实现Agent对话，合格自动提交，不合格补充材料的能力

src/pipeline.py

@@ -22,6 +22,7 @@ from . import get_logger
 from .config import load_config
 from .doc.extractor import extract_invoices
 from .doc.invoice import (
+    classify_invoice_batch,
     save_application_json,
     save_invoice_csv,
 )
@@ -35,25 +36,6 @@ from .doc.llm_extractor import (
     load_cache,
 )
 
-
-def _classify_invoice_batch(
-    invoices: list[dict[str, str]],
-) -> dict[str, list[dict[str, str]]]:
-    """按发票类型分组"""
-    travel: list[dict[str, str]] = []
-    general: list[dict[str, str]] = []
-    application: list[dict[str, str]] = []
-    for inv in invoices:
-        inv_type = inv.get("invoice_type", "general")
-        if inv_type == "application":
-            application.append(inv)
-        elif inv_type in ("train", "hotel"):
-            travel.append(inv)
-        else:
-            general.append(inv)
-    return {"travel": travel, "general": general, "application": application}
-
-
 log = get_logger("pipeline")
 
 
@@ -63,7 +45,7 @@ def _classify_from_cache(cache_path: Path) -> dict[str, list[dict[str, Any]]]:
 
     cache_map = load_cache(cache_path)
     invoices = [data for data in cache_map.values() if data.get("invoice_type") not in ("application", "payment")]
-    return _classify_invoice_batch(invoices)
+    return classify_invoice_batch(invoices)
 
 
 def _extract_travel_info_if_needed(groups: dict[str, list[dict[str, Any]]], cache_path: Path) -> dict[str, Any] | None: