feat: GEO/SEO structured data + search ranking tracker

platform/backend/app/api/topics.py

@@ -9,7 +9,9 @@ from ..database import get_db
 from ..models import Topic, TopicField, TopicConfigField, Article, ContentMetrics
 from ..schemas import (
     TopicCreate, TopicUpdate, TopicResponse, TopicScoreRequest,
+    TopicAnalyzeRequest, TopicAnalyzeResponse,
 )
+from ..core.nvidia_client import call_llm
 from .auth import get_current_user, org_filter
 
 router = APIRouter(prefix="/api/topics", tags=["topics"], dependencies=[Depends(get_current_user)])
@@ -93,6 +95,65 @@ def topic_stats(
     }
 
 
+@router.post("/analyze", response_model=TopicAnalyzeResponse)
+def analyze_topic(
+    data: TopicAnalyzeRequest,
+    db: Session = Depends(get_db),
+    current_user=Depends(get_current_user)
+):
+    """AI 分析用户输入的选题思路，返回结构化的选题信息"""
+    import json, re
+    from sqlalchemy import text as sa_text
+
+    refs = "\n".join(f"- {link}" for link in data.reference_links) if data.reference_links else "无"
+    prompt_text = f"""你是一个专业的内容策略师。用户提供了一个选题思路，请分析并提炼为结构化的选题信息。
+
+用户输入的原始内容：
+{data.raw_input}
+
+参考链接（如有）：
+{refs}
+
+请输出 JSON（只输出 JSON，不要其他文字）：
+{{
+  "title": "优化后的选题标题（20字内，含核心关键词，有吸引力）",
+  "format": "内容形式（趋势洞察/实操指南/对比分析/案例解读/观点讨论）",
+  "core_concept": "核心观点（一句话说清独特价值，20字内）",
+  "audience_pain": "受众痛点（目标读者的真实困惑或需求，20字内）",
+  "unique_angle": "差异化切入点（与常见文章不同的视角，20字内）",
+  "tags": ["标签1", "标签2", "标签3", "标签4", "标签5"]
+}}"""
+
+    try:
+        resp = call_llm(prompt_text, temperature=0.6, max_tokens=1500)
+    except Exception as e:
+        raise HTTPException(status_code=503, detail=f"AI 分析失败: {str(e)}")
+
+    # Parse JSON from response
+    resp = resp.strip()
+    # Remove markdown code fences if present
+    resp = re.sub(r'^```(?:json)?\s*', '', resp)
+    resp = re.sub(r'\s*```$', '', resp)
+    parsed = json.loads(resp)
+
+    field_name = None
+    if data.field_id:
+        field = db.query(TopicField).filter(TopicField.id == data.field_id).first()
+        if field:
+            field_name = field.name
+
+    return TopicAnalyzeResponse(
+        title=parsed.get("title", ""),
+        format=parsed.get("format", ""),
+        core_concept=parsed.get("core_concept", ""),
+        audience_pain=parsed.get("audience_pain", ""),
+        unique_angle=parsed.get("unique_angle", ""),
+        field_name=field_name,
+        tags=parsed.get("tags", []),
+        priority="中",
+    )
+
+
 @router.post("", response_model=TopicResponse)
 def create_topic(
     data: TopicCreate,
@@ -111,7 +172,7 @@ def create_topic(
         else:
             topic_id = f"T{datetime.now().strftime('%m%d%H%M')}"
 
-    field_name = None
+    field_name = "未分类"
     if data.field_id:
         field = db.query(TopicField).filter(TopicField.id == data.field_id).first()
         if field:
@@ -164,7 +225,7 @@ def update_topic(
         topic.field_id = data.field_id
         if data.field_id:
             field = db.query(TopicField).filter(TopicField.id == data.field_id).first()
-            topic.field_name = field.name if field else None
+            topic.field_name = field.name if field else '未分类'
 
     for k, v in data.model_dump(exclude_unset=True, exclude={"field_id"}).items():
         if k == "tags" or k == "custom_data" or k == "scoring_data":