Add explain analysis workflow and UI

backend/explain/category_engine.py

@@ -0,0 +1,69 @@
+# -*- coding: utf-8 -*-
+"""Rule-based news categorization for explain UI."""
+
+from __future__ import annotations
+
+from typing import Any, Dict, Iterable
+
+
+CATEGORY_KEYWORDS = {
+    "market": [
+        "market", "stock", "rally", "sell-off", "selloff", "trading",
+        "wall street", "s&p", "nasdaq", "dow", "index", "bull", "bear",
+        "correction", "volatility",
+    ],
+    "policy": [
+        "regulation", "fed", "federal reserve", "tariff", "sanction",
+        "interest rate", "policy", "government", "congress", "sec",
+        "trade war", "ban", "legislation", "tax",
+    ],
+    "earnings": [
+        "earnings", "revenue", "profit", "quarter", "eps", "guidance",
+        "forecast", "income", "sales", "beat", "miss", "outlook",
+        "financial results",
+    ],
+    "product_tech": [
+        "product", "ai", "chip", "cloud", "launch", "patent",
+        "technology", "innovation", "release", "platform", "model",
+        "software", "hardware", "gpu", "autonomous",
+    ],
+    "competition": [
+        "competitor", "rival", "market share", "overtake", "compete",
+        "competition", "vs", "versus", "battle", "challenge",
+    ],
+    "management": [
+        "ceo", "executive", "resign", "layoff", "restructure",
+        "management", "leadership", "appoint", "hire", "board",
+        "chairman",
+    ],
+}
+
+
+def categorize_news_rows(rows: Iterable[Dict[str, Any]]) -> Dict[str, Dict[str, Any]]:
+    """Bucket news rows by keyword categories."""
+    categories: Dict[str, Dict[str, Any]] = {
+        key: {
+            "label": key,
+            "count": 0,
+            "article_ids": [],
+        }
+        for key in CATEGORY_KEYWORDS
+    }
+
+    for row in rows:
+        text = " ".join(
+            [
+                str(row.get("title") or ""),
+                str(row.get("summary") or ""),
+                str(row.get("related") or ""),
+                str(row.get("category") or ""),
+            ]
+        ).lower()
+        article_id = row.get("id")
+        for category, keywords in CATEGORY_KEYWORDS.items():
+            if any(keyword in text for keyword in keywords):
+                categories[category]["count"] += 1
+                if article_id:
+                    categories[category]["article_ids"].append(article_id)
+
+    return categories