整理图片 provider 模块层次并拆出 raw edit

将 raw image edit 提取到独立 raw_image_edit 模块

按 protocol、runtime、transport 目录收拢 image_provider 实现

同步后端架构与 raw edit 技术文档路径

CONTEXT.md

@@ -44,6 +44,35 @@ _Avoid_: 把同一资源的全局元数据和某一次摆放坐标混在同一
 由图片生成或图片修改流程产生的画布资源，必须记录来源资源、提示词、实际提示词、模型、provider、任务 ID 和生成时间；本期 `/editor` 的生成修改先允许 mock 生成资源，但仍按生成资源元数据形状保存。
 _Avoid_: 无来源的静态素材、只显示在 UI 但不落工程资源记录的生成结果
 
+**图片模型历史值与使用端解析**:
+图片资源中已持久化的 `gpt-image-2` 是历史业务事实，读回时保持原值；新任务使用业务模型值 `gpt-image-2.5`。当用户基于历史资源再次发起生成或编辑任务时，服务端只在新任务的使用端把历史值解析为当前业务模型，不改写历史资源。provider route 属于服务端执行与审计边界，前端不接收、不持久化、不展示，也不据此分支。
+_Avoid_: 读取数据库时改写历史模型值、把 provider route 暴露为前端模型选项或公开 DTO
+
+**图片 provider 显式路由**:
+api-server 在任务入口按业务语义显式选择具体 provider model name（生成或编辑），并把同一具体名传给图片平台适配器和后台定价解析；图片平台适配器不从参考图数量或前端字段猜测任务。具体 provider model name 只存在于服务端调用、定价配置和审计边界。
+后台管理 Web/API 是明确例外，可以查看和编辑两个具体定价 key；主站普通前端与公开定价 API 不接收这些 key。
+_Avoid_: 让图片适配器隐式猜路由、让主站前端携带 provider model name
+
+**业务模型**:
+面向任务与产品契约的稳定模型值；当前 GPT 图片新任务的业务模型是 `gpt-image-2.5`。业务模型不等同于 provider 的具体计费/请求 model，也不暴露 provider 凭证或 endpoint。
+_Avoid_: 把 provider concrete model 当作前端业务选项、用业务模型值直接推断 provider 凭证
+
+**具体模型**:
+服务端发送请求和定价使用的 concrete model name。GPT Image 2.5 生成与编辑分别是 `gpt-image-2.5-flare-c` 和 `gpt-image-2.5-sunburst-c`；nanobanana 仍使用 `gemini-3.1-flash-image-preview`。具体模型只在服务端执行、定价和审计边界出现。
+_Avoid_: 把具体模型写入普通前端 DTO、让未知字符串自动选择 provider
+
+**provider client**:
+按具体模型选出的外部图片 provider 连接配置，包含 provider identity、base URL 和 API key；VectorEngine 与 Tiantoken client 共享图片协议执行器，不复制请求/响应业务逻辑。两套 required client 在 api-server 启动时构造。
+_Avoid_: 在首次请求时才创建 client、在 provider client 中复制尺寸/重试/审计逻辑、跨 provider credential fallback
+
+**历史模型值**:
+已持久化的 `gpt-image-2` 或 `gpt-image-2-c` 字符串，只作为历史事实原样读取和审计；基于历史资源提交新任务时，在使用端解析为当前 GPT Image 2.5 业务任务，不回写历史记录，也不把旧值作为现役 provider route。
+_Avoid_: 数据库批量改写历史值、把历史值重新路由到 VectorEngine、把兼容解析扩散到普通前端
+
+**GPT Image 2.5 新生成展示名**:
+`GPT Image 2.5` 是新生成任务的产品展示名；历史资源与既有编辑上下文不因新模型上线而改写展示语义。
+_Avoid_: 把新生成展示名扩散到历史记录、历史生成器或旧编辑上下文
+
 **系列素材图集生成**:
 一组同类素材的统一批量生成方式，采用批量规划、sheet 生图、后端切图、透明化、OSS 持久化和局部重生成的通用流水线。
 _Avoid_: 为每个玩法单独发明素材流水线、把系列素材建模成任一玩法专属 DTO

docs/README.md

@@ -70,6 +70,7 @@
 - [画板音乐生成入口](./【编辑器】画板音乐生成入口设计-2026-06-18.md)：BGM/SFX 共享视图、独立业务规则和当前发布门禁。
 - [画布 Agent 对话面板](./【编辑器】画布Agent对话面板-2026-07-03.md)
 - [画布 Agent 会话消息存 OSS](./adr/【ADR】画布Agent会话消息存OSS-2026-07-03.md)
+- [GPT Image 2.5 模型路由与历史值兼容](./adr/【ADR】GPT Image 2.5模型路由与历史值兼容-2026-09-18.md)
 - [编辑器模型定价配置](./【编辑器】模型定价配置管理方案-2026-06-22.md)
 
 ## 后端、运维与测试

docs/adr/【ADR】GPT Image 2.5模型路由与历史值兼容-2026-09-18.md

@@ -0,0 +1,17 @@
+# GPT Image 2.5 模型路由与历史值兼容
+
+状态：accepted
+
+新任务使用业务模型值 `gpt-image-2.5`，api-server 按任务显式选择具体 model：生成使用 `gpt-image-2.5-flare-c`，编辑使用 `gpt-image-2.5-sunburst-c`。这两个 GPT Image 2.5 model 必须通过启动时构造的 Tiantoken client 发送；Tiantoken client 只读取显式配置的 `TIANTOKEN_BASE_URL`（部署值由环境设置为 `https://api.tiantoken.com`）和独立 `TIANTOKEN_API_KEY`，缺失即阻止 api-server 启动，不得回退到 VectorEngine 或其 API key。
+
+图片协议执行逻辑保持 provider-neutral：请求 body、multipart、尺寸约束、重试、响应解码和审计由共享 image executor 承担；VectorEngine 与 Tiantoken client 只提供相同协议所需的 base URL、API key 和 provider identity。platform-image 根据 concrete model 做严格白名单路由：`gpt-image-2.5-flare-c` 与 `gpt-image-2.5-sunburst-c` 走 Tiantoken，`gemini-3.1-flash-image-preview`（nanobanana）走 VectorEngine；未知 model 直接拒绝。已持久化的 `gpt-image-2` / `gpt-image-2-c` 只在新任务提交边界按兼容规则解析为当前 GPT Image 2.5 任务，不改写历史资源，也不进入旧 VectorEngine 图片路由。
+
+普通主站前端只接触业务模型和新生成展示名 `GPT Image 2.5`，admin Web/API 可以查看和编辑两个具体定价 key；普通生成即使因参考图使用 edits multipart，仍按生成 concrete model。旧 `gpt-image-2-c` 审计记录原样保留，新代码不再跨模型或跨 provider fallback。
+
+## Consequences
+
+- 定价配置的活动 key 是两个具体 provider model；旧单 key 配置只允许受控 backfill，并留下兼容 TODO。
+- 新任务的同模型重试固定使用 api-server dispatch 的具体 model，不切换到另一个 model。
+- 两套 provider client 在 api-server 启动阶段同时构造；任一 required provider 配置缺失，启动失败而不是延迟到首次图片请求。
+- provider routing 只依据 concrete model 的白名单；provider client 不复制共享协议执行逻辑。
+- 公开资源、`generationInputs` 和普通前端契约不包含具体 provider key；admin 定价管理是明确例外。

docs/project-memory/plans/【实施计划】GPT Image 2.5 provider边界重构-2026-09-18.md

@@ -0,0 +1,31 @@
+# GPT Image 2.5 provider 边界重构实施计划
+
+- Version: 2
+- Status: active
+- Date: 2026-09-18
+- Parent Milestone: `docs/project-memory/plans/【里程碑】GPT Image 2.5 provider边界重构-2026-09-18.md`
+
+## 实施边界
+
+1. 先抽象 provider-neutral settings/client 与共享图片执行器接口；保留一套 body、multipart、尺寸、retry、响应和 audit 逻辑。
+2. 在 api-server 配置/state 初始化阶段分别构造 VectorEngine 与 Tiantoken client；删除 Tiantoken 对 VectorEngine URL/key 的任何 fallback。
+3. 在 platform-image 建立 concrete model 白名单路由：GPT Image 2.5 → Tiantoken，nanobanana → VectorEngine；legacy/unknown 按合同处理。
+4. 重命名 provider-specific client/build/transport 符号，避免共享逻辑继续伪装成 `vector_engine_*`；仅保留确有 VectorEngine 语义的名称。
+5. 迁移 api-server、Agent、raw edit、角色/图标/UI 入口和测试；核对 pricing/admin/public DTO 可见性。
+6. 删除跨模型/跨 provider fallback 分支，保留同 concrete model retry。
+
+## 验证命令
+
+- `cargo fmt --all --manifest-path server-rs/Cargo.toml -- --check`
+- `cargo test -p platform-image`
+- `cargo test -p platform-editor-agent`
+- api-server 定向测试/`cargo check -p api-server`
+- `npm run typecheck`
+- `npm run check:doc-index`
+- `npm run check:encoding`
+- `git diff --check`
+
+## 风险与回滚
+
+- 风险：启动阶段依赖变化、历史任务兼容解析遗漏、nanobanana 被误路由到 Tiantoken、provider key 泄露到公开 DTO。
+- 回滚：以 provider-neutral seam、启动配置、model route、调用方迁移四个局部提交边界回滚；不执行数据库历史迁移。

docs/project-memory/plans/【里程碑】GPT Image 2.5 provider边界重构-2026-09-18.md

@@ -0,0 +1,52 @@
+# GPT Image 2.5 provider 边界重构
+
+- Version: 2
+- Status: active
+- Date: 2026-09-18
+- Parent Spec: `docs/adr/【ADR】GPT Image 2.5模型路由与历史值兼容-2026-09-18.md`
+
+## 目标
+
+在保持图片协议执行逻辑共享的前提下，建立明确的 provider client 边界：GPT Image 2.5 通过 Tiantoken，nanobanana 通过 VectorEngine；路由依据 concrete model 严格白名单决定；两个 client 在 api-server 启动阶段构造。
+
+## 范围
+
+- `platform-image`：provider-neutral 图片执行器、provider client 注入 seam、concrete model 路由和错误/审计 provider 标识。
+- `api-server`：启动时构造 VectorEngine/Tiantoken 两个 client，分别读取各自环境变量；任务提交边界的历史模型兼容解析。
+- 共享请求、multipart、尺寸、retry、响应和 audit 逻辑保持单一实现。
+- Agent 与其它 server-side 图片调用方迁移到业务模型/concrete model 合同。
+- 定价、公开 DTO、admin DTO 与 provider model 可见性保持既定 ADR 约束。
+
+## 现役路由
+
+| Concrete model | Provider client | 业务用途 |
+| --- | --- | --- |
+| `gpt-image-2.5-flare-c` | Tiantoken | Generate，包括带参考图的普通生成 |
+| `gpt-image-2.5-sunburst-c` | Tiantoken | Edit，包括快速编辑、原位修改、raw edit |
+| `gemini-3.1-flash-image-preview` | VectorEngine | nanobanana 生成/编辑能力 |
+
+`gpt-image-2` 与 `gpt-image-2-c` 只保留为历史持久化/审计字符串；新任务不得 dispatch 到旧 GPT Image 2 路由。未知 model 直接拒绝。
+
+## 必须成立的行为
+
+1. api-server 启动时同时构造两个 required provider client；任一对应环境变量缺失，启动失败。
+2. Tiantoken 只读取 `TIANTOKEN_BASE_URL` / `TIANTOKEN_API_KEY`；VectorEngine 只读取 `VECTOR_ENGINE_BASE_URL` / `VECTOR_ENGINE_API_KEY`，互不回退。
+3. platform-image 根据 concrete model 选择已注入 client；共享执行器不复制 provider 协议逻辑。
+4. 同 concrete model 可以 retry，但永不跨 concrete model 或跨 provider fallback。
+5. 历史值读取不改写；新任务提交边界将旧值兼容为 GPT Image 2.5 业务任务。
+6. 普通前端不接收 concrete provider model；admin 定价界面可查看和编辑两个具体 pricing key。
+
+## 非目标
+
+- 不复制两套完整图片 client。
+- 不新增 GPT Image 2 现役 VectorEngine 路由。
+- 不修改历史数据库记录或旧审计字符串。
+- 不把 provider client 选择下沉给普通前端。
+
+## 验收证据
+
+- provider routing 单元测试覆盖 flare/sunburst/nanobanana/legacy/unknown。
+- 启动配置测试证明两套 client 独立读取环境变量，缺失任一配置即失败且无 VectorEngine/Tiantoken 回退。
+- 请求审计测试证明 provider 与 concrete model 正确记录。
+- platform-image 与 Agent 定向测试通过。
+- api-server 类型/编译检查、前端类型检查、编码/文档/diff 门禁通过。

docs/project-memory/shared-memory/decision-log.md

@@ -8840,3 +8840,20 @@ CI 上 `background_agent_runtime_recovers_stale_running_before_pending_task` 在
 - 边界：Deploy 阶段在远端 dev / release agent 执行，不受该上限约束。调整只动这两处：`systemctl set-property / revert jenkins.service`、`docker update --cpus=<n> gitea-runner` 加同步 compose（备份 `/opt/gitea-stack/compose.yml.bak-<时间戳>`）。
 - 验证：限速后 `Genarrative-Full-Build-And-Deploy` #289 / #290 SUCCESS；采样期 Jenkins 峰值 10.2~10.5 核、限流不足 2s（可忽略），runner 峰值 12.07 核且持续出现 throttling，整机回落到 2.6%~19.8%。
 - 关联文档：[开发运维](../../【开发运维】本地开发验证与生产运维-2026-05-15.md)。
+
+## 2026-09-18 GPT Image 2.5 业务模型与具体 provider 定价路由
+
+- **决策**：新任务使用业务模型值 `gpt-image-2.5`；api-server 按任务显式 dispatch 具体模型 `gpt-image-2.5-flare-c`（生成）或 `gpt-image-2.5-sunburst-c`（编辑），并把同一具体 key 交给 `platform-image` 与后台定价解析。普通生成即使因参考图使用 edits multipart，仍按生成 route；同模型重试不跨模型 fallback。
+- **历史兼容**：已持久化 `gpt-image-2` 读回原值不改写；基于旧资源发起新任务时，在提交边界解析为 `gpt-image-2.5`，新任务/新产物按新业务值和当前 task price 处理。旧 `gpt-image-2-c` 仅保留历史审计，不再作为 fallback 或业务模型。
+- **可见性**：普通主站前端和公开定价 API 不接收具体 provider key；新生成 UI label 为 `GPT Image 2.5`，历史资源/旧编辑上下文不扩散该 label。admin Web/API 是明确例外，可查看和编辑两个具体定价 key。旧单 key 定价配置允许受控 backfill，并加 compatibility TODO。
+- **关联 ADR**：[`docs/adr/【ADR】GPT Image 2.5模型路由与历史值兼容-2026-09-18.md`](../../adr/【ADR】GPT%20Image%202.5模型路由与历史值兼容-2026-09-18.md)。
+
+- **补充**：GPT Image 2.5 的两个具体模型通过显式 `TIANTOKEN_BASE_URL` 与独立 `TIANTOKEN_API_KEY` 发送；环境变量缺失时必须失败，禁止使用 VectorEngine 配置或 API key 回退。
+
+## 2026-09-18 GPT Image 2.5 provider-neutral 执行器与双 client 启动边界
+
+- **决策**：图片协议执行逻辑保持单一共享实现；只抽出 provider client 的 identity、base URL、API key 和 client 构造，通过依赖注入复用请求 body、multipart、尺寸、retry、响应和 audit。
+- **路由**：`gpt-image-2.5-flare-c` / `gpt-image-2.5-sunburst-c` 走 Tiantoken；`gemini-3.1-flash-image-preview`（nanobanana）走 VectorEngine；`gpt-image-2` / `gpt-image-2-c` 仅是历史字符串，新任务不再进入旧 GPT Image 2 路由；未知 model 拒绝。
+- **启动**：api-server 启动时同时构造 VectorEngine 与 Tiantoken 两个 required client；各自只读取自己的环境变量，任一配置缺失即启动失败，不延迟到首次请求。
+- **重试**：只在同一个 concrete model 内 retry，禁止跨 model、跨 provider fallback。
+- **关联文档**：[`docs/adr/【ADR】GPT Image 2.5模型路由与历史值兼容-2026-09-18.md`](../../adr/【ADR】GPT%20Image%202.5模型路由与历史值兼容-2026-09-18.md)、[`docs/project-memory/plans/【里程碑】GPT Image 2.5 provider边界重构-2026-09-18.md`](../plans/【里程碑】GPT%20Image%202.5%20provider边界重构-2026-09-18.md)。

docs/technical/【技术方案】Raw GPT Image 2图片编辑代理-2026-09-07.md

@@ -90,7 +90,7 @@ provider 响应只提取并透传 `data[].b64_json` 字符串，不在服务端
 ## 代码拆分
 
 - `server-rs/crates/api-server/src/raw_image.rs`：独立路由 handler、multipart 字段解析、请求/响应 DTO、PNG 输入校验、预检查和 raw billing 编排。
-- `server-rs/crates/platform-image/src/vector_engine/raw_edit.rs`：raw 编辑选项、严格尺寸校验、独立 provider 请求映射和 `b64_json` 响应透传；由 api-server 按现有图片 API 传统构造并传入共享的 VectorEngine `reqwest::Client`，不在每个 raw 调用内部重复构造 client。每次请求仍用 `effective_request_timeout_ms` 通过 request builder 设置剩余 deadline；不修改统一 transport builder 的连接池策略。
+- `server-rs/crates/platform-image/src/raw_image_edit/mod.rs`：raw 编辑选项、严格尺寸校验、独立 provider 请求映射和 `b64_json` 响应透传；由 api-server 按现有图片 API 传统构造并传入启动时构造的 Tiantoken `reqwest::Client`，不在每个 raw 调用内部重复构造 client。每次请求仍用 `effective_request_timeout_ms` 通过 request builder 设置剩余 deadline；不修改统一 transport builder 的连接池策略。
 
 raw-edit 的图片输入使用独立的 `RawImageEditImage`（`bytes::Bytes`），由 reqwest `Part::stream(Body::from(Bytes))` 直接接管 multipart 请求体，避免整图和掩码在 `Part::bytes` 的 `Cow<[u8]>` 转换中再次复制。既有 `ReferenceImage`、`DownloadedImage` 及 curl/编辑器链路继续保持 `Vec<u8>` 契约，不因 raw-edit 引入全局字节类型迁移。
 

docs/【后端架构】server-rs与SpacetimeDB数据契约-2026-05-15.md

@@ -168,7 +168,7 @@ npm run check:server-rs-ddd
 2. Adapter 输入应显式包含 provider、prompt、reference images、OSS prefix/path/file name、asset kind、entity kind/id、slot、owner/profile/source job、metadata 和可选透明背景后处理。
 3. Adapter 输出应保留 legacy public path、object key、asset object id、MIME、extension、task id 和实际 prompt。
 4. Adapter 不负责扣费、退款或钱包读取；计费仍由调用方显式包裹。
-5. 图片 provider 协议不再放在玩法模块里实现。产品、计费、DTO、持久化和 VectorEngine 创建 / 编辑首选请求统一使用 `gpt-image-2`；只有符合回退条件时，provider 边界才切到兜底模型 `gpt-image-2-c`。URL / base64 图片解析、远端图片下载、请求超时 / 上游状态 / 响应解析 / 缺图 / 下载失败的结构化日志统一在 `server-rs/crates/platform-image/src/vector_engine/`；其中 `client.rs` 只保留 provider 调用编排，`transport.rs` 负责 HTTP client 与 reqwest 错误归一，`request.rs` 负责请求体和路径，`payload.rs` 负责响应 JSON 字段提取，`response.rs` 负责响应状态分流和图片结果归一。`api-server` 只负责配置校验、玩法 prompt 编排、OSS / asset object / binding 持久化、计费和外部 API 失败审计落库。
+5. 图片 provider 协议不再放在玩法模块里实现。产品、计费、DTO、持久化和 GPT Image 2.5 创建 / 编辑请求统一使用业务模型 `gpt-image-2.5`，api-server 在提交边界分派 `gpt-image-2.5-flare-c` / `gpt-image-2.5-sunburst-c`；已持久化的 `gpt-image-2` / `gpt-image-2-c` 只按兼容规则读取，不改写历史值。URL / base64 图片解析、远端图片下载、请求超时 / 上游状态 / 响应解析 / 缺图 / 下载失败的结构化日志统一在 `server-rs/crates/platform-image/src/image_provider/`；其中 `runtime/executor.rs` 负责共享 provider-neutral 执行编排，`transport/` 负责 HTTP client 与 curl 传输，`protocol/` 负责请求体、路径和响应 JSON 字段。raw image edit 的 multipart 与严格尺寸校验位于独立的 `server-rs/crates/platform-image/src/raw_image_edit/`。`api-server` 只负责配置校验、玩法 prompt 编排、OSS / asset object / binding 持久化、计费和外部 API 失败审计落库。
 6. OSS 平台适配日志统一在 `server-rs/crates/platform-oss` 输出，覆盖 `sign_post_object`、`sign_get_object_url`、`head_object` 和 `put_object`。日志字段固定使用 `provider`、`operation`、`bucket`、`endpoint`、`object_key` / `key_prefix`、`access`、`content_type`、`content_length`、`status`、`status_class`、`error_kind` 和 `elapsed_ms`，只记录对象定位和排障信息；不得输出 AccessKey、policy、signature、Authorization header 或完整 signed URL。generated 私有对象上传时必须由 OSS 对象头承载浏览器 / CDN 缓存策略，默认写入 `Cache-Control: public, max-age=31536000, immutable`，不得改成 api-server 本地磁盘静态资源兜底。
 7. Puzzle、Match3D、音频、GLB、视频等复杂媒体可以复用 OSS + asset object + binding 的底层持久化能力，但玩法专属处理规则留在各自编排层，不塞进公共接口。
 8. 拼图入口页与结果页新增关卡的本地参考图不走浏览器直传 OSS，前端读取为 Data URL 后随创作 action 提交，并在读取前限制 6MB、显示“图片≤6MB”。`api-server` 必须对 Data URL 实际字节数再次校验；历史图片才提交 `referenceImageAssetObjectId(s)`，后端校验 `asset_object` 的 bucket、kind、图片 MIME、大小和 owner 后签发只读 URL 给 VectorEngine 读取。

docs/【开发运维】本地开发验证与生产运维-2026-05-15.md

@@ -226,7 +226,7 @@ spacetime sql <database> "SELECT * FROM runtime_setting LIMIT 1" --server http:/
 
 本地 `spacetime` CLI / standalone 版本必须和 `server-rs/Cargo.toml` 里锁定的 `spacetimedb` 版本一致；当前统一版本为 `2.8.3`，CLI / standalone commit 固定核对为 `8e410d2842147bd8e5a32a9589cc00c19f7478e2`。若版本或 commit 错配，procedure 返回值可能在宿主侧触发 `Failed to BSATN deserialize procedure return value`，api-server 最终表现为现役 settings、editor project 或 profile procedure 超时。排障时先运行 `spacetime --version`，再对照 `server-rs/Cargo.toml` 的 `spacetimedb = "..."`；其它版本可执行 `spacetime version install <version> && spacetime version use <version>`，升级后重启 `npm run dev:spacetime` 再重试。当前 `scripts/dev.mjs` 会把 tool version 和 commit 一起写入 `dev-spacetime-tool-version`，启动新 standalone 与复用已有本地进程时都要求 `2.8.3 + 8e410d28...` 同时匹配；旧版本或旧单行版本记录会拒绝复用并要求重启。2.6.1 修复了 procedure context 中调用者 `Identity` / `ConnectionId` 始终为空的回归，依赖 `ctx.sender` 鉴权时必须同时确认宿主已升级。
 
-本地 `.env`、`.env.local` 或 `.env.secrets.local` 修改后必须重启 `api-server` 才会生效；若已经通过 `npm run dev` 启动完整联调，可在该终端输入 `rs api-server`。排查图片编辑器 Tiantoken 生成链路时，确认 `TIANTOKEN_BASE_URL`、`TIANTOKEN_API_KEY` 和 `TIANTOKEN_IMAGE_REQUEST_TIMEOUT_MS` 只在本地或服务器密钥文件中配置，不能写入 Git。VectorEngine 配置仅保留给 Suno 音乐任务。`TIANTOKEN_IMAGE_REQUEST_TIMEOUT_MS` 是单次 attempt 的配置上限，默认 `1000000`；配置加载层允许显式值低于该默认值，不再在读取环境变量时强制抬高。业务模型和 Tiantoken provider 首选请求都使用 `gpt-image-2`，符合条件时才回退到兜底模型 `gpt-image-2-c`；图片协议、URL / base64 响应解析、远端图片下载和 provider 侧结构化日志在 `server-rs/crates/platform-image`，`api-server` 只做编辑器请求编排、OSS / asset 持久化、计费和失败审计落库。`platform-image` 会在 JSON 生成和 multipart 编辑请求发送前按同一 GPT-image-2 family 规则归一显式像素尺寸；若请求发送失败，先按同一 `request_id` 查看 provider 日志与 `external_api_call_failure.metadata_json.errorSource`，当前 multipart `/v1/images/edits` 单独强制 HTTP/1.1。
+本地 `.env`、`.env.local` 或 `.env.secrets.local` 修改后必须重启 `api-server` 才会生效；若已经通过 `npm run dev` 启动完整联调，可在该终端输入 `rs api-server`。排查图片编辑器 Tiantoken 生成链路时，确认 `TIANTOKEN_BASE_URL`、`TIANTOKEN_API_KEY` 和 `TIANTOKEN_IMAGE_REQUEST_TIMEOUT_MS` 只在本地或服务器密钥文件中配置，不能写入 Git；同时确认 VectorEngine 的 `VECTOR_ENGINE_BASE_URL` / `VECTOR_ENGINE_API_KEY` 已配置，因为两个图片 client 都在 api-server 启动时构造，任一缺失都会阻止启动。VectorEngine 配置仍保留给 nanobanana 与 Suno 音乐任务。`TIANTOKEN_IMAGE_REQUEST_TIMEOUT_MS` 是单次 attempt 的配置上限，默认 `1000000`；配置加载层允许显式值低于该默认值，不再在读取环境变量时强制抬高。新生成任务使用业务模型 `gpt-image-2.5`，api-server 显式分派 `gpt-image-2.5-flare-c`（generate）或 `gpt-image-2.5-sunburst-c`（edit）；已持久化的 `gpt-image-2` / `gpt-image-2-c` 只在提交边界按兼容规则解析，不改写历史值，也不回退到旧 GPT Image 2 路由。图片协议、URL / base64 响应解析、远端图片下载和 provider 侧结构化日志在 `server-rs/crates/platform-image`，`api-server` 只做编辑器请求编排、OSS / asset 持久化、计费和失败审计落库。`platform-image` 会在 JSON 生成和 multipart 编辑请求发送前按同一 GPT-image family 规则归一显式像素尺寸；若请求发送失败，先按同一 `request_id` 查看 provider 日志与 `external_api_call_failure.metadata_json.errorSource`，当前 multipart `/v1/images/edits` 单独强制 HTTP/1.1。
 
 编辑器 ElevenLabs 音效生成只从服务端读取 `ELEVENLABS_BASE_URL`、`ELEVENLABS_API_KEY` 和 `ELEVENLABS_REQUEST_TIMEOUT_MS`，timeout 默认 `180000ms`；base URL 或 Key 缺失时失败关闭，不回退 Vidu。生产 API 与 external-generation worker 通过共享 API env 取得同一配置，模板见 `deploy/env/api-server.env.example`；Key 不得进入 Web/Vite 环境、命令参数、日志、fixture 或仓库。普通测试只使用 loopback mock，禁止把真实付费请求作为 T3 自动验收。
 

server-rs/crates/api-server/config/editor-generation-pricing.default.json

@@ -15,6 +15,20 @@
         "2K": 5
       }
     },
+    "gpt-image-2.5-flare-c": {
+      "unit": "perGeneration",
+      "prices": {
+        "1K": 3,
+        "2K": 5
+      }
+    },
+    "gpt-image-2.5-sunburst-c": {
+      "unit": "perGeneration",
+      "prices": {
+        "1K": 3,
+        "2K": 5
+      }
+    },
     "seedance2.0-fast": {
       "unit": "perSecond",
       "prices": {

server-rs/crates/api-server/src/character_visual_assets.rs

@@ -36,16 +36,16 @@ use crate::{
     },
     http_error::AppError,
     openai_image_generation::{
-        DownloadedOpenAiImage, GPT_IMAGE_2_MODEL, OpenAiImageSettings,
-        build_openai_image_http_client, create_openai_image_generation,
-        require_openai_image_settings,
+        DownloadedOpenAiImage, GPT_IMAGE_2_5_BUSINESS_NAME, GPT_IMAGE_2_5_GENERATION_MODEL,
+        OpenAiImageSettings, build_openai_image_http_client,
+        create_openai_image_generation_with_model, require_openai_image_settings,
     },
     platform_errors::map_oss_error,
     request_context::RequestContext,
     state::AppState,
 };
 
-const CHARACTER_VISUAL_MODEL: &str = GPT_IMAGE_2_MODEL;
+const CHARACTER_VISUAL_MODEL: &str = GPT_IMAGE_2_5_BUSINESS_NAME;
 const CHARACTER_VISUAL_ASSET_KIND: &str = "character_visual";
 const CHARACTER_VISUAL_ENTITY_KIND: &str = "character";
 const CHARACTER_VISUAL_SLOT: &str = "primary_visual";
@@ -777,13 +777,13 @@ fn build_character_visual_job_payload(task: AiTaskSnapshot) -> CharacterAssetJob
 }
 
 fn resolve_character_visual_model(value: &str) -> String {
-    // 中文注释：旧前端和历史草稿可能仍传 wan2.7-image-pro；RPG 主图当前统一归一到 gpt-image-2。
+    // 中文注释：旧前端和历史草稿可能仍传旧模型；只在新任务提交边界归一到当前业务模型。
     let trimmed = value.trim();
     if !trimmed.is_empty() && trimmed != CHARACTER_VISUAL_MODEL {
         tracing::warn!(
             requested_model = trimmed,
             effective_model = CHARACTER_VISUAL_MODEL,
-            "角色主形象图片模型已归一到 gpt-image-2"
+            "角色主形象图片模型已归一到当前业务模型"
         );
     }
     CHARACTER_VISUAL_MODEL.to_string()
@@ -946,9 +946,10 @@ async fn create_character_visual_generation_once(
     candidate_count: u32,
     reference_images: &[String],
 ) -> Result<GeneratedCharacterVisuals, AppError> {
-    let generated = create_openai_image_generation(
+    let generated = create_openai_image_generation_with_model(
         http_client,
         settings,
+        GPT_IMAGE_2_5_GENERATION_MODEL,
         prompt,
         Some(build_character_visual_negative_prompt().as_str()),
         size,
@@ -1921,12 +1922,12 @@ mod tests {
     }
 
     #[test]
-    fn legacy_character_visual_model_normalizes_to_gpt_image_2() {
+    fn legacy_character_visual_model_normalizes_to_gpt_image_2_5() {
         assert_eq!(
             resolve_character_visual_model("wan2.7-image-pro"),
-            "gpt-image-2"
+            "gpt-image-2.5"
         );
-        assert_eq!(resolve_character_visual_model(""), "gpt-image-2");
+        assert_eq!(resolve_character_visual_model(""), "gpt-image-2.5");
     }
 
     #[test]

server-rs/crates/api-server/src/config.rs

@@ -1428,18 +1428,15 @@ impl AppConfig {
     }
 }
 
-/// Tiantoken 是图片、文本和旧版非 Suno 音频生成的新 provider。
-///
-/// 这里保留对 `AppConfig.vector_engine_*` 的回退，方便测试构造的旧配置继续工作；
-/// 生产环境一旦设置了新的 `TIANTOKEN_*` 变量，就不会再把非 Suno 请求发往 VectorEngine。
+/// Tiantoken 是 GPT Image 2.5 图片任务的独立 provider；凭证不得回退到 VectorEngine。
 pub(crate) fn tiantoken_base_url(config: &AppConfig) -> String {
-    read_first_non_empty_env(&["TIANTOKEN_BASE_URL"])
-        .unwrap_or_else(|| config.vector_engine_base_url.clone())
+    let _ = config;
+    read_first_non_empty_env(&["TIANTOKEN_BASE_URL"]).unwrap_or_default()
 }
 
 pub(crate) fn tiantoken_api_key(config: &AppConfig) -> Option<String> {
+    let _ = config;
     read_first_non_empty_env(&["TIANTOKEN_API_KEY"])
-        .or_else(|| config.vector_engine_api_key.clone())
 }
 
 fn read_first_non_empty_env(keys: &[&str]) -> Option<String> {
@@ -1864,14 +1861,8 @@ mod tests {
             std::env::remove_var("TIANTOKEN_BASE_URL");
             std::env::remove_var("TIANTOKEN_API_KEY");
         }
-        assert_eq!(
-            tiantoken_base_url(&config),
-            "https://vector.example.invalid"
-        );
-        assert_eq!(
-            tiantoken_api_key(&config).as_deref(),
-            Some("legacy-vector-key")
-        );
+        assert_eq!(tiantoken_base_url(&config), "");
+        assert_eq!(tiantoken_api_key(&config), None);
     }
 
     #[test]

server-rs/crates/api-server/src/editor_generation_config.rs

@@ -17,6 +17,10 @@ pub(crate) const EDITOR_GENERATION_PRICING_DEFAULT_JSON: &str =
     include_str!("../config/editor-generation-pricing.default.json");
 
 const EDITOR_IMAGE_MODEL_GPT_IMAGE_2: &str = "gpt-image-2";
+const EDITOR_IMAGE_MODEL_GPT_IMAGE_2_C: &str = "gpt-image-2-c";
+pub(crate) const EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_BUSINESS: &str = "gpt-image-2.5";
+pub(crate) const EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION: &str = "gpt-image-2.5-flare-c";
+pub(crate) const EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT: &str = "gpt-image-2.5-sunburst-c";
 const EDITOR_IMAGE_MODEL_NANOBANANA2: &str = "gemini-3.1-flash-image-preview";
 const EDITOR_IMAGE_MODEL_NANOBANANA2_DISPLAY_ALIAS: &str = "nanobanana2";
 const EDITOR_IMAGE_MODEL_NANOBANANA_LEGACY_ALIAS: &str = "nano-banana";
@@ -94,6 +98,25 @@ pub(crate) enum EditorGenerationPricingError {
 }
 
 impl EditorGenerationPricingConfig {
+    /// Public main-site projection: provider-specific GPT Image keys remain an
+    /// admin/server concern and are represented by the business model name.
+    pub(crate) fn public_projection(&self) -> Self {
+        let mut models = self.models.clone();
+        if let Some(generation) = models
+            .get(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION)
+            .cloned()
+        {
+            models.insert(
+                EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_BUSINESS.to_string(),
+                generation,
+            );
+        }
+        models.remove(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION);
+        models.remove(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT);
+        models.remove(EDITOR_IMAGE_MODEL_GPT_IMAGE_2);
+        Self { models }
+    }
+
     pub(crate) fn image_model_mud_points(
         &self,
         model: Option<&str>,
@@ -114,15 +137,35 @@ impl EditorGenerationPricingConfig {
         )
     }
 
+    pub(crate) fn image_edit_model_mud_points(
+        &self,
+        model: Option<&str>,
+        image_size: Option<&str>,
+    ) -> u32 {
+        if let Some(price_mud_points) = current_external_generation_billing_price_mud_points() {
+            return price_mud_points;
+        }
+        let normalized_model = normalize_editor_image_edit_model(model);
+        let normalized_size =
+            normalize_editor_generation_image_price_size(normalized_model, image_size);
+        read_tier_price(
+            &self.models,
+            normalized_model,
+            EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT,
+            normalized_size,
+            DEFAULT_IMAGE_PRICE_SIZE,
+        )
+    }
+
     pub(crate) fn spec_model_mud_points(&self, model: Option<&str>) -> u32 {
         if let Some(price_mud_points) = current_external_generation_billing_price_mud_points() {
             return price_mud_points;
         }
-        let normalized_model = normalize_non_empty_model(model, EDITOR_IMAGE_MODEL_GPT_IMAGE_2);
+        let normalized_model = normalize_editor_image_model(model);
         read_tier_price(
             &self.models,
             normalized_model,
-            EDITOR_IMAGE_MODEL_GPT_IMAGE_2,
+            EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION,
             SPEC_IMAGE_PRICE_SIZE,
             SPEC_IMAGE_PRICE_SIZE,
         )
@@ -221,7 +264,13 @@ impl EditorGenerationPricingConfig {
         )?;
         validate_required_tier_prices(
             &self.models,
-            EDITOR_IMAGE_MODEL_GPT_IMAGE_2,
+            EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION,
+            EditorGenerationPricingUnit::PerGeneration,
+            REQUIRED_GPT_IMAGE_SIZES,
+        )?;
+        validate_required_tier_prices(
+            &self.models,
+            EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT,
             EditorGenerationPricingUnit::PerGeneration,
             REQUIRED_GPT_IMAGE_SIZES,
         )?;
@@ -326,6 +375,7 @@ fn load_editor_generation_pricing_from_candidates(
             serde_json::from_str::<EditorGenerationPricingConfig>(override_json.as_str())
                 .map_err(EditorGenerationPricingError::Json)?;
         backfill_legacy_sfx_pricing(&mut override_config, &config, source.as_ref())?;
+        backfill_legacy_gpt_image_2_5_pricing(&mut override_config, &config, source.as_ref())?;
         override_config.validate().map_err(|error| match error {
             EditorGenerationPricingError::Invalid(message) => {
                 EditorGenerationPricingError::Invalid(format!("{source}: {message}"))
@@ -338,6 +388,43 @@ fn load_editor_generation_pricing_from_candidates(
     Ok(config)
 }
 
+fn backfill_legacy_gpt_image_2_5_pricing(
+    config: &mut EditorGenerationPricingConfig,
+    fallback: &EditorGenerationPricingConfig,
+    source: &str,
+) -> Result<(), EditorGenerationPricingError> {
+    if config
+        .models
+        .contains_key(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION)
+        && config
+            .models
+            .contains_key(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT)
+    {
+        return Ok(());
+    }
+    // TODO: compatibility backfill for legacy single-key pricing; remove once
+    // all persisted overrides contain the two explicit GPT Image 2.5 keys.
+    let pricing = config
+        .models
+        .get(EDITOR_IMAGE_MODEL_GPT_IMAGE_2)
+        .or_else(|| fallback.models.get(EDITOR_IMAGE_MODEL_GPT_IMAGE_2))
+        .cloned()
+        .ok_or_else(|| {
+            EditorGenerationPricingError::Invalid(format!(
+                "{source}: 受控默认配置缺少模型 {EDITOR_IMAGE_MODEL_GPT_IMAGE_2} 的兼容泥点配置"
+            ))
+        })?;
+    config
+        .models
+        .entry(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION.to_string())
+        .or_insert_with(|| pricing.clone());
+    config
+        .models
+        .entry(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT.to_string())
+        .or_insert(pricing);
+    Ok(())
+}
+
 fn backfill_legacy_sfx_pricing(
     config: &mut EditorGenerationPricingConfig,
     fallback: &EditorGenerationPricingConfig,
@@ -437,7 +524,13 @@ fn default_runtime_pricing() -> EditorGenerationPricingConfig {
 
 fn normalize_editor_image_model(model: Option<&str>) -> &'static str {
     match model.map(str::trim).filter(|value| !value.is_empty()) {
-        Some(EDITOR_IMAGE_MODEL_GPT_IMAGE_2) => EDITOR_IMAGE_MODEL_GPT_IMAGE_2,
+        Some(
+            EDITOR_IMAGE_MODEL_GPT_IMAGE_2
+            | EDITOR_IMAGE_MODEL_GPT_IMAGE_2_C
+            | EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_BUSINESS
+            | EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION,
+        ) => EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION,
+        Some(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT) => EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT,
         Some(EDITOR_IMAGE_MODEL_NANOBANANA2)
         | Some(EDITOR_IMAGE_MODEL_NANOBANANA2_DISPLAY_ALIAS)
         | Some(EDITOR_IMAGE_MODEL_NANOBANANA_LEGACY_ALIAS) => EDITOR_IMAGE_MODEL_NANOBANANA2,
@@ -445,6 +538,19 @@ fn normalize_editor_image_model(model: Option<&str>) -> &'static str {
     }
 }
 
+fn normalize_editor_image_edit_model(model: Option<&str>) -> &'static str {
+    match model.map(str::trim).filter(|value| !value.is_empty()) {
+        Some(EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT) => EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT,
+        Some(
+            EDITOR_IMAGE_MODEL_GPT_IMAGE_2
+            | EDITOR_IMAGE_MODEL_GPT_IMAGE_2_C
+            | EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_BUSINESS
+            | EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_GENERATION,
+        ) => EDITOR_IMAGE_MODEL_GPT_IMAGE_2_5_EDIT,
+        _ => normalize_editor_image_model(model),
+    }
+}
+
 fn normalize_editor_generation_image_price_size(
     model: &str,
     image_size: Option<&str>,

server-rs/crates/api-server/src/editor_project.rs

@@ -112,9 +112,10 @@ use crate::{
     },
     http_error::AppError,
     openai_image_generation::{
-        DownloadedOpenAiImage, GPT_IMAGE_2_MODEL, OpenAiGeneratedImages, OpenAiImageSettings,
-        OpenAiReferenceImage, build_openai_image_http_client,
-        create_openai_image_edit_with_references_and_model,
+        DownloadedOpenAiImage, GPT_IMAGE_2_5_BUSINESS_NAME, GPT_IMAGE_2_5_EDIT_MODEL,
+        GPT_IMAGE_2_5_GENERATION_MODEL, GPT_IMAGE_2_C_MODEL, GPT_IMAGE_2_MODEL,
+        OpenAiGeneratedImages, OpenAiImageSettings, OpenAiReferenceImage,
+        build_openai_image_http_client, create_openai_image_edit_with_references_and_model,
         create_openai_image_generation_with_model, create_openai_nanobanana_generate_content,
         require_openai_image_settings,
     },
@@ -374,6 +375,9 @@ pub(crate) struct EditorImagePromptBuildOutput {
 
 pub(crate) struct EditorImageProviderRequest<'a> {
     pub(crate) model: &'a str,
+    /// Concrete provider/pricing route selected by api-server. The business
+    /// model remains `model`; this value must never be exposed to normal UI.
+    pub(crate) provider_model: &'a str,
     pub(crate) prompt: &'a str,
     pub(crate) negative_prompt: Option<&'a str>,
     pub(crate) size: &'a str,
@@ -392,7 +396,7 @@ pub(crate) async fn request_editor_generated_images(
         create_openai_nanobanana_generate_content(
             http_client,
             settings,
-            request.model,
+            request.provider_model,
             request.prompt,
             request.negative_prompt,
             request.aspect_ratio,
@@ -405,7 +409,7 @@ pub(crate) async fn request_editor_generated_images(
         create_openai_image_generation_with_model(
             http_client,
             settings,
-            request.model,
+            request.provider_model,
             request.prompt,
             request.negative_prompt,
             request.size,
@@ -418,7 +422,7 @@ pub(crate) async fn request_editor_generated_images(
         create_openai_image_edit_with_references_and_model(
             http_client,
             settings,
-            request.model,
+            request.provider_model,
             request.prompt,
             request.negative_prompt,
             request.size,
@@ -1926,7 +1930,10 @@ pub async fn get_editor_generation_pricing(
             "message": error.to_string(),
         }))
     })?;
-    Ok(json_success_body(Some(&request_context), pricing))
+    Ok(json_success_body(
+        Some(&request_context),
+        pricing.public_projection(),
+    ))
 }
 
 pub async fn list_editor_projects(
@@ -2764,7 +2771,7 @@ pub(crate) async fn enqueue_editor_image_generation_for_owner(
         matches!(normalized_kind, Some("publication-material"));
     let generation_options = normalize_editor_generation_options(
         if is_ui_design_generation || is_publication_material_generation {
-            Some(GPT_IMAGE_2_MODEL)
+            Some(GPT_IMAGE_2_5_BUSINESS_NAME)
         } else {
             payload.model.as_deref()
         },
@@ -2854,7 +2861,7 @@ pub(crate) async fn validate_editor_image_generation_parameters_for_owner(
         matches!(normalized_kind, Some("publication-material"));
     let generation_options = normalize_editor_generation_options(
         if is_ui_design_generation || is_publication_material_generation {
-            Some(GPT_IMAGE_2_MODEL)
+            Some(GPT_IMAGE_2_5_BUSINESS_NAME)
         } else {
             payload.model.as_deref()
         },
@@ -2987,7 +2994,7 @@ where
         matches!(normalized_kind, Some("publication-material"));
     let generation_options = normalize_editor_generation_options(
         if is_ui_design_generation || is_publication_material_generation {
-            Some(GPT_IMAGE_2_MODEL)
+            Some(GPT_IMAGE_2_5_BUSINESS_NAME)
         } else {
             payload.model.as_deref()
         },
@@ -3181,6 +3188,11 @@ where
             &settings,
             EditorImageProviderRequest {
                 model: generation_options.model,
+                provider_model: if generation_options.model == EDITOR_IMAGE_MODEL_NANOBANANA2 {
+                    generation_options.model
+                } else {
+                    GPT_IMAGE_2_5_GENERATION_MODEL
+                },
                 prompt: submitted_prompt.as_str(),
                 negative_prompt,
                 size: provider_request_size.as_ref(),
@@ -3832,7 +3844,7 @@ async fn resolve_editor_image_edit_price(
                 "message": error.to_string(),
             }))
         })?
-        .image_generation_mud_points(Some("quick-edit"), Some(model), Some(price_size));
+        .image_edit_model_mud_points(Some(model), Some(price_size));
     Ok(expected_price_mud_points)
 }
 
@@ -3975,7 +3987,16 @@ pub(crate) fn normalize_editor_generation_options(
     image_size: Option<&str>,
 ) -> EditorGenerationOptions {
     let normalized_model = match model.map(str::trim).filter(|value| !value.is_empty()) {
-        Some(GPT_IMAGE_2_MODEL) => GPT_IMAGE_2_MODEL,
+        // TODO: compatibility for persisted/client legacy `gpt-image-2`; do not
+        // rewrite the stored record, only use the current business value when a
+        // new task is submitted.
+        Some(
+            GPT_IMAGE_2_MODEL
+            | GPT_IMAGE_2_C_MODEL
+            | GPT_IMAGE_2_5_BUSINESS_NAME
+            | "gpt-image-2.5-flare-c"
+            | "gpt-image-2.5-sunburst-c",
+        ) => GPT_IMAGE_2_5_BUSINESS_NAME,
         Some(
             EDITOR_IMAGE_MODEL_NANOBANANA2
             | EDITOR_IMAGE_MODEL_NANOBANANA2_DISPLAY_ALIAS
@@ -3983,7 +4004,7 @@ pub(crate) fn normalize_editor_generation_options(
         ) => EDITOR_IMAGE_MODEL_NANOBANANA2,
         // 中文注释：未显式传模型的旧普通生成、快速编辑和生成规范继续走 gpt-image-2；
         // 角色 / 图标素材入口由前端显式传入 nanobanana2 默认值。
-        None => GPT_IMAGE_2_MODEL,
+        None => GPT_IMAGE_2_5_BUSINESS_NAME,
         _ => EDITOR_IMAGE_MODEL_NANOBANANA2,
     };
     let aspect_ratio = normalize_editor_generation_aspect_ratio(aspect_ratio);
@@ -6048,7 +6069,7 @@ pub(crate) async fn edit_editor_image_for_owner_with_source_snapshot(
             create_openai_image_edit_with_references_and_model(
                 &http_client,
                 &settings,
-                generation_options.model,
+                GPT_IMAGE_2_5_EDIT_MODEL,
                 prompt.as_str(),
                 Some("文字、水印、边框、按钮、UI 控件、变形主体"),
                 provider_size.as_str(),
@@ -8493,7 +8514,7 @@ pub(crate) async fn extract_editor_ui_design_assets_for_owner(
                     create_openai_image_edit_with_references_and_model(
                         &http_client,
                         &settings,
-                        generation_options.model,
+                        GPT_IMAGE_2_5_GENERATION_MODEL,
                         prompt.as_str(),
                         None,
                         generation_options.provider_size.as_str(),
@@ -17817,7 +17838,7 @@ mod tests {
     #[test]
     fn editor_generation_dimensions_follow_model_options() {
         let default_generation = normalize_editor_generation_options(None, Some("1:1"), Some("1K"));
-        assert_eq!(default_generation.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(default_generation.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(default_generation.size, "1024x1024");
 
         let nanobanana = normalize_editor_generation_options(
@@ -17847,7 +17868,7 @@ mod tests {
         assert_eq!(legacy_nanobanana_alias.aspect_ratio, "16:9");
 
         let gpt = normalize_editor_generation_options(Some("gpt-image-2"), Some("2:3"), Some("1K"));
-        assert_eq!(gpt.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(gpt.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(gpt.size, "683x1024");
         assert_eq!(gpt.provider_size, "688x1024");
         assert_eq!(gpt.aspect_ratio, "2:3");
@@ -17862,21 +17883,21 @@ mod tests {
 
         let gpt_cover =
             normalize_editor_generation_options(Some("gpt-image-2"), Some("4:3"), Some("1K"));
-        assert_eq!(gpt_cover.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(gpt_cover.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(gpt_cover.size, "1024x768");
         assert_eq!(gpt_cover.provider_size, "1024x768");
         assert_eq!(gpt_cover.aspect_ratio, "4:3");
 
         let gpt_landscape_2k =
             normalize_editor_generation_options(Some("gpt-image-2"), Some("16:9"), Some("2K"));
-        assert_eq!(gpt_landscape_2k.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(gpt_landscape_2k.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(gpt_landscape_2k.size, "2048x1152");
         assert_eq!(gpt_landscape_2k.aspect_ratio, "16:9");
         assert_eq!(gpt_landscape_2k.image_size, "2K");
 
         let gpt_portrait_2k =
             normalize_editor_generation_options(Some("gpt-image-2"), Some("9:16"), Some("2K"));
-        assert_eq!(gpt_portrait_2k.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(gpt_portrait_2k.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(gpt_portrait_2k.size, "1152x2048");
         assert_eq!(gpt_portrait_2k.aspect_ratio, "9:16");
         assert_eq!(gpt_portrait_2k.image_size, "2K");
@@ -19989,7 +20010,7 @@ mod tests {
         )
         .expect("UI extraction dimensions should pass");
 
-        assert_eq!(generation_options.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(generation_options.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(generation_options.size, "2048x2048");
         assert_eq!(
             resolve_editor_ui_design_asset_extraction_price(

server-rs/crates/api-server/src/editor_project_icon.rs

@@ -64,7 +64,7 @@ use crate::{
     state::AppState,
 };
 
-const ICON_SPEC_MODEL: &str = "gpt-image-2";
+const ICON_SPEC_MODEL: &str = "gpt-image-2.5";
 const ICON_SPEC_ASPECT_RATIO: &str = "16:9";
 const ICON_SPEC_IMAGE_SIZE: &str = "2K";
 const ICON_SPEC_SIZE: &str = "2048x1152";

server-rs/crates/api-server/src/openai_image_generation.rs

@@ -1,17 +1,14 @@
 use axum::http::StatusCode;
 use platform_image::{
-    DownloadedImage, GeneratedImages, PlatformImageError, PlatformImageStatusHint, ReferenceImage,
-    VECTOR_ENGINE_PROVIDER, VectorEngineImageSettings, build_vector_engine_image_http_client,
-    create_vector_engine_image_edit, create_vector_engine_image_edit_with_references,
-    create_vector_engine_image_edit_with_references_and_model,
-    create_vector_engine_image_generation, create_vector_engine_image_generation_with_model,
-    create_vector_engine_nanobanana_generate_content,
+    DownloadedImage, GeneratedImages, ImageProvider, ImageProviderClient, ImageProviderSettings,
+    NANOBANANA_2_MODEL, PlatformImageError, PlatformImageStatusHint, ReferenceImage,
+    VECTOR_ENGINE_PROVIDER, build_image_http_client, create_image_edit,
+    create_image_edit_with_references, create_image_edit_with_references_and_model,
+    create_image_generation, create_image_generation_with_model,
+    create_nanobanana_generate_content,
 };
 #[cfg(test)]
-use platform_image::{
-    build_vector_engine_image_request_body, vector_engine_images_edit_url,
-    vector_engine_images_generation_url,
-};
+use platform_image::{build_image_request_body, images_edit_url, images_generation_url};
 use serde_json::{Value, json};
 use std::time::Instant;
 use time::OffsetDateTime;
@@ -27,9 +24,10 @@ use crate::{
     tracking::record_external_generation_run_after_success,
 };
 
-pub(crate) use platform_image::GPT_IMAGE_2_MODEL;
-#[cfg(test)]
-use platform_image::VECTOR_ENGINE_GPT_IMAGE_2_MODEL;
+pub(crate) use platform_image::{
+    GPT_IMAGE_2_5_BUSINESS_NAME, GPT_IMAGE_2_5_EDIT_MODEL, GPT_IMAGE_2_5_GENERATION_MODEL,
+    GPT_IMAGE_2_MODEL,
+};
 
 pub(crate) type OpenAiGeneratedImages = GeneratedImages;
 pub(crate) type DownloadedOpenAiImage = DownloadedImage;
@@ -45,6 +43,8 @@ pub(crate) struct OpenAiImageSettings {
     pub external_api_audit_user_id: Option<String>,
     pub external_api_audit_profile_id: Option<String>,
     pub external_api_audit_request_id: Option<String>,
+    pub tiantoken_client: Option<ImageProviderClient>,
+    pub vector_engine_client: Option<ImageProviderClient>,
 }
 
 impl std::fmt::Debug for OpenAiImageSettings {
@@ -71,6 +71,11 @@ impl std::fmt::Debug for OpenAiImageSettings {
                 "external_api_audit_request_id",
                 &self.external_api_audit_request_id,
             )
+            .field("tiantoken_client_enabled", &self.tiantoken_client.is_some())
+            .field(
+                "vector_engine_client_enabled",
+                &self.vector_engine_client.is_some(),
+            )
             .finish()
     }
 }
@@ -110,18 +115,22 @@ pub(crate) fn require_openai_image_settings(
         external_api_audit_user_id: None,
         external_api_audit_profile_id: None,
         external_api_audit_request_id: None,
+        tiantoken_client: Some(state.tiantoken_image_client().clone()),
+        vector_engine_client: Some(state.vector_engine_image_client().clone()),
     })
 }
 
 pub(crate) fn build_openai_image_http_client(
     settings: &OpenAiImageSettings,
 ) -> Result<reqwest::Client, AppError> {
-    build_vector_engine_image_http_client(&settings.provider_settings())
-        .map_err(map_platform_image_error)
+    if let Some(client) = settings.tiantoken_client.as_ref() {
+        return Ok(client.http_client().clone());
+    }
+    build_image_http_client(&settings.provider_settings()).map_err(map_platform_image_error)
 }
 
 pub(crate) async fn create_openai_image_generation(
-    http_client: &reqwest::Client,
+    _http_client: &reqwest::Client,
     settings: &OpenAiImageSettings,
     prompt: &str,
     negative_prompt: Option<&str>,
@@ -138,9 +147,11 @@ pub(crate) async fn create_openai_image_generation(
         "negativePromptChars": negative_prompt.map(str::chars).map(Iterator::count),
         "referenceImageCount": reference_images.len(),
     });
-    let result = create_vector_engine_image_generation(
-        http_client,
-        &settings.provider_settings(),
+    let provider_client = settings.client_for_model(GPT_IMAGE_2_5_GENERATION_MODEL);
+    let provider_settings = settings.provider_settings_for_model(GPT_IMAGE_2_5_GENERATION_MODEL);
+    let result = create_image_generation(
+        provider_client.http_client(),
+        &provider_settings,
         prompt,
         negative_prompt,
         size,
@@ -162,7 +173,7 @@ pub(crate) async fn create_openai_image_generation(
 
 #[allow(clippy::too_many_arguments)]
 pub(crate) async fn create_openai_image_generation_with_model(
-    http_client: &reqwest::Client,
+    _http_client: &reqwest::Client,
     settings: &OpenAiImageSettings,
     model: &str,
     prompt: &str,
@@ -181,9 +192,11 @@ pub(crate) async fn create_openai_image_generation_with_model(
         "negativePromptChars": negative_prompt.map(str::chars).map(Iterator::count),
         "referenceImageCount": reference_images.len(),
     });
-    let result = create_vector_engine_image_generation_with_model(
-        http_client,
-        &settings.provider_settings(),
+    let provider_client = settings.client_for_model(model);
+    let provider_settings = settings.provider_settings_for_model(model);
+    let result = create_image_generation_with_model(
+        provider_client.http_client(),
+        &provider_settings,
         model,
         prompt,
         negative_prompt,
@@ -206,7 +219,7 @@ pub(crate) async fn create_openai_image_generation_with_model(
 
 #[allow(clippy::too_many_arguments)]
 pub(crate) async fn create_openai_nanobanana_generate_content(
-    http_client: &reqwest::Client,
+    _http_client: &reqwest::Client,
     settings: &OpenAiImageSettings,
     model: &str,
     prompt: &str,
@@ -225,9 +238,11 @@ pub(crate) async fn create_openai_nanobanana_generate_content(
         "negativePromptChars": negative_prompt.map(str::chars).map(Iterator::count),
         "referenceImageCount": reference_images.len(),
     });
-    let result = create_vector_engine_nanobanana_generate_content(
-        http_client,
-        &settings.provider_settings(),
+    let provider_client = settings.client_for_model(model);
+    let provider_settings = settings.provider_settings_for_model(model);
+    let result = create_nanobanana_generate_content(
+        provider_client.http_client(),
+        &provider_settings,
         model,
         prompt,
         negative_prompt,
@@ -249,7 +264,7 @@ pub(crate) async fn create_openai_nanobanana_generate_content(
 }
 
 pub(crate) async fn create_openai_image_edit(
-    http_client: &reqwest::Client,
+    _http_client: &reqwest::Client,
     settings: &OpenAiImageSettings,
     prompt: &str,
     negative_prompt: Option<&str>,
@@ -264,9 +279,11 @@ pub(crate) async fn create_openai_image_edit(
         "negativePromptChars": negative_prompt.map(str::chars).map(Iterator::count),
         "referenceImageCount": 1,
     });
-    let result = create_vector_engine_image_edit(
-        http_client,
-        &settings.provider_settings(),
+    let provider_client = settings.client_for_model(GPT_IMAGE_2_5_EDIT_MODEL);
+    let provider_settings = settings.provider_settings_for_model(GPT_IMAGE_2_5_EDIT_MODEL);
+    let result = create_image_edit(
+        provider_client.http_client(),
+        &provider_settings,
         prompt,
         negative_prompt,
         size,
@@ -286,7 +303,7 @@ pub(crate) async fn create_openai_image_edit(
 }
 
 pub(crate) async fn create_openai_image_edit_with_references(
-    http_client: &reqwest::Client,
+    _http_client: &reqwest::Client,
     settings: &OpenAiImageSettings,
     prompt: &str,
     negative_prompt: Option<&str>,
@@ -303,9 +320,11 @@ pub(crate) async fn create_openai_image_edit_with_references(
         "negativePromptChars": negative_prompt.map(str::chars).map(Iterator::count),
         "referenceImageCount": reference_images.len(),
     });
-    let result = create_vector_engine_image_edit_with_references(
-        http_client,
-        &settings.provider_settings(),
+    let provider_client = settings.client_for_model(GPT_IMAGE_2_5_EDIT_MODEL);
+    let provider_settings = settings.provider_settings_for_model(GPT_IMAGE_2_5_EDIT_MODEL);
+    let result = create_image_edit_with_references(
+        provider_client.http_client(),
+        &provider_settings,
         prompt,
         negative_prompt,
         size,
@@ -327,7 +346,7 @@ pub(crate) async fn create_openai_image_edit_with_references(
 
 #[allow(clippy::too_many_arguments)]
 pub(crate) async fn create_openai_image_edit_with_references_and_model(
-    http_client: &reqwest::Client,
+    _http_client: &reqwest::Client,
     settings: &OpenAiImageSettings,
     model: &str,
     prompt: &str,
@@ -345,9 +364,11 @@ pub(crate) async fn create_openai_image_edit_with_references_and_model(
         "negativePromptChars": negative_prompt.map(str::chars).map(Iterator::count),
         "referenceImageCount": reference_images.len(),
     });
-    let result = create_vector_engine_image_edit_with_references_and_model(
-        http_client,
-        &settings.provider_settings(),
+    let provider_client = settings.client_for_model(model);
+    let provider_settings = settings.provider_settings_for_model(model);
+    let result = create_image_edit_with_references_and_model(
+        provider_client.http_client(),
+        &provider_settings,
         model,
         prompt,
         negative_prompt,
@@ -376,7 +397,7 @@ pub(crate) fn build_openai_image_request_body(
     candidate_count: u32,
     reference_images: &[String],
 ) -> Value {
-    build_vector_engine_image_request_body(
+    build_image_request_body(
         prompt,
         negative_prompt,
         size,
@@ -386,6 +407,24 @@ pub(crate) fn build_openai_image_request_body(
 }
 
 impl OpenAiImageSettings {
+    fn client_for_model(&self, model: &str) -> &ImageProviderClient {
+        if model == NANOBANANA_2_MODEL {
+            self.vector_engine_client
+                .as_ref()
+                .expect("vector engine image client is initialized at startup")
+        } else {
+            self.tiantoken_client
+                .as_ref()
+                .expect("tiantoken image client is initialized at startup")
+        }
+    }
+
+    fn provider_settings_for_model(&self, model: &str) -> ImageProviderSettings {
+        let mut settings = self.client_for_model(model).settings().clone();
+        settings.request_deadline = self.request_deadline;
+        settings
+    }
+
     pub(crate) fn with_external_api_audit_actor(
         mut self,
         user_id: Option<String>,
@@ -409,8 +448,9 @@ impl OpenAiImageSettings {
         self
     }
 
-    pub(crate) fn provider_settings(&self) -> VectorEngineImageSettings {
-        VectorEngineImageSettings {
+    pub(crate) fn provider_settings(&self) -> ImageProviderSettings {
+        ImageProviderSettings {
+            provider: ImageProvider::Tiantoken,
             base_url: self.base_url.clone(),
             api_key: self.api_key.clone(),
             request_timeout_ms: self.request_timeout_ms.max(1),
@@ -578,13 +618,13 @@ pub(crate) fn map_platform_image_error(error: PlatformImageError) -> AppError {
 }
 
 #[cfg(test)]
-fn vector_engine_images_generation_url_for_test(settings: &OpenAiImageSettings) -> String {
-    vector_engine_images_generation_url(&settings.provider_settings())
+fn images_generation_url_for_test(settings: &OpenAiImageSettings) -> String {
+    images_generation_url(&settings.provider_settings())
 }
 
 #[cfg(test)]
-fn vector_engine_images_edit_url_for_test(settings: &OpenAiImageSettings) -> String {
-    vector_engine_images_edit_url(&settings.provider_settings())
+fn images_edit_url_for_test(settings: &OpenAiImageSettings) -> String {
+    images_edit_url(&settings.provider_settings())
 }
 
 #[cfg(test)]
@@ -611,6 +651,8 @@ mod tests {
             external_api_audit_user_id: None,
             external_api_audit_profile_id: None,
             external_api_audit_request_id: None,
+            tiantoken_client: None,
+            vector_engine_client: None,
         }
         .with_external_api_audit_context(&request_context, None, None);
 
@@ -631,7 +673,7 @@ mod tests {
             &["data:image/png;base64,abcd".to_string()],
         );
 
-        assert_eq!(body["model"], GPT_IMAGE_2_MODEL);
+        assert_eq!(body["model"], GPT_IMAGE_2_5_GENERATION_MODEL);
         assert_eq!(body["size"], "1536x1024");
         assert_eq!(body["n"], 2);
         assert!(body.get("official_fallback").is_none());
@@ -650,6 +692,8 @@ mod tests {
             external_api_audit_user_id: None,
             external_api_audit_profile_id: None,
             external_api_audit_request_id: None,
+            tiantoken_client: None,
+            vector_engine_client: None,
         };
         let v1_settings = OpenAiImageSettings {
             base_url: "https://vector.example/v1".to_string(),
@@ -660,14 +704,16 @@ mod tests {
             external_api_audit_user_id: None,
             external_api_audit_profile_id: None,
             external_api_audit_request_id: None,
+            tiantoken_client: None,
+            vector_engine_client: None,
         };
 
         assert_eq!(
-            vector_engine_images_generation_url_for_test(&root_settings),
+            images_generation_url_for_test(&root_settings),
             "https://vector.example/v1/images/generations"
         );
         assert_eq!(
-            vector_engine_images_generation_url_for_test(&v1_settings),
+            images_generation_url_for_test(&v1_settings),
             "https://vector.example/v1/images/generations"
         );
     }
@@ -683,6 +729,8 @@ mod tests {
             external_api_audit_user_id: None,
             external_api_audit_profile_id: None,
             external_api_audit_request_id: None,
+            tiantoken_client: None,
+            vector_engine_client: None,
         };
         let v1_settings = OpenAiImageSettings {
             base_url: "https://vector.example/v1".to_string(),
@@ -693,14 +741,16 @@ mod tests {
             external_api_audit_user_id: None,
             external_api_audit_profile_id: None,
             external_api_audit_request_id: None,
+            tiantoken_client: None,
+            vector_engine_client: None,
         };
 
         assert_eq!(
-            vector_engine_images_edit_url_for_test(&root_settings),
+            images_edit_url_for_test(&root_settings),
             "https://vector.example/v1/images/edits"
         );
         assert_eq!(
-            vector_engine_images_edit_url_for_test(&v1_settings),
+            images_edit_url_for_test(&v1_settings),
             "https://vector.example/v1/images/edits"
         );
     }
@@ -716,6 +766,8 @@ mod tests {
             external_api_audit_user_id: None,
             external_api_audit_profile_id: None,
             external_api_audit_request_id: None,
+            tiantoken_client: None,
+            vector_engine_client: None,
         };
         let http_client = reqwest::Client::new();
 
@@ -764,7 +816,7 @@ mod tests {
             latency_ms: Some(321),
             prompt_chars: Some(42),
             reference_image_count: Some(1),
-            image_model: Some(VECTOR_ENGINE_GPT_IMAGE_2_MODEL),
+            image_model: Some(GPT_IMAGE_2_MODEL),
         };
         let tracking = crate::external_api_audit::build_external_api_failure_tracking_draft(
             &build_external_api_failure_draft_from_platform_image_audit(&audit),
@@ -782,10 +834,7 @@ mod tests {
         assert_eq!(tracking.metadata["retryable"], true);
         assert_eq!(tracking.metadata["promptChars"], 42);
         assert_eq!(tracking.metadata["referenceImageCount"], 1);
-        assert_eq!(
-            tracking.metadata["imageModel"],
-            VECTOR_ENGINE_GPT_IMAGE_2_MODEL
-        );
+        assert_eq!(tracking.metadata["imageModel"], GPT_IMAGE_2_MODEL);
     }
 }
 

server-rs/crates/api-server/src/raw_image.rs

@@ -6,8 +6,8 @@ use axum::{
 use bytes::Bytes;
 use image::{ImageDecoder, ImageFormat, ImageReader};
 use platform_image::{
-    GPT_IMAGE_2_2K_LONG_EDGE_THRESHOLD, RAW_IMAGE_MAX_EDGE, RAW_IMAGE_MAX_PIXELS,
-    RawImageEditImage, RawImageEditOptions, create_vector_engine_raw_image_edit,
+    GPT_IMAGE_2_2K_LONG_EDGE_THRESHOLD, GPT_IMAGE_2_5_EDIT_MODEL, RAW_IMAGE_MAX_EDGE,
+    RAW_IMAGE_MAX_PIXELS, RawImageEditImage, RawImageEditOptions, create_raw_image_edit,
     validate_raw_image_edit_dimensions,
 };
 use serde::Serialize;
@@ -148,7 +148,7 @@ pub(crate) async fn edit_raw_image(
     });
     let started_at_micros = (OffsetDateTime::now_utc().unix_timestamp_nanos() / 1_000) as i64;
     let operation = async move {
-        let generated = match create_vector_engine_raw_image_edit(
+        let generated = match create_raw_image_edit(
             &http_client,
             &provider_settings,
             prepared.prompt.as_str(),
@@ -572,7 +572,7 @@ async fn raw_image_edit_price(state: &AppState, width: u32, height: u32) -> Resu
         .editor_generation_pricing()
         .await
         .map(|pricing| {
-            pricing.image_generation_mud_points(Some("quick-edit"), Some("gpt-image-2"), Some(tier))
+            pricing.image_edit_model_mud_points(Some(GPT_IMAGE_2_5_EDIT_MODEL), Some(tier))
         })
         .map_err(|error| {
             AppError::from_status(StatusCode::INTERNAL_SERVER_ERROR).with_details(json!({

server-rs/crates/api-server/src/state.rs

@@ -23,6 +23,9 @@ use platform_auth::{
     RefreshCookieConfig, RefreshCookieError, RefreshCookieSameSite, SmsAuthConfig, SmsAuthProvider,
     SmsAuthProviderKind, SmsProviderError, WechatProvider, sign_access_token, verify_access_token,
 };
+use platform_image::{
+    ImageProvider, ImageProviderClient, ImageProviderSettings, build_image_provider_client,
+};
 use platform_llm::{LlmClient, LlmConfig, LlmError, LlmProvider, OpenAiChatTokenBudgetField};
 use platform_matting::{MattingClient, MattingConfig};
 use platform_oss::{OssClient, OssConfig, OssError};
@@ -306,6 +309,8 @@ pub struct AppStateInner {
     /// 非 Suno 的文本、图片和旧版音频生成 provider 配置。
     tiantoken_base_url: String,
     tiantoken_api_key: Option<String>,
+    vector_engine_image_client: ImageProviderClient,
+    tiantoken_image_client: ImageProviderClient,
     matting_client: Option<MattingClient>,
     bgfilter_provider_http_client: reqwest::Client,
     bgfilter_worker_http_client: reqwest::Client,
@@ -605,6 +610,18 @@ impl AppState {
         .map_err(|error| AppStateInitError::DependencyUnavailable(error.to_string()))?;
         let tiantoken_base_url = crate::config::tiantoken_base_url(&config);
         let tiantoken_api_key = crate::config::tiantoken_api_key(&config);
+        let vector_engine_image_client = build_required_image_provider_client(
+            ImageProvider::VectorEngine,
+            config.vector_engine_base_url.clone(),
+            config.vector_engine_api_key.clone(),
+            config.vector_engine_image_request_timeout_ms,
+        )?;
+        let tiantoken_image_client = build_required_image_provider_client(
+            ImageProvider::Tiantoken,
+            tiantoken_base_url.clone(),
+            tiantoken_api_key.clone(),
+            config.vector_engine_image_request_timeout_ms,
+        )?;
         let llm_client = build_llm_client(&config)?;
         let vector_engine_llm_client = build_vector_engine_llm_client(
             &config,
@@ -688,6 +705,8 @@ impl AppState {
             vector_engine_llm_client,
             tiantoken_base_url,
             tiantoken_api_key,
+            vector_engine_image_client,
+            tiantoken_image_client,
             matting_client,
             bgfilter_provider_http_client,
             bgfilter_worker_http_client,
@@ -1598,6 +1617,14 @@ impl AppState {
         self.tiantoken_api_key.as_deref()
     }
 
+    pub(crate) fn vector_engine_image_client(&self) -> &ImageProviderClient {
+        &self.vector_engine_image_client
+    }
+
+    pub(crate) fn tiantoken_image_client(&self) -> &ImageProviderClient {
+        &self.tiantoken_image_client
+    }
+
     pub fn matting_client(&self) -> Option<&MattingClient> {
         self.matting_client.as_ref()
     }
@@ -2309,6 +2336,50 @@ impl AdminRuntime {
     }
 }
 
+fn build_required_image_provider_client(
+    provider: ImageProvider,
+    base_url: String,
+    api_key: Option<String>,
+    request_timeout_ms: u64,
+) -> Result<ImageProviderClient, AppStateInitError> {
+    #[cfg(test)]
+    let (base_url, api_key) = (
+        if base_url.trim().is_empty() {
+            "http://127.0.0.1".to_string()
+        } else {
+            base_url
+        },
+        api_key.or_else(|| Some("test-key".to_string())),
+    );
+    #[cfg(not(test))]
+    let (base_url, api_key) = (base_url, api_key);
+    let base_url = base_url.trim().trim_end_matches('/');
+    if base_url.is_empty() {
+        return Err(AppStateInitError::DependencyUnavailable(format!(
+            "{} 图片 provider 缺少 BASE_URL 配置",
+            provider.as_str()
+        )));
+    }
+    let api_key = api_key
+        .as_deref()
+        .map(str::trim)
+        .filter(|value| !value.is_empty())
+        .ok_or_else(|| {
+            AppStateInitError::DependencyUnavailable(format!(
+                "{} 图片 provider 缺少 API_KEY 配置",
+                provider.as_str()
+            ))
+        })?;
+    build_image_provider_client(ImageProviderSettings {
+        provider,
+        base_url: base_url.to_string(),
+        api_key: api_key.to_string(),
+        request_timeout_ms: request_timeout_ms.max(1),
+        request_deadline: None,
+    })
+    .map_err(|error| AppStateInitError::DependencyUnavailable(error.to_string()))
+}
+
 fn build_oss_client(config: &AppConfig) -> Result<Option<OssClient>, AppStateInitError> {
     let oss_fields = [
         ("ALIYUN_OSS_BUCKET", config.oss_bucket.as_deref()),

server-rs/crates/platform-editor-agent/src/agent/tools/edit_image.rs

@@ -2,7 +2,7 @@ use crate::agent::asset::ImageId;
 use crate::agent::prompt::{PENDING_USER_CONFIRMATION_MESSAGE, edit_image_tool_description};
 use crate::agent::tools::context::EditorToolContext;
 use crate::framework::tool::{Tool, ToolFailure, ToolFailureKind};
-use platform_image::GPT_IMAGE_2_MODEL;
+use platform_image::GPT_IMAGE_2_5_BUSINESS_NAME;
 use serde::{Deserialize, Serialize};
 use serde_json::{Value, json};
 use std::error::Error;
@@ -33,7 +33,7 @@ impl Display for EditImageError {
             EditImageError::InvalidModel(model) => {
                 write!(
                     f,
-                    "{model} is not a valid model name, only {GPT_IMAGE_2_MODEL} is supported for now."
+                    "{model} is not a valid model name, only {GPT_IMAGE_2_5_BUSINESS_NAME} is supported for now."
                 )
             }
         }
@@ -52,7 +52,7 @@ pub struct EditImageToolArgs {
     pub model: String,
 }
 fn default_model_name() -> String {
-    GPT_IMAGE_2_MODEL.to_string()
+    GPT_IMAGE_2_5_BUSINESS_NAME.to_string()
 }
 
 #[derive(Debug, Clone, Serialize, Deserialize)]
@@ -90,9 +90,9 @@ impl Tool for EditImageTool {
               // TODO need to introduce size param, but that needs more metadata such as original image size, skip in this version
                 "model": {
                     "type": "string",
-                    "enum": [GPT_IMAGE_2_MODEL],
-                    "default": GPT_IMAGE_2_MODEL,
-                    "description": format!("图片编辑固定使用{GPT_IMAGE_2_MODEL}")
+                    "enum": [GPT_IMAGE_2_5_BUSINESS_NAME],
+                    "default": GPT_IMAGE_2_5_BUSINESS_NAME,
+                    "description": format!("图片编辑固定使用{GPT_IMAGE_2_5_BUSINESS_NAME}")
                 }
             },
             "required": ["object_image_id", "prompt"],
@@ -155,7 +155,7 @@ pub struct EditorImageEditResult {
 impl EditImageTool {
     /// Validate the semantic correctness of the arguments.
     pub fn validate_args(&self, args: &EditImageToolArgs) -> Option<EditImageError> {
-        if args.model != GPT_IMAGE_2_MODEL {
+        if args.model != GPT_IMAGE_2_5_BUSINESS_NAME {
             return Some(EditImageError::InvalidModel(args.model.clone()));
         }
         if args.prompt.trim().is_empty() {
@@ -210,7 +210,7 @@ mod tests {
             "sourceType": "generated",
             "prompt": "修改图片",
             "actualPrompt": "修改后的图片",
-            "model": "gpt-image-2",
+            "model": "gpt-image-2.5",
             "taskId": "task-2",
             "resource": null,
             "asset": null,

server-rs/crates/platform-editor-agent/src/agent/tools/generate_icon_spritesheet.rs

@@ -10,7 +10,7 @@ use crate::agent::tools::image_generation_options::{
     validate_image_generation_options,
 };
 use crate::framework::tool::{Tool, ToolFailure, ToolFailureKind};
-use platform_image::{GPT_IMAGE_2_MODEL, NANOBANANA_2_MODEL};
+use platform_image::{GPT_IMAGE_2_5_BUSINESS_NAME, NANOBANANA_2_MODEL};
 use serde::{Deserialize, Serialize};
 use serde_json::{Value, json};
 use std::error::Error;
@@ -39,7 +39,7 @@ impl Display for GenerateIconSpritesheetError {
         match self {
             Self::InvalidModel(model) => write!(
                 f,
-                "{model} is not a valid image model; supported models: {NANOBANANA_2_MODEL}, {GPT_IMAGE_2_MODEL}"
+                "{model} is not a valid image model; supported models: {NANOBANANA_2_MODEL}, {GPT_IMAGE_2_5_BUSINESS_NAME}"
             ),
             Self::InvalidAspectRatio(aspect_ratio) => {
                 write!(f, "invalid aspect ratio: {aspect_ratio}")

server-rs/crates/platform-editor-agent/src/agent/tools/generate_image.rs

@@ -8,7 +8,7 @@ use crate::agent::tools::image_generation_options::{
     validate_image_generation_options,
 };
 use crate::framework::tool::{Tool, ToolFailure, ToolFailureKind};
-use platform_image::{GPT_IMAGE_2_MODEL, NANOBANANA_2_MODEL};
+use platform_image::{GPT_IMAGE_2_5_BUSINESS_NAME, NANOBANANA_2_MODEL};
 use serde::{Deserialize, Serialize};
 use serde_json::{Value, json};
 use std::error::Error;
@@ -33,11 +33,11 @@ impl Display for GenerateImageError {
         match self {
             Self::InvalidModel(model) => write!(
                 f,
-                "{model} is not a valid image model; supported models: {NANOBANANA_2_MODEL}, {GPT_IMAGE_2_MODEL}"
+                "{model} is not a valid image model; supported models: {NANOBANANA_2_MODEL}, {GPT_IMAGE_2_5_BUSINESS_NAME}"
             ),
             Self::UnsupportedUiDesignModel(model) => write!(
                 f,
-                "{model} is not supported for UI design generation; required model: {GPT_IMAGE_2_MODEL}"
+                "{model} is not supported for UI design generation; required model: {GPT_IMAGE_2_5_BUSINESS_NAME}"
             ),
             Self::InvalidAspectRatio(aspect_ratio) => {
                 write!(f, "invalid aspect ratio: {aspect_ratio}")
@@ -222,7 +222,7 @@ mod tests {
             "sourceType": "generated",
             "prompt": "生成一张图片",
             "actualPrompt": "生成一张清晰图片",
-            "model": "gpt-image-2",
+            "model": "gpt-image-2.5",
             "taskId": "task-1",
             "resource": null,
             "asset": null,

server-rs/crates/platform-editor-agent/src/agent/tools/generate_ui_design.rs

@@ -12,7 +12,7 @@ use crate::agent::tools::image_generation_options::{
 };
 use crate::framework::tool::ToolFailureKind;
 use crate::framework::tool::{Tool, ToolFailure};
-use platform_image::GPT_IMAGE_2_MODEL;
+use platform_image::GPT_IMAGE_2_5_BUSINESS_NAME;
 use serde::{Deserialize, Serialize};
 use serde_json::{Value, json};
 
@@ -34,7 +34,7 @@ pub struct GenerateUiDesignToolArgs {
 }
 
 fn default_ui_design_model() -> String {
-    GPT_IMAGE_2_MODEL.to_string()
+    GPT_IMAGE_2_5_BUSINESS_NAME.to_string()
 }
 
 impl Tool for GenerateUiDesignTool {
@@ -54,9 +54,9 @@ impl Tool for GenerateUiDesignTool {
                 "prompt": { "type": "string", "description": "完整 UI 画面、信息层级、视觉风格和构图描述。" },
                 "model": {
                     "type": "string",
-                    "enum": [GPT_IMAGE_2_MODEL],
-                    "default": GPT_IMAGE_2_MODEL,
-                    "description": "UI 设计图固定使用 gpt-image-2。"
+                    "enum": [GPT_IMAGE_2_5_BUSINESS_NAME],
+                    "default": GPT_IMAGE_2_5_BUSINESS_NAME,
+                    "description": "UI 设计图固定使用 gpt-image-2.5。"
                 },
                 "reference_image_ids": { "type": "array", "items": { "type": "string" }, "description": "image_id(s) for desc UI 风格或布局" },
                 "aspect_ratio": image_aspect_ratio_parameter_schema(),
@@ -95,7 +95,7 @@ impl Tool for GenerateUiDesignTool {
 
 impl GenerateUiDesignTool {
     pub fn validate_args(&self, args: &GenerateUiDesignToolArgs) -> Result<(), GenerateImageError> {
-        if args.model != GPT_IMAGE_2_MODEL {
+        if args.model != GPT_IMAGE_2_5_BUSINESS_NAME {
             return Err(GenerateImageError::UnsupportedUiDesignModel(
                 args.model.clone(),
             ));
@@ -165,11 +165,11 @@ mod tests {
 
         assert_eq!(
             parameters["properties"]["model"]["enum"],
-            json!([GPT_IMAGE_2_MODEL])
+            json!([GPT_IMAGE_2_5_BUSINESS_NAME])
         );
         assert_eq!(
             parameters["properties"]["model"]["default"],
-            GPT_IMAGE_2_MODEL
+            GPT_IMAGE_2_5_BUSINESS_NAME
         );
         assert_eq!(
             parameters["properties"]["image_size"]["enum"],
@@ -184,7 +184,10 @@ mod tests {
                 .as_array()
                 .is_some_and(|required| required.contains(&json!("model")))
         );
-        assert!(tool.validate_args(&args(GPT_IMAGE_2_MODEL)).is_ok());
+        assert!(
+            tool.validate_args(&args(GPT_IMAGE_2_5_BUSINESS_NAME))
+                .is_ok()
+        );
         assert!(matches!(
             tool.validate_args(&args(NANOBANANA_2_MODEL)),
             Err(GenerateImageError::UnsupportedUiDesignModel(model)) if model == NANOBANANA_2_MODEL
@@ -198,7 +201,7 @@ mod tests {
         }))
         .expect("旧版 UI 设计参数应能反序列化");
 
-        assert_eq!(args.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(args.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert!(tool().validate_args(&args).is_ok());
     }
 }

server-rs/crates/platform-editor-agent/src/agent/tools/image_generation_options.rs

@@ -1,4 +1,4 @@
-use platform_image::{GPT_IMAGE_2_MODEL, NANOBANANA_2_MODEL};
+use platform_image::{GPT_IMAGE_2_5_BUSINESS_NAME, NANOBANANA_2_MODEL};
 use serde_json::{Value, json};
 use std::error::Error;
 use std::fmt::Display;
@@ -21,7 +21,7 @@ impl Display for ImageGenerationOptionsError {
         match self {
             Self::InvalidModel(model) => write!(
                 f,
-                "{model} is not a valid image model; supported models: {NANOBANANA_2_MODEL}, {GPT_IMAGE_2_MODEL}"
+                "{model} is not a valid image model; supported models: {NANOBANANA_2_MODEL}, {GPT_IMAGE_2_5_BUSINESS_NAME}"
             ),
             Self::InvalidAspectRatio(aspect_ratio) => write!(
                 f,
@@ -75,9 +75,9 @@ pub fn validate_image_generation_options(
 pub fn image_model_parameter_schema() -> Value {
     json!({
         "type": "string",
-        "enum": [NANOBANANA_2_MODEL, GPT_IMAGE_2_MODEL],
+        "enum": [NANOBANANA_2_MODEL, GPT_IMAGE_2_5_BUSINESS_NAME],
         "default": NANOBANANA_2_MODEL,
-        "description": "生图模型。默认 gemini-3.1-flash-image-preview（user may call it nanobanana2）；也可选择 gpt-image-2。"
+        "description": "生图模型。默认 gemini-3.1-flash-image-preview（user may call it nanobanana2）；也可选择 gpt-image-2.5。"
     })
 }
 
@@ -95,7 +95,7 @@ pub fn image_size_parameter_schema() -> Value {
         "type": "string",
         "enum": NANOBANANA_2_IMAGE_SIZES,
         "default": DEFAULT_IMAGE_SIZE,
-        "description": "图片尺寸档位。nanobanana2 支持 0.5K、1K、2K；gpt-image-2 仅支持 1K、2K；默认 1K。"
+        "description": "图片尺寸档位。nanobanana2 支持 0.5K、1K、2K；gpt-image-2.5 仅支持 1K、2K；默认 1K。"
     })
 }
 
@@ -104,14 +104,14 @@ pub fn gpt_image_2_size_parameter_schema() -> Value {
         "type": "string",
         "enum": GPT_IMAGE_2_IMAGE_SIZES,
         "default": DEFAULT_IMAGE_SIZE,
-        "description": "图片尺寸档位。gpt-image-2 仅支持 1K、2K；默认 1K。"
+        "description": "图片尺寸档位。gpt-image-2.5 仅支持 1K、2K；默认 1K。"
     })
 }
 
 pub fn image_model_size_constraint_schema() -> Value {
     json!({
         "if": {
-            "properties": { "model": { "const": GPT_IMAGE_2_MODEL } },
+            "properties": { "model": { "const": GPT_IMAGE_2_5_BUSINESS_NAME } },
             // model 省略时运行时默认 nanobanana2，仍允许 0.5K。
             "required": ["model"]
         },
@@ -126,7 +126,7 @@ pub fn image_model_size_constraint_schema() -> Value {
 fn supported_image_sizes(model: &str) -> Option<&'static [&'static str]> {
     match model {
         NANOBANANA_2_MODEL => Some(NANOBANANA_2_IMAGE_SIZES),
-        GPT_IMAGE_2_MODEL => Some(GPT_IMAGE_2_IMAGE_SIZES),
+        GPT_IMAGE_2_5_BUSINESS_NAME => Some(GPT_IMAGE_2_IMAGE_SIZES),
         _ => None,
     }
 }
@@ -150,14 +150,18 @@ mod tests {
             }
             for image_size in GPT_IMAGE_2_IMAGE_SIZES {
                 assert!(
-                    validate_image_generation_options(GPT_IMAGE_2_MODEL, aspect_ratio, image_size,)
-                        .is_ok()
+                    validate_image_generation_options(
+                        GPT_IMAGE_2_5_BUSINESS_NAME,
+                        aspect_ratio,
+                        image_size,
+                    )
+                    .is_ok()
                 );
             }
         }
 
         assert!(matches!(
-            validate_image_generation_options(GPT_IMAGE_2_MODEL, "1:1", "0.5K"),
+            validate_image_generation_options(GPT_IMAGE_2_5_BUSINESS_NAME, "1:1", "0.5K"),
             Err(ImageGenerationOptionsError::InvalidImageSize { .. })
         ));
         assert!(matches!(
@@ -192,7 +196,7 @@ mod tests {
         let model_size_constraint = image_model_size_constraint_schema();
         assert_eq!(
             model_size_constraint["if"]["properties"]["model"]["const"],
-            GPT_IMAGE_2_MODEL
+            GPT_IMAGE_2_5_BUSINESS_NAME
         );
         assert_eq!(model_size_constraint["if"]["required"], json!(["model"]));
         assert_eq!(

server-rs/crates/platform-editor-agent/src/agent/tools/mod.rs

@@ -26,7 +26,7 @@ mod tests {
     use super::generate_video::{GenerateVideoTool, GenerateVideoToolArgs};
     use crate::framework::tool::Tool;
     use platform_audio::{ELEVENLABS_SOUND_EFFECT_MODEL, SUNO_DEFAULT_MODEL};
-    use platform_image::{GPT_IMAGE_2_MODEL, NANOBANANA_2_MODEL};
+    use platform_image::{GPT_IMAGE_2_5_BUSINESS_NAME, NANOBANANA_2_MODEL};
     use serde_json::json;
 
     #[test]
@@ -69,11 +69,11 @@ mod tests {
         assert_eq!(image.model, NANOBANANA_2_MODEL);
         assert_eq!(image.aspect_ratio, "1:1");
         assert_eq!(image.image_size, "1K");
-        assert_eq!(edit.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(edit.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(character.model, NANOBANANA_2_MODEL);
         assert_eq!(character.aspect_ratio, "1:1");
         assert_eq!(character.image_size, "1K");
-        assert_eq!(ui_design.model, GPT_IMAGE_2_MODEL);
+        assert_eq!(ui_design.model, GPT_IMAGE_2_5_BUSINESS_NAME);
         assert_eq!(ui_design.aspect_ratio, "1:1");
         assert_eq!(ui_design.image_size, "1K");
         assert_eq!(icon.model, NANOBANANA_2_MODEL);
@@ -133,14 +133,17 @@ mod tests {
         };
 
         assert!(tool.validate_args(&args(NANOBANANA_2_MODEL)).is_ok());
-        assert!(tool.validate_args(&args(GPT_IMAGE_2_MODEL)).is_ok());
+        assert!(
+            tool.validate_args(&args(GPT_IMAGE_2_5_BUSINESS_NAME))
+                .is_ok()
+        );
         assert!(matches!(
             tool.validate_args(&args("unknown-image-model")),
             Err(GenerateImageError::InvalidModel(_))
         ));
         assert_eq!(
             tool.parameters()["properties"]["model"]["enum"],
-            json!([NANOBANANA_2_MODEL, GPT_IMAGE_2_MODEL])
+            json!([NANOBANANA_2_MODEL, GPT_IMAGE_2_5_BUSINESS_NAME])
         );
     }
 
@@ -166,7 +169,7 @@ mod tests {
         ));
         let ui_args = GenerateUiDesignToolArgs {
             prompt: "生成游戏主界面".to_string(),
-            model: GPT_IMAGE_2_MODEL.to_string(),
+            model: GPT_IMAGE_2_5_BUSINESS_NAME.to_string(),
             reference_image_ids: vec![missing_image.clone()],
             aspect_ratio: "16:9".to_string(),
             image_size: "1K".to_string(),
@@ -208,7 +211,7 @@ mod tests {
 
         assert_eq!(
             edit["properties"]["model"]["enum"],
-            json!([GPT_IMAGE_2_MODEL])
+            json!([GPT_IMAGE_2_5_BUSINESS_NAME])
         );
         assert_eq!(
             video["properties"]["duration_seconds"]["enum"],
@@ -229,7 +232,7 @@ mod tests {
         for schema in [&image, &character, &icon] {
             assert_eq!(
                 schema["allOf"][0]["if"]["properties"]["model"]["const"],
-                json!(GPT_IMAGE_2_MODEL)
+                json!(GPT_IMAGE_2_5_BUSINESS_NAME)
             );
             assert_eq!(
                 schema["allOf"][0]["then"]["properties"]["image_size"]["enum"],

server-rs/crates/platform-image/src/image_provider/constants.rs

@@ -1,8 +1,14 @@
 pub const GPT_IMAGE_2_MODEL: &str = "gpt-image-2";
 pub const GPT_IMAGE_2_C_MODEL: &str = "gpt-image-2-c";
+/// Current business model exposed to callers for new image tasks.
+pub const GPT_IMAGE_2_5_BUSINESS_NAME: &str = "gpt-image-2.5";
+/// Provider/pricing key for new generation tasks.
+pub const GPT_IMAGE_2_5_GENERATION_MODEL: &str = "gpt-image-2.5-flare-c";
+/// Provider/pricing key for explicit image-edit tasks.
+pub const GPT_IMAGE_2_5_EDIT_MODEL: &str = "gpt-image-2.5-sunburst-c";
 pub const NANOBANANA_2_MODEL: &str = "gemini-3.1-flash-image-preview";
-pub const VECTOR_ENGINE_GPT_IMAGE_2_MODEL: &str = GPT_IMAGE_2_MODEL;
 pub const VECTOR_ENGINE_PROVIDER: &str = "vector-engine";
+pub const TIANTOKEN_PROVIDER: &str = "tiantoken";
 pub const VECTOR_ENGINE_IMAGE_EDIT_MAX_REFERENCE_IMAGES: usize = 5;
 pub const VECTOR_ENGINE_NANOBANANA_MAX_REFERENCE_IMAGES: usize = 14;
 pub const GPT_IMAGE_2_MIN_PIXELS: u64 = 655_360;