feat(accounts): 支持按计划类型过滤图像模型账户

- 添加了按计划类型筛选账户的功能，新增 _account_matches_plan_type 方法
- 扩展了图像模型类型定义，支持 plus、team、pro 计划前缀的模型
- 修改了账户服务中的令牌获取方法，支持 plan_type 参数过滤
- 在前端图像组件中添加了模型选择下拉框，支持新模型类型
- 实现了动态模型列表展示，根据账户类型显示可用的图像模型
- 添加了图像模型的计划类型解析和验证功能
- 更新了 API 接口以支持新的图像模型类型和账户筛选逻辑
- 添加了相关的单元测试验证计划类型过滤功能

services/account_service.py

@@ -126,6 +126,16 @@ class AccountService:
             return True
         return int(account.get("quota") or 0) > 0
 
+    @classmethod
+    def _account_matches_plan_type(cls, account: dict, plan_type: str | None = None) -> bool:
+        if not plan_type:
+            return True
+        normalized_plan = cls._normalize_account_type(plan_type)
+        normalized_account = cls._normalize_account_type(account.get("type"))
+        if not normalized_plan or not normalized_account:
+            return False
+        return normalized_plan.lower() == normalized_account.lower()
+
     @staticmethod
     def _normalize_account_type(value: object) -> str | None:
         raw = str(value or "").strip()
@@ -460,30 +470,45 @@ class AccountService:
         with self._lock:
             return list(self._accounts)
 
-    def _list_ready_candidate_tokens(self, excluded_tokens: set[str] | None = None) -> list[str]:
+    def _list_ready_candidate_tokens(
+            self,
+            excluded_tokens: set[str] | None = None,
+            plan_type: str | None = None,
+    ) -> list[str]:
         excluded = set(excluded_tokens or set())
         return [
             token
             for item in self._accounts.values()
             if self._is_image_account_available(item)
+               and self._account_matches_plan_type(item, plan_type)
                and (token := item.get("access_token") or "")
                and token not in excluded
         ]
 
-    def _list_available_candidate_tokens(self, excluded_tokens: set[str] | None = None) -> list[str]:
+    def _list_available_candidate_tokens(
+            self,
+            excluded_tokens: set[str] | None = None,
+            plan_type: str | None = None,
+    ) -> list[str]:
         max_concurrency = max(1, int(config.image_account_concurrency or 1))
         return [
             token
-            for token in self._list_ready_candidate_tokens(excluded_tokens)
+            for token in self._list_ready_candidate_tokens(excluded_tokens, plan_type)
             if int(self._image_inflight.get(token, 0)) < max_concurrency
         ]
 
-    def _acquire_next_candidate_token(self, excluded_tokens: set[str] | None = None) -> str:
+    def _acquire_next_candidate_token(
+            self,
+            excluded_tokens: set[str] | None = None,
+            plan_type: str | None = None,
+    ) -> str:
         with self._image_slot_condition:
             while True:
-                if not self._list_ready_candidate_tokens(excluded_tokens):
-                    raise RuntimeError("no available image quota")
-                tokens = self._list_available_candidate_tokens(excluded_tokens)
+                if not self._list_ready_candidate_tokens(excluded_tokens, plan_type):
+                    raise RuntimeError(
+                        f"no available {plan_type} image quota" if plan_type else "no available image quota"
+                    )
+                tokens = self._list_available_candidate_tokens(excluded_tokens, plan_type)
                 if tokens:
                     access_token = tokens[self._index % len(tokens)]
                     self._index += 1
@@ -503,10 +528,13 @@ class AccountService:
                 self._image_inflight[access_token] = current_inflight - 1
             self._image_slot_condition.notify_all()
 
-    def get_available_access_token(self) -> str:
+    def get_available_access_token(self, plan_type: str | None = None) -> str:
         attempted_tokens: set[str] = set()
         while True:
-            access_token = self._acquire_next_candidate_token(excluded_tokens=attempted_tokens)
+            access_token = self._acquire_next_candidate_token(
+                excluded_tokens=attempted_tokens,
+                plan_type=plan_type,
+            )
             attempted_tokens.add(access_token)
             try:
                 account = self.fetch_remote_info(access_token, "get_available_access_token")

services/openai_backend_api.py

@@ -15,7 +15,7 @@ from PIL import Image
 from services.account_service import account_service
 from services.config import config
 from services.proxy_service import proxy_settings
-from utils.helper import UpstreamHTTPError, ensure_ok, iter_sse_payloads, new_uuid
+from utils.helper import UpstreamHTTPError, ensure_ok, iter_sse_payloads, new_uuid, split_image_model
 from utils.log import logger
 from utils.pow import build_legacy_requirements_token, build_proof_token, parse_pow_resources
 from utils.turnstile import solve_turnstile_token
@@ -399,13 +399,13 @@ class OpenAIBackendAPI:
 
     def _image_model_slug(self, model: str) -> str:
         """把标准图片模型名映射到底层 model slug。"""
-        model = str(model or "").strip()
-        if not model:
+        _, base_model = split_image_model(model)
+        if not base_model:
             return "auto"
-        if model == "gpt-image-2":
+        if base_model == "gpt-image-2":
             return "gpt-5-3"
-        if model == CODEX_IMAGE_MODEL:
-            return model
+        if base_model == CODEX_IMAGE_MODEL:
+            return base_model
         return "auto"
 
     def _image_headers(self, path: str, requirements: ChatRequirements, conduit_token: str = "", accept: str = "*/*") -> \

services/protocol/conversation.py

@@ -13,7 +13,7 @@ from services.account_service import account_service
 from services.config import config
 from services.image_storage_service import image_storage_service
 from services.openai_backend_api import ImagePollTimeoutError, OpenAIBackendAPI
-from utils.helper import IMAGE_MODELS, extract_image_from_message_content
+from utils.helper import IMAGE_MODELS, extract_image_from_message_content, is_supported_image_model, split_image_model
 from utils.image_tokens import count_image_content_tokens
 from utils.log import logger
 
@@ -488,7 +488,7 @@ def conversation_events(
     quality: str = "auto",
 ) -> Iterator[dict[str, Any]]:
     normalized = normalize_messages(messages or ([{"role": "user", "content": prompt}] if prompt else []))
-    image_model = str(model or "").strip() in IMAGE_MODELS
+    image_model = is_supported_image_model(model)
     history_text = "" if image_model else assistant_history_text(normalized)
     history_messages = [] if image_model else assistant_history_messages(normalized)
     final_prompt = prompt_with_global_system(build_image_prompt(prompt, size, quality)) if image_model else prompt
@@ -623,15 +623,16 @@ def stream_image_outputs(
 
 
 def stream_image_outputs_with_pool(request: ConversationRequest) -> Iterator[ImageOutput]:
-    if str(request.model or "").strip() not in IMAGE_MODELS:
-        raise ImageGenerationError("unsupported image model,supported models: " + ", ".join(IMAGE_MODELS))
+    if not is_supported_image_model(request.model):
+        raise ImageGenerationError("unsupported image model,supported models: " + ", ".join(sorted(IMAGE_MODELS)))
 
     emitted = False
     last_error = ""
     for index in range(1, request.n + 1):
         while True:
             try:
-                token = account_service.get_available_access_token()
+                plan_type, _ = split_image_model(request.model)
+                token = account_service.get_available_access_token(plan_type=plan_type)
             except RuntimeError as exc:
                 if emitted:
                     return

services/protocol/openai_v1_models.py

@@ -2,8 +2,9 @@ from __future__ import annotations
 
 from typing import Any
 
+from services.account_service import account_service
 from services.openai_backend_api import OpenAIBackendAPI
-from utils.helper import IMAGE_MODELS
+from utils.helper import CODEX_IMAGE_MODEL
 
 
 def list_models() -> dict[str, Any]:
@@ -12,7 +13,27 @@ def list_models() -> dict[str, Any]:
     if not isinstance(data, list):
         return result
     seen = {str(item.get("id") or "").strip() for item in data if isinstance(item, dict)}
-    for model in sorted(IMAGE_MODELS):
+    dynamic_models: set[str] = set()
+    accounts = account_service.list_accounts()
+    normalized_types = {
+        normalized
+        for account in accounts
+        if isinstance(account, dict)
+           and (normalized := account_service._normalize_account_type(account.get("type")))
+    }
+
+    if accounts:
+        dynamic_models.add("gpt-image-2")
+    if normalized_types & {"Plus", "Team", "Pro"}:
+        dynamic_models.add(CODEX_IMAGE_MODEL)
+    if "Plus" in normalized_types:
+        dynamic_models.add(f"plus-{CODEX_IMAGE_MODEL}")
+    if "Team" in normalized_types:
+        dynamic_models.add(f"team-{CODEX_IMAGE_MODEL}")
+    if "Pro" in normalized_types:
+        dynamic_models.add(f"pro-{CODEX_IMAGE_MODEL}")
+
+    for model in sorted(dynamic_models):
         if model not in seen:
             data.append({
                 "id": model,

test/test_account_image_capabilities.py

@@ -10,7 +10,7 @@ os.environ.setdefault("CHATGPT2API_AUTH_KEY", "test-auth")
 from services.account_service import AccountService
 from services.auth_service import AuthService
 from services.storage.json_storage import JSONStorageBackend
-from utils.helper import anonymize_token
+from utils.helper import anonymize_token, split_image_model
 
 
 class AccountCapabilityTests(unittest.TestCase):
@@ -66,6 +66,34 @@ class AccountCapabilityTests(unittest.TestCase):
             self.assertEqual(updated["status"], "正常")
             self.assertTrue(updated["image_quota_unknown"])
 
+    def test_split_image_model_supports_plan_type_prefix(self) -> None:
+        self.assertEqual(split_image_model("gpt-image-2"), (None, "gpt-image-2"))
+        self.assertEqual(split_image_model("plus-codex-gpt-image-2"), ("plus", "codex-gpt-image-2"))
+        self.assertEqual(split_image_model("team-codex-gpt-image-2"), ("team", "codex-gpt-image-2"))
+        self.assertEqual(split_image_model("pro-codex-gpt-image-2"), ("pro", "codex-gpt-image-2"))
+        self.assertEqual(split_image_model("plus-gpt-image-2"), (None, None))
+        self.assertEqual(split_image_model("unknown-image-model"), (None, None))
+
+    def test_get_available_access_token_filters_by_plan_type(self) -> None:
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            service = AccountService(JSONStorageBackend(Path(tmp_dir) / "accounts.json"))
+            service.add_account_items(
+                [
+                    {"access_token": "token-plus", "type": "Plus", "status": "正常", "quota": 3},
+                    {"access_token": "token-pro", "type": "Pro", "status": "正常", "quota": 3},
+                ]
+            )
+
+            service.fetch_remote_info = lambda access_token, event="fetch_remote_info": service.get_account(access_token)
+
+            plus_token = service.get_available_access_token(plan_type="plus")
+            pro_token = service.get_available_access_token(plan_type="pro")
+            service.release_image_slot(plus_token)
+            service.release_image_slot(pro_token)
+
+            self.assertEqual(plus_token, "token-plus")
+            self.assertEqual(pro_token, "token-pro")
+
 
 class TokenLogTests(unittest.TestCase):
     def test_anonymize_token_hides_raw_value(self) -> None:

test/test_v1_models.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import json
 import unittest
+from unittest import mock
 
 import requests
 
@@ -13,6 +14,31 @@ BASE_URL = "http://localhost:8000"
 
 
 class ModelListTests(unittest.TestCase):
+    def test_list_models_only_returns_image_models_backed_by_account_types(self):
+        with (
+            mock.patch.object(
+                openai_v1_models.OpenAIBackendAPI,
+                "list_models",
+                return_value={"object": "list", "data": []},
+            ),
+            mock.patch.object(
+                openai_v1_models.account_service,
+                "list_accounts",
+                return_value=[
+                    {"access_token": "token-free", "type": "free"},
+                    {"access_token": "token-team", "type": "Team"},
+                ],
+            ),
+        ):
+            result = openai_v1_models.list_models()
+
+        ids = {item["id"] for item in result["data"]}
+        self.assertIn("gpt-image-2", ids)
+        self.assertIn("codex-gpt-image-2", ids)
+        self.assertIn("team-codex-gpt-image-2", ids)
+        self.assertNotIn("plus-codex-gpt-image-2", ids)
+        self.assertNotIn("pro-codex-gpt-image-2", ids)
+
     def test_list_models_function(self):
         """测试直接调用服务层获取模型列表。"""
         result = openai_v1_models.list_models()

utils/helper.py

@@ -11,7 +11,15 @@ from curl_cffi import requests
 from fastapi import HTTPException
 from utils.log import logger
 
-IMAGE_MODELS = {"gpt-image-2", "codex-gpt-image-2"}
+BASE_IMAGE_MODELS = {"gpt-image-2", "codex-gpt-image-2"}
+IMAGE_MODEL_PLAN_TYPES = ("plus", "team", "pro")
+CODEX_IMAGE_MODEL = "codex-gpt-image-2"
+PREFIXED_CODEX_IMAGE_MODELS = {
+    f"{plan_type}-{CODEX_IMAGE_MODEL}"
+    for plan_type in IMAGE_MODEL_PLAN_TYPES
+}
+IMAGE_MODELS = BASE_IMAGE_MODELS | PREFIXED_CODEX_IMAGE_MODELS
+PUBLIC_IMAGE_MODELS = BASE_IMAGE_MODELS | PREFIXED_CODEX_IMAGE_MODELS
 OUTPUT_DIR = Path(__file__).resolve().parent / "output"
 
 SUPPORTED_JSON_IMAGE_MIME_TYPES = {"image/png", "image/jpeg", "image/jpg", "image/webp", "image/gif"}
@@ -94,10 +102,30 @@ def new_uuid() -> str:
     return str(uuid.uuid4())
 
 
+def split_image_model(model: object) -> tuple[str | None, str | None]:
+    normalized = str(model or "").strip().lower()
+    if not normalized:
+        return None, None
+    if normalized in BASE_IMAGE_MODELS:
+        return None, normalized
+    for plan_type in IMAGE_MODEL_PLAN_TYPES:
+        prefix = f"{plan_type}-"
+        if normalized.startswith(prefix):
+            base_model = normalized[len(prefix):]
+            if base_model == CODEX_IMAGE_MODEL:
+                return plan_type, base_model
+    return None, None
+
+
+def is_supported_image_model(model: object) -> bool:
+    _, base_model = split_image_model(model)
+    return base_model is not None
+
+
 def is_image_chat_request(body: dict[str, object]) -> bool:
     model = str(body.get("model") or "").strip()
     modalities = body.get("modalities")
-    if model in IMAGE_MODELS:
+    if is_supported_image_model(model):
         return True
     return isinstance(modalities, list) and "image" in {str(item or "").strip().lower() for item in modalities}
 

web/src/app/accounts/page.tsx

@@ -43,10 +43,12 @@ import {
 import {
   deleteAccounts,
   fetchAccounts,
+  fetchModels,
   refreshAccounts,
   updateAccount,
   type Account,
   type AccountStatus,
+  type Model,
 } from "@/lib/api";
 import { useAuthGuard } from "@/lib/use-auth-guard";
 import { cn } from "@/lib/utils";
@@ -164,9 +166,21 @@ function displayAccountType(account: Account) {
   return account.type || "Free";
 }
 
+function displayAccountSource(account: Account) {
+  const source = String(account.source_type || "").trim().toLowerCase();
+  if (!source) {
+    return "web";
+  }
+  if (source === "web") {
+    return "web";
+  }
+  return source;
+}
+
 function AccountsPageContent() {
   const didLoadRef = useRef(false);
   const [accounts, setAccounts] = useState<Account[]>([]);
+  const [availableModels, setAvailableModels] = useState<Model[]>([]);
   const [selectedIds, setSelectedIds] = useState<string[]>([]);
   const [query, setQuery] = useState("");
   const [typeFilter, setTypeFilter] = useState("all");
@@ -176,6 +190,7 @@ function AccountsPageContent() {
   const [editingAccount, setEditingAccount] = useState<Account | null>(null);
   const [editStatus, setEditStatus] = useState<AccountStatus>("正常");
   const [isLoading, setIsLoading] = useState(true);
+  const [isLoadingModels, setIsLoadingModels] = useState(true);
   const [isRefreshing, setIsRefreshing] = useState(false);
   const [isDeleting, setIsDeleting] = useState(false);
   const [isUpdating, setIsUpdating] = useState(false);
@@ -198,12 +213,26 @@ function AccountsPageContent() {
     }
   };
 
+  const loadModels = async () => {
+    setIsLoadingModels(true);
+    try {
+      const data = await fetchModels();
+      setAvailableModels(Array.isArray(data.data) ? data.data : []);
+    } catch (error) {
+      const message = error instanceof Error ? error.message : "加载模型列表失败";
+      toast.error(message);
+    } finally {
+      setIsLoadingModels(false);
+    }
+  };
+
   useEffect(() => {
     if (didLoadRef.current) {
       return;
     }
     didLoadRef.current = true;
     void loadAccounts();
+    void loadModels();
   }, []);
 
   const filteredAccounts = useMemo(() => {
@@ -467,6 +496,42 @@ function AccountsPageContent() {
             );
           })}
         </div>
+        <Card className="rounded-2xl border-white/80 bg-white/90 shadow-sm">
+          <CardContent className="p-4">
+            <div className="mb-3 text-sm font-medium text-stone-700">
+              系统可用模型
+              <span className="ml-1 text-stone-400">({availableModels.length})</span>
+            </div>
+            <div className="flex flex-wrap gap-2">
+              {availableModels.length > 0 ? (
+                availableModels.map((model) => (
+                  <button
+                    key={model.id}
+                    type="button"
+                    className="inline-flex cursor-pointer items-center rounded-full border border-stone-200 bg-white px-2.5 py-1 text-xs font-medium text-stone-700 transition hover:border-stone-300 hover:bg-stone-50"
+                    onClick={() => {
+                      void navigator.clipboard.writeText(model.id);
+                      toast.success("模型名已复制");
+                    }}
+                    title={`点击复制 ${model.id}`}
+                  >
+                    <img
+                      src="/openai.svg"
+                      alt=""
+                      aria-hidden="true"
+                      className="mr-1.5 size-3.5 shrink-0"
+                    />
+                    {model.id}
+                  </button>
+                ))
+              ) : isLoadingModels ? (
+                <span className="text-sm text-stone-400">正在加载模型列表...</span>
+              ) : (
+                <span className="text-sm text-stone-400">当前暂无可用模型</span>
+              )}
+            </div>
+          </CardContent>
+        </Card>
       </section>
 
       <section className="space-y-4">
@@ -589,7 +654,7 @@ function AccountsPageContent() {
             </div>
 
             <div className="overflow-x-auto">
-              <table className="w-full min-w-[920px] text-left">
+              <table className="w-full min-w-[1000px] text-left">
                 <thead className="border-b border-stone-100 text-[11px] text-stone-400 uppercase tracking-[0.18em]">
                   <tr>
                     <th className="w-12 px-4 py-3">
@@ -600,6 +665,7 @@ function AccountsPageContent() {
                     </th>
                     <th className="w-56 px-4 py-3">token</th>
                     <th className="w-28 px-4 py-3">类型</th>
+                    <th className="w-24 px-4 py-3">来源</th>
                     <th className="w-24 px-4 py-3">状态</th>
                     <th className="w-56 px-4 py-3">账号信息</th>
                     <th className="w-32 px-4 py-3">创建时间</th>
@@ -654,6 +720,11 @@ function AccountsPageContent() {
                             {displayAccountType(account)}
                           </Badge>
                         </td>
+                        <td className="px-4 py-3">
+                          <Badge variant="outline" className="rounded-md border-stone-200 text-stone-600">
+                            {displayAccountSource(account)}
+                          </Badge>
+                        </td>
                         <td className="px-4 py-3">
                           <Badge
                             variant={status.badge}

web/src/app/image/components/image-composer.tsx

@@ -5,6 +5,7 @@ import { useEffect, useMemo, useRef, useState, type ClipboardEvent, type DragEve
 import { ImageLightbox } from "@/components/image-lightbox";
 import { Button } from "@/components/ui/button";
 import { Input } from "@/components/ui/input";
+import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select";
 import { Textarea } from "@/components/ui/textarea";
 import type { ImageModel } from "@/lib/api";
 import { cn } from "@/lib/utils";
@@ -64,6 +65,9 @@ const qualityOptions = [
 const modelOptions: Array<{ value: ImageModel; label: string }> = [
   { value: "gpt-image-2", label: "gpt-image-2" },
   { value: "codex-gpt-image-2", label: "codex-gpt-image-2" },
+  { value: "plus-codex-gpt-image-2", label: "plus-codex-gpt-image-2" },
+  { value: "team-codex-gpt-image-2", label: "team-codex-gpt-image-2" },
+  { value: "pro-codex-gpt-image-2", label: "pro-codex-gpt-image-2" },
 ];
 
 const aspectOptions = [
@@ -124,13 +128,21 @@ export function ImageComposer({
   const qualityLabel = qualityOptions.find((option) => option.value === imageQuality)?.label || "自动";
   const ratioLabel = imageRatio === "auto" ? "auto" : `${imageRatio}(${imageTier})`;
   const imageSizeLabel = `${qualityLabel} · ${ratioLabel} · ${imageCount || 1} 张`;
+  const selectedModelLabel = modelOptions.find((option) => option.value === imageModel)?.label || imageModel;
 
   useEffect(() => {
     if (!isSizeMenuOpen) {
       return;
     }
     const handlePointerDown = (event: MouseEvent) => {
-      if (!sizeMenuRef.current?.contains(event.target as Node)) {
+      const target = event.target;
+      if (
+        target instanceof Element &&
+        target.closest('[data-slot="select-content"], [data-slot="select-trigger"]')
+      ) {
+        return;
+      }
+      if (!sizeMenuRef.current?.contains(target as Node)) {
         setIsSizeMenuOpen(false);
       }
     };
@@ -346,24 +358,41 @@ export function ImageComposer({
                         <h3 className="mb-3 text-base font-semibold text-stone-950">图像设置</h3>
                         <div className="mb-3">
                           <div className="mb-2 text-sm font-medium text-stone-900">模型</div>
-                          <div className="grid grid-cols-2 gap-2">
-                            {modelOptions.map((option) => {
-                              const active = option.value === imageModel;
-                              return (
-                                <button
+                          <Select
+                            value={imageModel}
+                            onValueChange={(value) => {
+                              onImageModelChange(value as ImageModel);
+                            }}
+                          >
+                            <SelectTrigger className="h-10 rounded-xl border-stone-200 bg-white text-sm shadow-none">
+                              <div className="flex min-w-0 items-center gap-2">
+                                <img
+                                  src="/openai.svg"
+                                  alt=""
+                                  aria-hidden="true"
+                                  className="size-4 shrink-0 text-stone-700"
+                                />
+                                <span className="truncate">{selectedModelLabel}</span>
+                              </div>
+                            </SelectTrigger>
+                            <SelectContent className="z-[120]">
+                              {modelOptions.map((option) => (
+                                <SelectItem
                                   key={option.value}
-                                  type="button"
-                                  className={cn(
-                                    "h-9 cursor-pointer rounded-full border border-stone-200 bg-white px-3 text-sm text-stone-800 transition hover:border-stone-300 hover:bg-stone-50",
-                                    active && "border-stone-950 bg-white font-medium text-stone-950",
-                                  )}
-                                  onClick={() => onImageModelChange(option.value)}
+                                  value={option.value}
+                                  className="pl-10"
+                                  style={{
+                                    backgroundImage: "url('/openai.svg')",
+                                    backgroundRepeat: "no-repeat",
+                                    backgroundPosition: "12px center",
+                                    backgroundSize: "16px 16px",
+                                  }}
                                 >
                                   {option.label}
-                                </button>
-                              );
-                            })}
-                          </div>
+                                </SelectItem>
+                              ))}
+                            </SelectContent>
+                          </Select>
                         </div>
                         <div className="mb-3">
                           <div className="mb-2 text-sm font-medium text-stone-900">质量</div>

web/src/app/image/page.tsx

@@ -50,6 +50,13 @@ const IMAGE_QUALITY_STORAGE_KEY = "chatgpt2api:image_last_quality";
 const IMAGE_MODEL_STORAGE_KEY = "chatgpt2api:image_last_model";
 const IMAGE_COUNT_STORAGE_KEY = "chatgpt2api:image_last_count";
 const SCROLL_TO_LATEST_THRESHOLD = 160;
+const SUPPORTED_IMAGE_MODELS: ImageModel[] = [
+  "gpt-image-2",
+  "codex-gpt-image-2",
+  "plus-codex-gpt-image-2",
+  "team-codex-gpt-image-2",
+  "pro-codex-gpt-image-2",
+];
 
 function clampImageCount(value: string) {
   return String(Math.min(100, Math.max(1, Math.floor(Number(value) || 1))));
@@ -118,6 +125,10 @@ function dataUrlToFile(dataUrl: string, fileName: string, mimeType?: string) {
   return new File([bytes], fileName, { type: mimeType || matchedMimeType || "image/png" });
 }
 
+function normalizeStoredImageModel(value: string | null): ImageModel {
+  return SUPPORTED_IMAGE_MODELS.includes(value as ImageModel) ? (value as ImageModel) : "gpt-image-2";
+}
+
 function buildReferenceImageFromResult(image: StoredImage, fileName: string): StoredReferenceImage | null {
   if (!image.b64_json) {
     return null;
@@ -481,7 +492,7 @@ function ImagePageContent({ isAdmin }: { isAdmin: boolean }) {
         setImageWidth("1024");
         setImageHeight("1024");
         setImageQuality(storedQuality || "auto");
-        setImageModel(storedModel === "codex-gpt-image-2" ? "codex-gpt-image-2" : "gpt-image-2");
+        setImageModel(normalizeStoredImageModel(storedModel));
         setImageCount(storedCount ? clampImageCount(storedCount) : "1");
 
         const items = await listImageConversations();

web/src/lib/api.ts

@@ -2,7 +2,12 @@ import { httpRequest, request } from "@/lib/request";
 
 export type AccountType = string;
 export type AccountStatus = "正常" | "限流" | "异常" | "禁用";
-export type ImageModel = "gpt-image-2" | "codex-gpt-image-2";
+export type ImageModel =
+  | "gpt-image-2"
+  | "codex-gpt-image-2"
+  | "plus-codex-gpt-image-2"
+  | "team-codex-gpt-image-2"
+  | "pro-codex-gpt-image-2";
 export type AuthRole = "admin" | "user";
 export type ImageStorageMode = "local" | "webdav" | "both";
 
@@ -19,6 +24,7 @@ export type ImageStorageSettings = {
 export type Account = {
   access_token: string;
   type: AccountType;
+  source_type?: string | null;
   status: AccountStatus;
   quota: number;
   image_quota_unknown?: boolean;
@@ -36,10 +42,25 @@ export type Account = {
   last_used_at?: string | null;
 };
 
+export type Model = {
+  id: string;
+  object: string;
+  created: number;
+  owned_by: string;
+  permission: unknown[];
+  root: string;
+  parent: string | null;
+};
+
 type AccountListResponse = {
   items: Account[];
 };
 
+type ModelListResponse = {
+  object: string;
+  data: Model[];
+};
+
 type AccountMutationResponse = {
   items: Account[];
   added?: number;
@@ -267,6 +288,10 @@ export async function fetchAccounts() {
   return httpRequest<AccountListResponse>("/api/accounts");
 }
 
+export async function fetchModels() {
+  return httpRequest<ModelListResponse>("/v1/models");
+}
+
 export async function createAccounts(tokens: string[]) {
   return httpRequest<AccountMutationResponse>("/api/accounts", {
     method: "POST",