release: OpenNexus 0.5.0

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"])