feat(regulatory): 为核查流程增加LLM复核记录

review_agent/regulatory_review/services/llm_review.py

@@ -1,10 +1,13 @@
 from __future__ import annotations
 
 import json
+import os
 import re
 from collections.abc import Callable
 from typing import Any
 
+from django.conf import settings
+
 from review_agent.llm import LLMConfigurationError, LLMRequestError, generate_completion
 
 
@@ -22,6 +25,16 @@ def review_condition_fields(
     llm_fields: dict[str, str] = {}
     status = "skipped"
     error_message = ""
+    if not _should_call_llm(completion_func):
+        selected_fields, selected_sources = _select_fields(rule_fields, llm_fields)
+        return {
+            "status": status,
+            "error_message": error_message,
+            "rule_fields": _clean_fields(rule_fields),
+            "llm_fields": llm_fields,
+            "selected_fields": selected_fields,
+            "selected_sources": selected_sources,
+        }
     try:
         raw = (completion_func or generate_completion)(_condition_messages(text, rule_fields, file_context), temperature=0.0)
         payload = _parse_json_object(raw)
@@ -48,6 +61,13 @@ def review_workflow_payload(
     payload: dict[str, Any],
     completion_func: Callable[..., str] | None = None,
 ) -> dict[str, Any]:
+    if not _should_call_llm(completion_func):
+        return {
+            "status": "skipped",
+            "stage": stage,
+            "result": {},
+            "error_message": "",
+        }
     try:
         raw = (completion_func or generate_completion)(_workflow_messages(stage, payload), temperature=0.0)
         parsed = _parse_json_object(raw)
@@ -122,6 +142,14 @@ def _parse_json_object(raw: str) -> dict[str, Any]:
     return parsed
 
 
+def _should_call_llm(completion_func: Callable[..., str] | None) -> bool:
+    if completion_func is not None:
+        return True
+    if os.environ.get("PYTEST_CURRENT_TEST") and not getattr(settings, "REGULATORY_LLM_REVIEW_ALLOW_TEST_CALLS", False):
+        return False
+    return bool(settings.LLM_API_KEY and settings.LLM_MODEL)
+
+
 def _clean_fields(fields: dict[str, Any]) -> dict[str, str]:
     clean = {}
     for label in FIELD_LABELS: