zyc
ce7eaefe1d
本轮(生图模型选择 + 火山接入): - 工作室新增「生图模型」选择器(模特上身图/平台套图头部 chip + 图片创作底部 Pill), 默认火山 Seedream,可切 gpt-image-2;选择写入 localStorage,下次进页面读回 - 后端 resolve_image_model 解析所选模型;enqueue_standalone_images 接 image_model - worker 按模型能力分流:有 image_edit(gpt-image)走多图编辑;无(火山)走 image_generation(image=参考图);新增 _ratio_to_volcano_size 让火山按比例出图 → 内衣等敏感品类用火山可绕开 gpt-image 的 sexual 内容审核 模特上身图提示词: - 穿戴/非穿戴分流、按 index 变化动作场景镜头、负面词尾接、多图参考序号自适应 - _product_reference_urls:商品参考真实上传图优先、排除 AI 生成图、可多张 其他(并入此前各会话未提交改动): - 图片创作多会话(ImageConversation + migration 0019)、任务中心按类型过滤 - accounts/projects/assets/team/auth 等零散调整、相关测试 - 测试脚本(tryon_*.py)、测试清单(core/bug/*.xlsx)
198 lines
10 KiB
Python
198 lines
10 KiB
Python
from django.db.models import Count
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from django.utils import timezone
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from rest_framework import status
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from rest_framework.decorators import action
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from rest_framework.response import Response
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from rest_framework.views import APIView
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from rest_framework.viewsets import ModelViewSet, ReadOnlyModelViewSet
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from apps.assets.serializers import AssetSerializer
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from apps.common.api import TeamScopedViewSetMixin, get_current_team
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from apps.common.celery_health import require_worker
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from .models import AITask, ImageConversation, ModelConfig
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from .serializers import AITaskSerializer, ImageConversationSerializer, ModelConfigSerializer
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from .services import enqueue_standalone_images
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class GenerateImageView(APIView):
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"""独立生图(不绑项目)· 图片创作/模特图/平台套图共用 —— **异步**。
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POST /api/ai/generate-image/ 提交生成,秒级返回 RESERVED 任务列表(慢出图交给 worker)。
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GET /api/ai/generate-image/?ids=… 轮询这些任务的状态;成功的任务带回成图 asset。
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"""
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def post(self, request):
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require_worker() # 异步出图依赖 worker 兜底执行,没 worker 直接拒绝(否则任务永远 RESERVED)
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prompt = str(request.data.get("prompt") or "").strip()
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if not prompt:
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return Response({"detail": "prompt 不能为空"}, status=status.HTTP_400_BAD_REQUEST)
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mode = str(request.data.get("mode") or "image")
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try:
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count = int(request.data.get("count") or 1)
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except (TypeError, ValueError):
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count = 1
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product_id = str(request.data.get("product_id") or "").strip() or None
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reference_product = bool(request.data.get("reference_product"))
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model_id = str(request.data.get("model_id") or "").strip() or None
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model_entity_id = str(request.data.get("model_entity_id") or "").strip() or None
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ratio = str(request.data.get("ratio") or "").strip() or None
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image_model = str(request.data.get("image_model") or "").strip() or None
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conversation_id = str(request.data.get("conversation_id") or "").strip() or None
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# 用户在图片创作里上传的参考图(已先传成 Asset),按 id 列表带入 → 生成时作多图参考(image_edit)
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raw_refs = request.data.get("reference_image_ids") or []
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if isinstance(raw_refs, str):
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raw_refs = [s for s in raw_refs.split(",") if s.strip()]
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reference_image_ids = [str(r).strip() for r in raw_refs if str(r).strip()]
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team = get_current_team(request.user)
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# 对话归属:传了 id 就用现成对话(限本团队);没传则自动开一条新对话,标题取 prompt 前 24 字。
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conversation = None
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if conversation_id:
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conversation = ImageConversation.objects.filter(team=team, id=conversation_id, is_deleted=False).first()
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if conversation is None:
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conversation = ImageConversation.objects.create(
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team=team,
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created_by=request.user,
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mode=mode if mode in dict(ImageConversation.Mode.choices) else ImageConversation.Mode.IMAGE,
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product_id=product_id,
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title=(prompt[:24] or "默认创作"),
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)
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try:
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tasks = enqueue_standalone_images(team=team, user=request.user, prompt=prompt, mode=mode, count=count, product_id=product_id, reference_product=reference_product, model_id=model_id, model_entity_id=model_entity_id, ratio=ratio, image_model=image_model, conversation=conversation, reference_image_ids=reference_image_ids)
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except ValueError as exc: # 无可用模型 / 余额不足等,立即反馈
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return Response({"detail": str(exc)}, status=status.HTTP_400_BAD_REQUEST)
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# 本次提交即刷新对话活跃时间,左栏「最近」据此置顶
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ImageConversation.objects.filter(id=conversation.id).update(last_active_at=timezone.now())
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return Response(
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{"conversation_id": str(conversation.id), "tasks": [{"id": str(t.id), "status": t.status} for t in tasks]},
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status=status.HTTP_202_ACCEPTED,
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)
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def get(self, request):
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team = get_current_team(request.user)
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ids = [s for s in str(request.query_params.get("ids") or "").split(",") if s]
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if not ids:
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return Response({"tasks": []})
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tasks = AITask.objects.filter(team=team, id__in=ids).prefetch_related(
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"generated_assets", "generated_assets__files"
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)
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data = [
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{
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"id": str(t.id),
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"status": t.status,
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"error_message": t.error_message,
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"assets": AssetSerializer(
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[a for a in t.generated_assets.all() if not a.is_deleted], many=True
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).data,
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}
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for t in tasks
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]
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return Response({"tasks": data})
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class AITaskViewSet(TeamScopedViewSetMixin, ReadOnlyModelViewSet):
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# 序列化器不含 request_payload/response_payload(单条可达 3MB+ base64 图),defer 掉:
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# 否则只为序列化 14 个小字段也会把几十 MB blob 从库里拉回(远程库实测 40 条要 30s+)。
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# 默认按创建时间倒序:任务中心 = 历史流水,最新的(多为成功)排最前。
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# 缺省排序时 MySQL 按主键(UUID)乱序返回,会把一批旧失败记录顶到首页,
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# 前端只取首页 → 误判「全部失败」。order_by 保证稳定且新任务优先。
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queryset = AITask.objects.select_related("team", "project", "model_config", "model_config__provider").defer("request_payload", "response_payload").order_by("-created_at")
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serializer_class = AITaskSerializer
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search_fields = ["idempotency_key", "provider_task_id", "project__name"]
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ordering_fields = ["created_at", "updated_at", "completed_at"]
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def get_queryset(self):
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# 可选 ?task_type=a,b,c 过滤:生图工作室的任务中心只想看生图任务(模特上身图/平台套图/
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# 图片创作 = person_image / product_image),不掺脚本/实体抽取/故事板等流水线内部任务。
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queryset = super().get_queryset()
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# 从 request_payload(已 defer)里只抽 batch_id / mode 两个 JSON 标量供前端「按批分组 + 标签」用:
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# KeyTextTransform 在 SQL 层 JSON_EXTRACT,不会把几 MB 的 payload 整列拉回(避开 payload 性能坑)。
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from django.db.models.fields.json import KeyTextTransform
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queryset = queryset.annotate(
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rp_batch_id=KeyTextTransform("batch_id", "request_payload"),
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rp_mode=KeyTextTransform("mode", "request_payload"),
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)
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raw = self.request.query_params.get("task_type", "").strip()
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if raw:
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types = [t.strip() for t in raw.split(",") if t.strip()]
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if types:
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queryset = queryset.filter(task_type__in=types)
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return queryset
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class ImageConversationViewSet(TeamScopedViewSetMixin, ModelViewSet):
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"""图片创作工作室的「对话」CRUD。
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list 按 ?mode= 过滤、排除软删、按 last_active_at 倒序(左栏「最近」);
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create 开新对话;partial_update 重命名;destroy 软删(不连带删图)。
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detail action `tasks` 返回该对话下的生图任务 + 成图 asset,供切换对话时回填批次流。
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"""
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serializer_class = ImageConversationSerializer
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queryset = ImageConversation.objects.filter(is_deleted=False).select_related("product").order_by("-last_active_at")
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def get_queryset(self):
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queryset = super().get_queryset().annotate(_task_count=Count("tasks"))
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mode = self.request.query_params.get("mode", "").strip()
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if mode:
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queryset = queryset.filter(mode=mode)
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return queryset
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def perform_destroy(self, instance):
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# 软删:对话从列表消失,但其 AITask.conversation 置空由 DB on_delete=SET_NULL 不触发(我们没真删),
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# 成图始终留在资产库。仅打标记。
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instance.is_deleted = True
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instance.save(update_fields=["is_deleted", "updated_at"])
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@action(detail=True, methods=["get"])
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def tasks(self, request, pk=None):
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from apps.assets.models import Asset
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from apps.assets.serializers import _asset_preview
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conversation = self.get_object()
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tasks = (
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AITask.objects.filter(conversation=conversation)
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.prefetch_related("generated_assets", "generated_assets__files")
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.order_by("created_at")
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)
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# 参考图 id → {name,url}:跨任务可能重复,缓存一次解析,供切换/刷新后批次头回显「参考了哪些图」
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ref_cache: dict[str, dict] = {}
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def resolve_refs(ids):
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out = []
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for rid in ids or []:
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rid = str(rid)
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if rid not in ref_cache:
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a = Asset.objects.filter(id=rid).prefetch_related("files").first()
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ref_cache[rid] = {"name": a.name, "url": _asset_preview(a)} if a else None
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if ref_cache[rid]:
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out.append(ref_cache[rid])
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return out
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data = [
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{
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"id": str(t.id),
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"status": t.status,
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"error_message": t.error_message,
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"prompt": (t.request_payload or {}).get("prompt", ""),
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"batch_id": (t.request_payload or {}).get("batch_id", ""),
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"ratio": (t.request_payload or {}).get("ratio") or "",
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"reference_images": resolve_refs((t.request_payload or {}).get("reference_image_ids")),
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"created_at": t.created_at,
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"assets": AssetSerializer(
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[a for a in t.generated_assets.all() if not a.is_deleted], many=True
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).data,
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}
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for t in tasks
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]
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return Response({"conversation_id": str(conversation.id), "tasks": data})
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class ModelConfigViewSet(ReadOnlyModelViewSet):
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# 按创建序固定排序:最早创建的 active 模型排第一 = 前端选择器默认项,与 get_default_model 口径一致
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# (否则 DB 默认序不稳定,可能默认选到 Gemini 等;用户要默认 = 豆包 2.0 Pro,它最早创建)
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queryset = ModelConfig.objects.select_related("provider").filter(status=ModelConfig.Status.ACTIVE).order_by("created_at")
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serializer_class = ModelConfigSerializer
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search_fields = ["name", "display_name", "capability"]
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ordering_fields = ["created_at", "display_name"]
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