feat: dual LLM mode (default via .env, custom per-request) for AI analysis

requirements/views.py

@@ -1,3 +1,4 @@
+import json
 import logging
 
 from django.db import transaction
@@ -12,6 +13,26 @@ from .models import Requirement, Submission
 logger = logging.getLogger(__name__)
 
 
+def _parse_llm_override(request) -> dict:
+    raw = request.data.get("llm")
+    if not raw:
+        return {}
+    if isinstance(raw, str):
+        try:
+            raw = json.loads(raw)
+        except json.JSONDecodeError:
+            return {}
+    return raw if isinstance(raw, dict) else {}
+
+
+def _validate_llm_override(override: dict) -> str | None:
+    if override.get("mode") != "custom":
+        return None
+    if not (override.get("base_url") or "").strip() or not (override.get("model") or "").strip():
+        return "custom 模式必须提供 llm.base_url 和 llm.model"
+    return None
+
+
 @api_view(["POST"])
 @permission_classes([IsAuthenticated])
 @transaction.atomic
@@ -20,13 +41,19 @@ def create_requirement(request):
     content = (request.data.get("content") or "").strip()
     if not title or not content:
         return Response({"detail": "title 和 content 不能为空"}, status=status.HTTP_400_BAD_REQUEST)
+    override = _parse_llm_override(request)
+    err = _validate_llm_override(override)
+    if err:
+        return Response({"detail": err}, status=status.HTTP_400_BAD_REQUEST)
     try:
-        spec = analyze_requirements(content)
+        spec = analyze_requirements(content, override)
     except Exception:
         logger.exception("AI 分析作业要求失败, 使用默认检测计划")
         from .llm import _default_spec
         spec = _default_spec()
-    requirement = Requirement.objects.create(title=title, content=content, spec=spec)
+    requirement = Requirement.objects.create(
+        title=title, content=content, spec=spec, llm_config=override,
+    )
     from .serializers import RequirementSerializer
     return Response(RequirementSerializer(requirement).data, status=status.HTTP_201_CREATED)