691 lines
31 KiB
TypeScript
691 lines
31 KiB
TypeScript
import { scopedLocalStorage } from "@/lib/user-scope";
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import { useMemo } from "react";
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import type { ModelTag } from "@/lib/model-tags";
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import { create } from "zustand";
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import { persist, createJSONStorage } from "zustand/middleware";
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import { nanoid } from "nanoid";
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import { modelProtocolCapability, normalizeModelProtocol, type ModelProtocol } from "@/lib/model-protocols";
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import { normalizeVideoDuration, normalizeVideoResolution } from "@/lib/video-generation-options";
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import { type ModelCapabilityConfig } from "@/lib/model-capabilities";
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import { useUserStore } from "@/stores/use-user-store";
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import type { CapabilitySpec, PublicChannelModelAvailability, PublicLogicalModelPriceTier } from "@/services/api/logical-models";
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import { type WorkflowFieldMapping, normalizeRunningHubCapability, normalizeRunningHubWorkflowKind, normalizeSavedWorkflowFields, mergeWorkflowFieldMappings, normalizeWorkflowFieldMappings } from "./config-workflow-fields";
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import {
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decodeChannelModel,
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modelOptionName,
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modelOptionsFromChannels,
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normalizeModelOptionValue,
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CHANNEL_MODEL_SEPARATOR,
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uniqueModelOptions,
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encodeChannelModel,
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hasSystemModelPrice,
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isChannelModelValue,
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modelDisplayName,
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modelIcon,
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modelOptionLabel,
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} from "./config-model-options";
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import { normalizeRawModelName } from "./config-model-options";
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export { CHANNEL_MODEL_SEPARATOR, normalizeRawModelName, uniqueModelOptions } from "./config-model-options";
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export { mergeWorkflowFieldMappings, normalizeRunningHubCapability, normalizeRunningHubWorkflowKind, normalizeWorkflowFieldMappings, type WorkflowFieldMapping } from "./config-workflow-fields";
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export { decodeChannelModel, encodeChannelModel, hasSystemModelPrice, isChannelModelValue, modelDisplayName, modelIcon, modelOptionLabel, modelOptionName, modelOptionsFromChannels, normalizeModelOptionValue } from "./config-model-options";
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export type ApiCallFormat = "openai" | "gemini" | "claude";
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export type ChannelInterfaceType = ModelProtocol;
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export type ChannelHeader = { name: string; value: string };
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export type RunningHubCapability = "image" | "video" | "audio";
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export type RunningHubWorkflowKind = "workflow" | "app";
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export type RunningHubWorkflow = {
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kind?: RunningHubWorkflowKind;
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capability?: RunningHubCapability;
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workflowId: string;
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webappId?: string;
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title?: string;
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description?: string;
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fields?: WorkflowFieldMapping[];
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workflowJson?: Record<string, unknown>;
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optionalImageMode?: string;
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raw?: Record<string, unknown>;
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};
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export type RunningHubConfig = {
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enabled: boolean;
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baseUrl: string;
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apiKey: string;
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walletApiKey: string;
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/** 仅用于 RunningHub 参考素材上传，通常填写企业级 API Key。 */
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uploadApiKey?: string;
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useWallet: boolean;
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capability: RunningHubCapability;
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selectedKind: RunningHubWorkflowKind;
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workflowId: string;
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workflows: RunningHubWorkflow[];
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};
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export type WorkflowGraphPreview = {
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nodes: Array<{ id: string; title?: string; classType?: string }>;
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edges: Array<{ from: string; to: string }>;
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};
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// 兼容仍在使用旧目录标识的会话恢复和模型选择器。
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export const PUBLIC_MODEL_CATALOG_ID = "managed";
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export type ModelChannel = {
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id: string;
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name: string;
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sortOrder?: number;
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baseUrl: string;
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apiKey: string;
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secretKey?: string;
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headers?: ChannelHeader[];
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apiFormat: ApiCallFormat;
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interfaceType?: ChannelInterfaceType;
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models: string[];
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// 仅平台目录使用：将已保存的旧 SKU 选择重定向到当前模型家族。
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modelAliases?: Record<string, string>;
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scope?: "system" | "user";
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enabled?: boolean;
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hasApiKey?: boolean;
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hasSecretKey?: boolean;
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concurrencyLimit?: number;
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proxyUrl?: string;
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modelCosts?: Array<{
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model: string;
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displayName?: string;
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channelLabel?: string;
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tags?: ModelTag[];
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description?: string;
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icon?: string;
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capability: ModelCapability;
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protocol?: ModelProtocol;
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pricePolicy?: "channel" | "unified";
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billingMode: "fixed_request" | "per_second" | "token";
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unitPriceMicrocredits: number;
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inputTokenPriceMicrocredits?: number;
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outputTokenPriceMicrocredits?: number;
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cachedTokenPriceMicrocredits?: number;
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capabilityConfig?: ModelCapabilityConfig;
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logicalModelId?: string;
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logicalCapabilitySpec?: CapabilitySpec;
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logicalCapabilityProfiles?: CapabilitySpec[];
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logicalPriceTiers?: PublicLogicalModelPriceTier[];
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defaultOptions?: Record<string, unknown>;
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availability?: PublicChannelModelAvailability;
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available?: boolean;
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}>;
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};
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export type AiConfig = {
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channelMode: "remote";
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baseUrl: string;
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apiKey: string;
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apiFormat: ApiCallFormat;
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channels: ModelChannel[];
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runningHub: RunningHubConfig;
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/** 仅用于单次生成任务路由，不属于全局渠道启用状态。 */
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taskWorkflowProvider?: "model" | "runninghub";
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model: string;
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imageModel: string;
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videoModel: string;
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textModel: string;
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audioModel: string;
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audioVoice: string;
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audioFormat: string;
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audioSpeed: string;
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audioLanguage: string;
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audioDialect: string;
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audioInstructions: string;
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audioEmotionControlMethod: string;
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audioEmotionRandom: string;
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audioEmotionHappy: string;
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audioEmotionAngry: string;
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audioEmotionSad: string;
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audioEmotionAfraid: string;
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audioEmotionDisgusted: string;
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audioEmotionMelancholic: string;
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audioEmotionSurprised: string;
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audioEmotionCalm: string;
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videoSeconds: string;
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vquality: string;
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videoGenerateAudio: string;
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videoWatermark: string;
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videoArkPrivateAssetUpload: string;
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systemPrompt: string;
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models: string[];
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imageModels: string[];
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videoModels: string[];
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textModels: string[];
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audioModels: string[];
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quality: string;
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size: string;
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transparentBackground: string;
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count: string;
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canvasImageCount: string;
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};
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export const CONFIG_STORE_KEY = "open_ai_canvas:ai_config_store";
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export type ModelCapability = "image" | "video" | "text" | "audio";
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const OPENAI_BASE_URL = "https://api.openai.com";
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const GEMINI_BASE_URL = "https://generativelanguage.googleapis.com";
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const LEGACY_DEFAULT_MODEL_NAMES = new Set(["gpt-image-2", "grok-imagine-video", "gpt-5.5", "gpt-4o-mini-tts"]);
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export const defaultConfig: AiConfig = {
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channelMode: "remote",
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baseUrl: OPENAI_BASE_URL,
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apiKey: "",
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apiFormat: "openai",
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// 创作端模型目录只能来自后台公开逻辑模型和用户自定义渠道，不能内置供应商模型。
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channels: [],
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runningHub: { enabled: false, baseUrl: "https://www.runninghub.cn", apiKey: "", walletApiKey: "", uploadApiKey: "", useWallet: false, capability: "image", selectedKind: "workflow", workflowId: "", workflows: [] },
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taskWorkflowProvider: "model",
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model: "",
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imageModel: "",
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videoModel: "",
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textModel: "",
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audioModel: "",
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audioVoice: "alloy",
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audioFormat: "mp3",
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audioSpeed: "1",
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audioLanguage: "",
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audioDialect: "",
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audioInstructions: "",
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audioEmotionControlMethod: "与音色参考音频相同",
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audioEmotionRandom: "false",
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audioEmotionHappy: "0",
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audioEmotionAngry: "0",
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audioEmotionSad: "0",
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audioEmotionAfraid: "0",
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audioEmotionDisgusted: "0",
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audioEmotionMelancholic: "0",
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audioEmotionSurprised: "0",
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audioEmotionCalm: "0",
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videoSeconds: "6",
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vquality: "720",
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videoGenerateAudio: "true",
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videoWatermark: "false",
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videoArkPrivateAssetUpload: "true",
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systemPrompt: "",
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models: [],
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imageModels: [],
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videoModels: [],
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textModels: [],
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audioModels: [],
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quality: "auto",
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size: "1:1",
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transparentBackground: "false",
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count: "1",
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canvasImageCount: "1",
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};
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type ConfigStore = {
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config: AiConfig;
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updateConfig: <K extends keyof AiConfig>(key: K, value: AiConfig[K]) => void;
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replaceConfig: (config: AiConfig) => void;
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mergeSystemChannels: (channels: ModelChannel[]) => void;
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isAiConfigReady: (config: AiConfig, model: string) => boolean;
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};
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export type ConfigStoreSnapshot = {
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config?: Partial<AiConfig>;
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};
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function isVideoModelName(model: string) {
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const value = modelOptionName(model).toLowerCase();
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return (
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value.includes("seedance") ||
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value.includes("video") ||
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value.includes("sora") ||
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value.includes("veo") ||
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value.includes("kling") ||
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value.includes("wan") ||
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value.includes("hailuo") ||
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value.includes("pika") ||
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value.includes("runway") ||
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value.includes("gen-3") ||
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value.includes("gen3") ||
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value.includes("hunyuan-video") ||
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value.includes("hunyuanvideo") ||
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value.includes("cogvideo") ||
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value.includes("mochi") ||
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value.includes("latte") ||
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value.includes("stable-video") ||
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value.includes("svd") ||
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value.includes("animatediff") ||
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value.includes("ltx-video") ||
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value.includes("ltxvideo") ||
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value.includes("minimax-video") ||
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value.includes("abab-video")
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);
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}
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function isImageModelName(model: string) {
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const value = modelOptionName(model).toLowerCase();
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return (
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!isVideoModelName(model) &&
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!isAudioModelName(model) &&
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(value.includes("seedream") ||
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value.includes("gpt-image") ||
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value.includes("image") ||
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value.includes("dall-e") ||
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value.includes("dalle") ||
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value.includes("imagen") ||
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value.includes("flux") ||
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value.includes("sdxl") ||
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value.includes("stable-diffusion") ||
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value.includes("midjourney") ||
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value.includes("nano-banana") ||
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value.includes("nanobanana") ||
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value.includes("ideogram") ||
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value.includes("recraft") ||
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value.includes("playground") ||
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value.includes("leonardo"))
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);
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}
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function isAudioModelName(model: string) {
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const value = modelOptionName(model).toLowerCase();
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return value.includes("audio") || value.includes("tts") || value.includes("speech") || value.includes("voice") || value.includes("music") || value.includes("sound");
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}
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function isTextModelName(model: string) {
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return !isImageModelName(model) && !isVideoModelName(model) && !isAudioModelName(model);
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}
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export function modelMatchesCapability(model: string, capability?: ModelCapability) {
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if (!capability) return true;
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if (capability === "image") return isImageModelName(model);
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if (capability === "video") return isVideoModelName(model);
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if (capability === "audio") return isAudioModelName(model);
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return isTextModelName(model);
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}
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export function filterModelsByCapability(models: string[], capability?: ModelCapability, channels?: ModelChannel[]) {
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if (!capability) return models;
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return models.filter((model) => {
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const decoded = decodeChannelModel(model);
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const channel = decoded ? channels?.find((item) => item.id === decoded.channelId) : undefined;
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const modelName = decoded?.model || modelOptionName(model);
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const costEntry = channel?.modelCosts?.find((item) => item.model === modelName);
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// 协议层优先级最高：协议决定 API 端点，明确属于其他能力时直接排除，
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// 防止用户将 video/image/audio 协议的模型误标为 text 后混入文本下拉。
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const protocolCapability = modelProtocolCapability(costEntry?.protocol);
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if (protocolCapability) return protocolCapability === capability;
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// 渠道接口层：渠道级协议推断能力
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const channelCapability = capabilityForChannelInterface(channel?.interfaceType);
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if (channelCapability) return channelCapability === capability;
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// 配置能力层：用户显式标记的 capability
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const configuredCapability = costEntry?.capability;
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if (configuredCapability) return configuredCapability === capability;
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// 模型名启发式：最后回退
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return modelMatchesCapability(model, capability);
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});
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}
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export function selectableModelsByCapability(config: AiConfig, capability?: ModelCapability) {
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// 选项目录只从当前有效渠道重建，不能信任旧快照里残留的 config.models。
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// 这样旧版本内置模型、未绑定渠道的裸模型不会再次进入创作端。
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const models = modelOptionsFromChannels(config.channels);
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if (!capability) return models;
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return filterModelsByCapability(models, capability, config.channels);
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}
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export function configuredModelMatchesCapability(config: AiConfig, model: string, capability?: ModelCapability) {
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const normalized = normalizeModelOptionValue(model, config.channels);
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if (!normalized) return false;
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return selectableModelsByCapability(config, capability).includes(normalized);
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}
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function isAiConfigReady(config: AiConfig, model: string) {
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if (config.taskWorkflowProvider === "runninghub") {
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const key = config.runningHub.apiKey;
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return Boolean(config.runningHub.enabled && config.runningHub.baseUrl.trim() && key.trim() && config.runningHub.workflowId.trim());
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}
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const channel = resolveModelChannel(config, model);
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return Boolean(model.trim() && channel.baseUrl.trim() && channel.apiKey.trim());
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}
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export const useConfigStore = create<ConfigStore>()(
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persist(
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(set) => ({
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config: defaultConfig,
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updateConfig: (key, value) =>
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set((state) => ({
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config: {
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...state.config,
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[key]: value,
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},
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})),
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replaceConfig: (config) => set({ config }),
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mergeSystemChannels: (channels) =>
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set((state) => {
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const systemChannels = channels.map((channel, index) =>
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createModelChannel({
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...channel,
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id: channel.id || `system-${index + 1}`,
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name: "系统模型",
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scope: "system",
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apiKey: channel.apiKey || "system",
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}),
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);
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const userChannels = state.config.channels.filter((channel) => channel.scope !== "system");
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return normalizeConfigSnapshot({ config: { ...state.config, channels: [...systemChannels, ...userChannels] } });
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}),
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isAiConfigReady: (config, model) => isAiConfigReady(config, model),
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}),
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{
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name: CONFIG_STORE_KEY,
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storage: createJSONStorage(() => scopedLocalStorage),
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partialize: (state) => ({ config: state.config }),
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merge: (persisted, current) => {
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const persistedState = (persisted || {}) as Partial<ConfigStore>;
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return {
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...current,
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...normalizeConfigSnapshot({ config: persistedState.config }),
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};
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},
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},
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),
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);
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export function normalizeConfigSnapshot(snapshot: ConfigStoreSnapshot | undefined = {}) {
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// 坏存储/旧版本快照可能是 undefined 或缺 config，兜底为 defaultConfig，保证渲染不崩溃
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const persistedConfig = (snapshot?.config || {}) as Partial<AiConfig>;
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const persistedRunningHub = persistedConfig.runningHub;
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const runningHubCapability = normalizeRunningHubCapability(persistedRunningHub?.capability, defaultConfig.runningHub.capability);
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const runningHubWorkflows = Array.isArray(persistedRunningHub?.workflows)
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? persistedRunningHub.workflows
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.filter((item): item is RunningHubWorkflow => Boolean(item && typeof item === "object" && String(item.workflowId || "").trim()))
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.map((item) => {
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const capability = normalizeRunningHubCapability(item.capability, runningHubCapability);
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return {
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...item,
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kind: normalizeRunningHubWorkflowKind(item.kind),
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workflowId: String(item.workflowId || "").trim(),
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capability,
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fields: normalizeSavedWorkflowFields(item, capability),
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};
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})
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: [];
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const runningHubWorkflowID = String(persistedRunningHub?.workflowId || "").trim();
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const runningHubSelectedKind = persistedRunningHub?.selectedKind ? normalizeRunningHubWorkflowKind(persistedRunningHub.selectedKind) : normalizeRunningHubWorkflowKind(runningHubWorkflows.find((item) => item.workflowId === runningHubWorkflowID)?.kind);
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const config = {
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...defaultConfig,
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...persistedConfig,
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taskWorkflowProvider: "model" as const,
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runningHub: {
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...defaultConfig.runningHub,
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...(persistedRunningHub || {}),
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capability: runningHubCapability,
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selectedKind: runningHubSelectedKind,
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workflowId: runningHubWorkflowID,
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workflows: runningHubWorkflows,
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},
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};
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const hasPersistedChannels = Array.isArray(persistedConfig.channels);
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if (!hasPersistedChannels) config.channels = [];
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const channels = normalizeChannels(config, !hasPersistedChannels);
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const models = modelOptionsFromChannels(channels);
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const imageModels = filterModelsByCapability(models, "image", channels);
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const videoModels = filterModelsByCapability(models, "video", channels);
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const textModels = filterModelsByCapability(models, "text", channels);
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const audioModels = filterModelsByCapability(models, "audio", channels);
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const model = normalizeSelectedModel(config.model || config.imageModel || config.textModel, channels, models);
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return {
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config: {
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...config,
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channelMode: "remote" as const,
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apiFormat: normalizeApiFormat(config.apiFormat),
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channels,
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models,
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model,
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imageModel: normalizeSelectedModel(config.imageModel || model, channels, imageModels),
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videoModel: normalizeSelectedModel(config.videoModel, channels, videoModels),
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textModel: normalizeSelectedModel(config.textModel || model, channels, textModels),
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audioModel: normalizeSelectedModel(config.audioModel || defaultConfig.audioModel, channels, audioModels),
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audioVoice: config.audioVoice || defaultConfig.audioVoice,
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audioFormat: config.audioFormat || defaultConfig.audioFormat,
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audioSpeed: config.audioSpeed || defaultConfig.audioSpeed,
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audioLanguage: config.audioLanguage || "",
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audioDialect: config.audioDialect || "",
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audioInstructions: config.audioInstructions || "",
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audioEmotionControlMethod: config.audioEmotionControlMethod || defaultConfig.audioEmotionControlMethod,
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audioEmotionRandom: config.audioEmotionRandom || defaultConfig.audioEmotionRandom,
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audioEmotionHappy: config.audioEmotionHappy || defaultConfig.audioEmotionHappy,
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audioEmotionAngry: config.audioEmotionAngry || defaultConfig.audioEmotionAngry,
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audioEmotionSad: config.audioEmotionSad || defaultConfig.audioEmotionSad,
|
||
audioEmotionAfraid: config.audioEmotionAfraid || defaultConfig.audioEmotionAfraid,
|
||
audioEmotionDisgusted: config.audioEmotionDisgusted || defaultConfig.audioEmotionDisgusted,
|
||
audioEmotionMelancholic: config.audioEmotionMelancholic || defaultConfig.audioEmotionMelancholic,
|
||
audioEmotionSurprised: config.audioEmotionSurprised || defaultConfig.audioEmotionSurprised,
|
||
audioEmotionCalm: config.audioEmotionCalm || defaultConfig.audioEmotionCalm,
|
||
// 旧版全局 systemPrompt 会跨任务污染请求；提示词定制现已按 operation 由服务端编译。
|
||
systemPrompt: "",
|
||
videoSeconds: normalizeVideoDuration(config.videoSeconds),
|
||
vquality: normalizeVideoResolution(config.vquality),
|
||
videoGenerateAudio: config.videoGenerateAudio || "true",
|
||
videoWatermark: config.videoWatermark || "false",
|
||
videoArkPrivateAssetUpload: config.videoArkPrivateAssetUpload || "true",
|
||
transparentBackground: config.transparentBackground === "true" ? "true" : "false",
|
||
canvasImageCount: config.canvasImageCount || defaultConfig.canvasImageCount,
|
||
imageModels,
|
||
videoModels,
|
||
textModels,
|
||
audioModels,
|
||
},
|
||
};
|
||
}
|
||
|
||
function normalizeSelectedModel(value: string, channels: ModelChannel[], options: string[]) {
|
||
const model = normalizeModelOptionValue(value, channels);
|
||
return model && options.includes(model) ? model : options[0] || "";
|
||
}
|
||
|
||
export function useEffectiveConfig() {
|
||
const config = useConfigStore((state) => state.config);
|
||
const customChannelsEnabled = useUserStore((state) => state.features.customChannelsEnabled);
|
||
return useMemo(() => effectiveConfigForCustomChannels(config, customChannelsEnabled), [config, customChannelsEnabled]);
|
||
}
|
||
|
||
export function effectiveConfigForCustomChannels(config: AiConfig, customChannelsEnabled: boolean): AiConfig {
|
||
if (customChannelsEnabled) return config;
|
||
const channels = config.channels.filter((channel) => channel.scope === "system");
|
||
return normalizeConfigSnapshot({ config: { ...config, channels } }).config;
|
||
}
|
||
|
||
export function createModelChannel(channel?: Partial<ModelChannel>): ModelChannel {
|
||
const apiFormat = normalizeApiFormat(channel?.apiFormat);
|
||
const interfaceType = normalizeChannelInterfaceType(channel?.interfaceType);
|
||
const providedBaseUrl = channel?.baseUrl?.trim();
|
||
return {
|
||
id: channel?.id?.trim() || nanoid(),
|
||
name: channel?.name?.trim() || "新渠道",
|
||
sortOrder: channel?.sortOrder ?? 0,
|
||
baseUrl: providedBaseUrl || (interfaceType ? defaultBaseUrlForChannelInterface(interfaceType) : defaultBaseUrlForApiFormat(apiFormat)),
|
||
apiKey: channel?.apiKey || "",
|
||
secretKey: channel?.secretKey || "",
|
||
headers: Array.isArray(channel?.headers) ? channel.headers.map((header) => ({ name: String(header.name || ""), value: String(header.value || "") })) : [],
|
||
apiFormat,
|
||
interfaceType,
|
||
models: uniqueRawModels(channel?.models || []),
|
||
scope: channel?.scope === "system" ? "system" : "user",
|
||
enabled: channel?.enabled !== false,
|
||
hasApiKey: channel?.hasApiKey,
|
||
hasSecretKey: channel?.hasSecretKey,
|
||
modelCosts: channel?.modelCosts?.map((item) => ({ ...item, protocol: normalizeModelProtocol(item.protocol) })),
|
||
};
|
||
}
|
||
|
||
export function resolveModelChannel(config: AiConfig, value: string) {
|
||
const decoded = decodeChannelModel(value);
|
||
const model = decoded?.model || value;
|
||
const matched = decoded ? config.channels.find((channel) => channel.id === decoded.channelId) : config.channels.find((channel) => channel.models.includes(model));
|
||
return matched || config.channels[0] || createModelChannel({ id: "default", name: "默认渠道", baseUrl: config.baseUrl, apiKey: config.apiKey, apiFormat: config.apiFormat, models: config.models.map(modelOptionName) });
|
||
}
|
||
|
||
export function logicalModelIDForConfig(config: AiConfig) {
|
||
const channel = resolveModelChannel(config, config.model);
|
||
return channel.modelCosts?.find((item) => item.model === modelOptionName(config.model))?.logicalModelId || "";
|
||
}
|
||
|
||
export function channelConnectionSignature(channel: ModelChannel) {
|
||
return [channel.baseUrl.trim(), channel.apiKey.trim(), channel.secretKey?.trim() || "", channel.apiFormat, channel.interfaceType || "auto", JSON.stringify(channel.headers || [])].join("\n");
|
||
}
|
||
|
||
export function resolveModelRequestConfig(config: AiConfig, value: string) {
|
||
const channel = resolveModelChannel(config, value);
|
||
const model = modelOptionName(value || config.model);
|
||
const modelProtocol = channel.modelCosts?.find((item) => item.model === model)?.protocol;
|
||
const interfaceType = modelProtocol || channel.interfaceType;
|
||
return {
|
||
...config,
|
||
model,
|
||
baseUrl: channel.baseUrl,
|
||
apiKey: channel.apiKey,
|
||
secretKey: channel.secretKey,
|
||
headers: channel.headers,
|
||
apiFormat: interfaceType ? (interfaceType === "gemini-veo" || interfaceType === "gemini-image" ? ("gemini" as const) : interfaceType === "claude-api" ? ("claude" as const) : ("openai" as const)) : channel.apiFormat,
|
||
interfaceType,
|
||
channelId: channel.scope === "system" ? channel.id : "",
|
||
};
|
||
}
|
||
|
||
function normalizeChannels(config: AiConfig, ensureDefault = true) {
|
||
const persistedChannels = Array.isArray(config.channels) ? config.channels : [];
|
||
const channels = persistedChannels
|
||
.map((channel, index) =>
|
||
createModelChannel({
|
||
...channel,
|
||
id: channel.id || (index === 0 ? "default" : `channel-${index + 1}`),
|
||
name: channel.name || (index === 0 ? "默认渠道" : `渠道 ${index + 1}`),
|
||
models: uniqueRawModels(channel.models || []),
|
||
}),
|
||
)
|
||
.filter((channel) => !isEmptyDefaultChannel(channel));
|
||
if (!channels.length && ensureDefault && config.apiKey.trim()) {
|
||
channels.push(
|
||
createModelChannel({
|
||
id: "default",
|
||
name: "默认渠道",
|
||
baseUrl: config.baseUrl || defaultConfig.baseUrl,
|
||
apiKey: config.apiKey || "",
|
||
apiFormat: config.apiFormat || defaultConfig.apiFormat,
|
||
models: uniqueRawModels([...(config.models || []), config.model, config.imageModel, config.videoModel, config.textModel, config.audioModel]),
|
||
}),
|
||
);
|
||
}
|
||
return channels.map((channel) => ({ ...channel, models: uniqueRawModels(channel.models) }));
|
||
}
|
||
|
||
function isEmptyDefaultChannel(channel: ModelChannel) {
|
||
if (channel.scope === "system") return false;
|
||
if (channel.id !== "default" || channel.name.trim() !== "默认渠道" || channel.apiKey.trim()) return false;
|
||
const baseUrl = channel.baseUrl.trim().replace(/\/+$/, "");
|
||
const defaultBaseUrl = defaultConfig.baseUrl.trim().replace(/\/+$/, "");
|
||
if (baseUrl && baseUrl !== defaultBaseUrl) return false;
|
||
// 只清理旧版本写入浏览器的无密钥“默认渠道”和内置模型；没有 API Key 但已填写自定义模型时仍保留，
|
||
// 让用户可以先保存模型目录再补充密钥，而不是把真实自定义配置误判为空。
|
||
return !channel.models.length || channel.models.every((model) => LEGACY_DEFAULT_MODEL_NAMES.has(modelOptionName(model)));
|
||
}
|
||
|
||
export function defaultBaseUrlForApiFormat(apiFormat: ApiCallFormat) {
|
||
return apiFormat === "gemini" ? GEMINI_BASE_URL : OPENAI_BASE_URL;
|
||
}
|
||
|
||
export function defaultBaseUrlForChannelInterface(interfaceType?: ChannelInterfaceType) {
|
||
if (interfaceType === "gemini-veo" || interfaceType === "gemini-image") return GEMINI_BASE_URL;
|
||
if (interfaceType === "novita-video") return "https://api.novita.ai/v3";
|
||
if (interfaceType === "volcengine-ark-agent-plan-image" || interfaceType === "volcengine-ark-agent-plan-video") return "https://ark.cn-beijing.volces.com/api/plan/v3";
|
||
if (interfaceType === "volcengine-ark-image" || interfaceType === "volcengine-ark-video") return "https://ark.cn-beijing.volces.com/api/v3";
|
||
if (interfaceType === "volcengine-jimeng-image" || interfaceType === "volcengine-jimeng-video") return "https://visual.volcengineapi.com";
|
||
if (interfaceType === "minimax-video") return "https://api.minimaxi.com";
|
||
if (interfaceType === "grok-image" || interfaceType === "newapi" || interfaceType === "newapi-channel-1" || interfaceType === "newapi-channel-2" || interfaceType === "xai-video") return "";
|
||
return OPENAI_BASE_URL;
|
||
}
|
||
|
||
function capabilityForChannelInterface(interfaceType?: ChannelInterfaceType): ModelCapability | undefined {
|
||
return modelProtocolCapability(interfaceType);
|
||
}
|
||
|
||
function normalizeApiFormat(apiFormat: unknown): ApiCallFormat {
|
||
return apiFormat === "gemini" || apiFormat === "claude" ? apiFormat : "openai";
|
||
}
|
||
|
||
function normalizeChannelInterfaceType(value: unknown): ChannelInterfaceType | undefined {
|
||
return normalizeModelProtocol(value);
|
||
}
|
||
|
||
function uniqueRawModels(models: string[]) {
|
||
return Array.from(new Set((models || []).map(normalizeRawModelName).filter(Boolean)));
|
||
}
|
||
|
||
export function buildApiUrl(baseUrl: string, path: string) {
|
||
let normalizedBaseUrl = resolveBackendApiUrl(baseUrl).replace(/\/+$/, "");
|
||
normalizedBaseUrl = normalizeArkPlanBaseUrl(normalizedBaseUrl);
|
||
const requestPath = path.startsWith("/") ? path : `/${path}`;
|
||
if (isSystemProxyBaseUrl(normalizedBaseUrl)) return `${normalizedBaseUrl}${requestPath}`;
|
||
|
||
const knownPrefixes = ["/api/plan/v3", "/api/v3", "/v1beta", "/v1", "/v2", "/v3"];
|
||
const requestPrefixFor = (value: string) =>
|
||
knownPrefixes.find((prefix) => {
|
||
const lower = value.toLowerCase();
|
||
return lower === prefix || lower.startsWith(`${prefix}/`) || lower.startsWith(`${prefix}?`) || lower.startsWith(`${prefix}#`);
|
||
}) || "";
|
||
const basePrefixFor = (value: string) =>
|
||
knownPrefixes.find((prefix) => {
|
||
const lower = value.toLowerCase();
|
||
return lower.endsWith(prefix) || lower.includes(`${prefix}/`) || lower.includes(`${prefix}?`) || lower.includes(`${prefix}#`);
|
||
}) || "";
|
||
const basePrefix = basePrefixFor(normalizedBaseUrl);
|
||
const requestPrefix = requestPrefixFor(requestPath);
|
||
if (requestPrefix) {
|
||
const root = basePrefix ? normalizedBaseUrl.slice(0, -basePrefix.length) : normalizedBaseUrl;
|
||
return `${root}${requestPath}`;
|
||
}
|
||
return `${normalizedBaseUrl}${basePrefix ? "" : "/v1"}${requestPath}`;
|
||
}
|
||
|
||
export function resolveBackendApiUrl(value: string) {
|
||
const url = value.trim();
|
||
if (!url.startsWith("/api/")) return url;
|
||
const backendBaseUrl = String(import.meta.env.VITE_CANVAS_BACKEND_URL || "/api")
|
||
.trim()
|
||
.replace(/\/+$/, "");
|
||
return backendBaseUrl === "/api" ? url : `${backendBaseUrl}${url.slice("/api".length)}`;
|
||
}
|
||
|
||
export function isSystemProxyBaseUrl(baseUrl: string) {
|
||
return Boolean(systemProxyChannelId(baseUrl));
|
||
}
|
||
|
||
export function systemProxyChannelId(baseUrl: string) {
|
||
const value = baseUrl.trim();
|
||
const lowerValue = value.toLowerCase();
|
||
for (const marker of ["/api/ai/system/", "/api/"]) {
|
||
const index = lowerValue.lastIndexOf(marker);
|
||
if (index < 0) continue;
|
||
const remainder = value.slice(index + marker.length);
|
||
if (/[/?#]/.test(remainder)) continue;
|
||
const channelId = remainder.trim();
|
||
if (channelId && !channelId.includes("\\") && !["v1", "v1beta", "v2", "v3", "plan", "ai"].includes(channelId.toLowerCase())) return channelId;
|
||
}
|
||
return "";
|
||
}
|
||
|
||
function normalizeArkPlanBaseUrl(baseUrl: string) {
|
||
try {
|
||
const url = new URL(baseUrl);
|
||
const path = url.pathname.replace(/\/+$/, "");
|
||
const lowerPath = path.toLowerCase();
|
||
const arkPlanIndex = lowerPath.indexOf("/api/plan/v3");
|
||
if (arkPlanIndex < 0) return baseUrl;
|
||
const end = arkPlanIndex + "/api/plan/v3".length;
|
||
if (lowerPath.length !== end && lowerPath[end] !== "/") return baseUrl;
|
||
url.pathname = path.slice(0, end);
|
||
url.search = "";
|
||
url.hash = "";
|
||
return url.toString().replace(/\/+$/, "");
|
||
} catch {
|
||
return baseUrl;
|
||
}
|
||
}
|