feat: 知识库笔记工坊立项 + contributor 功能 + Fable5 视角文档

- 知识库笔记工坊子项目立项：PRD v1.0 + 寄存条 + CLAUDE.md 登记
- 后端：知识库上传记录 contributor、新增 /contributors 接口
- 前端：知识库列表支持按贡献人筛选
- 新增 Fable5 视角模式库/案例集/建议文档

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/api/knowledge.py

@@ -37,7 +37,7 @@ async def upload_md_files(
             continue
         try:
             content = await f.read()
-            item = svc.store_md_file(content, f.filename)
+            item = svc.store_md_file(content, f.filename, contributor=current_user.display_name or current_user.username)
             results.append({
                 "id": item.id,
                 "title": item.title,
@@ -93,6 +93,16 @@ def list_distinct_sources(
     return [{"source": s} for s in sources]
 
 
+@router.get("/contributors")
+def list_distinct_contributors(
+    session: Session = Depends(get_session),
+    current_user: User = Depends(require_role(UserRole.zhipianren, UserRole.zebian, UserRole.biandao)),
+):
+    svc = KnowledgeService()
+    contributors = svc.get_distinct_contributors()
+    return [{"contributor": c} for c in contributors]
+
+
 @router.get("/grouped")
 def get_grouped_knowledge_items(
     session: Session = Depends(get_session),

backend/app/services/knowledge_service.py

@@ -187,12 +187,16 @@ class KnowledgeService:
         import re
         return re.findall(r"\[\[([^\]]+)\]\]", text)
 
-    def store_md_file(self, file_content: bytes, file_name: str) -> KnowledgeItem:
+    def store_md_file(self, file_content: bytes, file_name: str, contributor: Optional[str] = None) -> KnowledgeItem:
         """
         读取一篇 md 内容，调用 embo-01 拿到向量，写入 knowledge_items + knowledge_embeddings
         """
         parsed = self.parse_md_file(file_content, file_name)
 
+        metadata = parsed["metadata"] or {}
+        if contributor:
+            metadata["contributor"] = contributor
+
         # 调用 embedding（type="db" 表示存入知识库）
         embedding_list = self.embedder.embed_single(parsed["content_md"], embed_type="db")
 
@@ -204,7 +208,7 @@ class KnowledgeService:
                 source_file_name=parsed["source_file_name"],
                 author=parsed["author"],
                 publish_date=parsed["publish_date"],
-                tags=parsed["metadata"],
+                tags=metadata if metadata else None,
                 related_entities=parsed["related_entities"],
             )
             session.add(item)
@@ -244,6 +248,7 @@ class KnowledgeService:
                 # 从 tags(JSONB) 取 source_detail
                 tags = item.tags or {}
                 source_detail = tags.get("source_detail") if isinstance(tags, dict) else None
+                contributor = tags.get("contributor") if isinstance(tags, dict) else None
                 results.append({
                     "id": item.id,
                     "title": item.title,
@@ -252,6 +257,7 @@ class KnowledgeService:
                     "source_type": item.source_type,
                     "source_file_name": item.source_file_name,
                     "source_detail": source_detail,
+                    "contributor": contributor or "栏目冷启动",
                     "created_at": item.created_at,
                 })
             return results
@@ -267,6 +273,17 @@ class KnowledgeService:
                     sources.add(tags["source_detail"])
             return sorted(list(sources))
 
+    def get_distinct_contributors(self) -> list[str]:
+        """返回库里所有不重复的贡献人（从 JSONB 提取），供筛选下拉用。"""
+        with Session(engine) as session:
+            items = session.exec(select(KnowledgeItem)).all()
+            contributors = set()
+            for item in items:
+                tags = item.tags or {}
+                c = tags.get("contributor") if isinstance(tags, dict) else None
+                contributors.add(c or "栏目冷启动")
+            return sorted(list(contributors))
+
     def search_similar(self, query_text: str, top_k: int = 10, min_similarity: float = 0.3) -> list[dict]:
         """
         语义检索：查询句转为向量，用 SQL 余弦距离（<=>）在数据库层检索