Initial commit: stock analysis backend and prototype UI.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/rag.py

@@ -0,0 +1,37 @@
+"""轻量 RAG：检索与个股/大盘相关的资讯，做情绪标注，作为 LLM 上下文降低幻觉。
+
+当前为基于来源接口 + 关键词情绪的检索式上下文；后续可平滑升级为向量检索（embedding + 向量库）。
+"""
+from __future__ import annotations
+
+import akshare_service as svc
+
+
+def stock_news(symbol: str, limit: int = 5):
+    """返回个股相关资讯（已带利好/利空标注）。"""
+    try:
+        data = svc.get_stock_news(symbol, limit=limit)
+        return data.get("list", [])[:limit]
+    except Exception:
+        return []
+
+
+def _senti_score(items):
+    pos = sum(1 for x in items if x.get("sentiment") == "利好")
+    neg = sum(1 for x in items if x.get("sentiment") == "利空")
+    if pos > neg:
+        return "利好", pos, neg
+    if neg > pos:
+        return "利空", pos, neg
+    return "中性", pos, neg
+
+
+def stock_context(symbol: str, limit: int = 5):
+    """供 AI 诊断使用：检索资讯 + 汇总情绪。"""
+    items = stock_news(symbol, limit)
+    tone, pos, neg = _senti_score(items)
+    block = ""
+    if items:
+        block = "近期相关资讯（检索）：\n" + "\n".join(
+            f"- [{x.get('sentiment','中性')}] {x.get('title','')}（{x.get('time','')}）" for x in items)
+    return {"items": items, "tone": tone, "pos": pos, "neg": neg, "block": block}