked: credentials are available to authorized local calls.') }}</p>
-    <p class="subtle">{{ t('口令至少12个字符。遗失口令后需恢复备份或重新配置密钥；笔记仍可使用。', 'Use at least 12 characters. A lost password requires a backup or re-entering credentials; notes remain available.') }}</p>
+    <p>{{ locked ? t('已锁定：使用模型密钥前请解锁。', 'Locked: unlock before using provider credentials.') : automatic ? t('已自动解锁：凭据由当前 Windows 用户的系统加密保护。', 'Automatically unlocked: credentials are protected for the current Windows user.') : t('已解锁：密钥仅由本机受控调用使用。', 'Unlocked: credentials are available to authorized local calls.') }}</p>
+    <p class="subtle">{{ automatic ? t('应用重启后会自动解锁；Windows 锁屏仍会立即撤销当前会话。', 'The vault unlocks automatically after an app restart; locking Windows still revokes the current session immediately.') : t('口令至少12个字符。成功解锁后将为当前 Windows 用户启用自动解锁。', 'Use at least 12 characters. A successful unlock enables automatic unlock for the current Windows user.') }}</p>
     <form @submit.prevent="act(locked ? 'unlock' : 'change_password')">
       <label>{{ locked ? t('解锁口令', 'Vault password') : t('新口令', 'New password') }}
         <input v-model="password" type="password" minlength="12" maxlength="1024" required autocomplete="off" :disabled="busy" />

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>v0.5.0</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/agentService.ts

@@ -39,7 +39,7 @@ export interface CreateAgentRunRequest {
   max_steps?: number
   tool_timeout_seconds?: number
   run_timeout_seconds?: number
-  token_budget?: number
+  token_budget?: number | null
   allow_network?: boolean
   max_concurrent_tools?: number
 }

frontend/src/services/mediaService.ts

@@ -21,6 +21,8 @@ export const mediaService = {
   }),
   revisions: (id: string) => apiClient.get<{items: MediaJob[]}>(`/api/media/transcriptions/${encodeURIComponent(id)}/revisions`),
   note: (id: string, title: string, update_existing = false) => apiClient.post<{note_id: string; title: string}>(`/api/media/transcriptions/${encodeURIComponent(id)}/notes`, { title, update_existing }),
+  artifacts: (id: string, body: {title: string; knowledge_title?: string; provider_id: string; model: string; update_existing?: boolean}) =>
+    apiClient.post<{transcript: {note_id: string; title: string}; knowledge_note: {note_id: string; title: string}}>(`/api/media/transcriptions/${encodeURIComponent(id)}/artifacts`, body),
   audio: (id: string) => resolveApiUrl(`/api/media/attachments/${encodeURIComponent(id)}`),
   impact: (id: string) => apiClient.get<{message:string;retained_note_ids:string[]}>(`/api/media/attachments/${encodeURIComponent(id)}/cleanup-impact`),
   purge: (id: string) => apiClient.delete(`/api/media/attachments/${encodeURIComponent(id)}`),

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('0.5.0')
 })
 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`)

scripts/build-core.py

@@ -61,6 +61,13 @@ def main():
         "--name", "opennexus-core", "--distpath", str(output / "dist"),
         "--workpath", str(output / "work"), "--specpath", str(output),
         "--collect-submodules", "app", "--collect-all", "sqlite_vec",
+        # 本地模型使用独立 Python 进程执行；冻结后的 Core 必须保留可直接运行的 Worker 源文件。
+        "--add-data", str(ROOT / "backend" / "app" / "local_models" / "worker.py") + ":app/local_models",
+        "--add-data", str(ROOT / "backend" / "app" / "local_models" / "protocol.py") + ":app/local_models",
+        # 设置页可以在可写的数据目录中安装模型运行环境，安装器及其锁文件需随 Core 发布。
+        "--add-data", str(ROOT / "backend" / "scripts" / "install-model-runtime.ps1") + ":scripts",
+        "--add-data", str(ROOT / "backend" / "scripts" / "model-requirements.lock") + ":scripts",
+        "--add-data", str(ROOT / "backend" / "scripts" / "model-requirements.txt") + ":scripts",
         "--add-data", str(ROOT / "backend" / "extensions" / "plugins" / "text-tools") + ":extensions/plugins/text-tools",
         "--add-data", str(ROOT / "backend" / "extensions" / "plugins" / "chat-policy") + ":extensions/plugins/chat-policy",
         "--add-data", str(ROOT / "backend" / "extensions" / "skills" / "knowledge-assistant") + ":extensions/skills/knowledge-assistant",

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=0.5.0
 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 **0.5.0**。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-0.5.0.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。
+0.5.0 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: ${OPENNEXUS_SYNC_TAG:-0.5.0}
+    image: opennexus-sync:${OPENNEXUS_SYNC_TAG:-0.5.0}
     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: ${OPENNEXUS_SYNC_TAG:-0.5.0}
+    image: opennexus-sync:${OPENNEXUS_SYNC_TAG:-0.5.0}
     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": "0.5.0",
   "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 = "0.5.0"
 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 = "0.5.0"
 source = { virtual = "." }
 dependencies = [
     { name = "boto3" },