改成导excel

backend/app/routes/spam_routes.py

@@ -1,4 +1,4 @@
-from flask import Blueprint, current_app, request
+from flask import Blueprint, current_app, request, send_file, after_this_request
 from flask_jwt_extended import jwt_required
 
 from app.extensions import db
@@ -367,3 +367,56 @@ def import_samples():
 
     db.session.commit()
     return ok({"created": created, "updated": updated}, "样本导入完成")
+
+
+@spam_bp.post("/export/xlsx")
+@jwt_required()
+def export_xlsx():
+    user = current_user()
+    if not user:
+        return fail("用户不存在", 404)
+
+    payload = request.get_json(silent=True) or {}
+    items = payload.get("items") or []
+    if not isinstance(items, list) or not items:
+        return fail("items 必须是非空数组", 400)
+
+    import os
+    import tempfile
+    import pandas as pd
+
+    rows = []
+    for item in items:
+        tokens = item.get("reason_tokens") or []
+        token_str = "; ".join(t.get("token", "") for t in tokens) if isinstance(tokens, list) else ""
+        prediction_text = "垃圾信息" if item.get("prediction") == "spam" else "正常信息"
+
+        rows.append({
+            "文本": item.get("text", ""),
+            "判定结果": prediction_text,
+            "分类标签": item.get("category_label", ""),
+            "置信度": f"{float(item.get("confidence", 0) or 0) * 100:.2f}%",
+            "垃圾概率": f"{float(item.get("spam_probability", 0) or 0) * 100:.2f}%",
+            "正常概率": f"{float(item.get("ham_probability", 0) or 0) * 100:.2f}%",
+            "风险关键词": token_str,
+        })
+
+    df = pd.DataFrame(rows)
+    tmp = tempfile.NamedTemporaryFile(suffix=".xlsx", delete=False)
+    tmp.close()
+    df.to_excel(tmp.name, index=False, engine="openpyxl")
+
+    @after_this_request
+    def cleanup(response):
+        try:
+            os.unlink(tmp.name)
+        except Exception:
+            pass
+        return response
+
+    return send_file(
+        tmp.name,
+        mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+        as_attachment=True,
+        download_name="batch_detect.xlsx",
+    )