@piapi/sdk
Version:
SDK for PIAPI
1 lines • 42.5 kB
Source Map (JSON)
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createTryonRequest(params: Kling.VirtualTryonParams): CreateTaskRequest {\n // 验证必需参数\n if (!params.model_input) {\n throw new Error(\"model_input is required\");\n }\n\n // 验证互斥参数\n if (params.dress_input && (params.upper_input || params.lower_input)) {\n throw new Error(\"Cannot use dress_input together with upper_input or lower_input\");\n }\n\n if (!params.dress_input && !params.upper_input && !params.lower_input) {\n throw new Error(\"Must provide either dress_input or upper_input/lower_input\");\n }\n\n const request: CreateTaskRequest = {\n model: \"kling\",\n task_type: \"ai_try_on\",\n input: {\n ...KlingTryonAPI.DEFAULT_PARAMS,\n ...params,\n },\n };\n\n if (this.config.webhookUrl && this.config.webhookSecret) {\n request.config = {\n webhook_config: {\n endpoint: this.config.webhookUrl,\n secret: this.config.webhookSecret,\n },\n };\n }\n\n return request;\n }\n\n async tryOn(params: Kling.VirtualTryonParams): Promise<TaskResponse> {\n const request = this.createTryonRequest(params);\n return this.createTask(request);\n }\n\n async tryOnAndWait(params: Kling.VirtualTryonParams, options?: {\n maxAttempts?: number;\n interval?: number;\n }): Promise<TaskResponse> {\n const request = this.createTryonRequest(params);\n return this.createTaskAndWait(request, options);\n }\n}\n","import { PIAPI } from '@core/base';\nimport { CreateTaskRequest, TaskResponse } from '@core/types';\nimport { Kling } from './types';\n\nexport class KlingEffectsAPI extends PIAPI {\n private config: Kling.Config;\n\n constructor(apiKey: string, config: Kling.Config = {}, baseUrl?: string) {\n super(apiKey, baseUrl);\n this.config = config;\n }\n\n // Effects 配置信息 - 定义每个 effect 的可用模式和是否需要 prompt\n private static EFFECTS_CONFIG: Record<Kling.EffectName, {\n stdMode: boolean;\n proMode: boolean;\n requiresPrompt: boolean;\n }> = {\n squish: { stdMode: true, proMode: false, requiresPrompt: false },\n expansion: { stdMode: true, proMode: false, requiresPrompt: false },\n jellycat_oversea: { stdMode: true, proMode: false, requiresPrompt: false },\n spinoff: { stdMode: false, proMode: true, requiresPrompt: false },\n rocket: { stdMode: true, proMode: true, requiresPrompt: true },\n hearting: { stdMode: true, proMode: true, requiresPrompt: true },\n fighting: { stdMode: true, proMode: true, requiresPrompt: true },\n kissing: { stdMode: true, proMode: true, requiresPrompt: true },\n hugging: { stdMode: true, proMode: true, requiresPrompt: true },\n figure: { stdMode: true, proMode: false, requiresPrompt: false },\n vstack: { stdMode: true, proMode: true, requiresPrompt: false },\n surfing: { stdMode: true, proMode: true, requiresPrompt: false },\n birthday: { stdMode: true, proMode: true, requiresPrompt: true },\n water: { stdMode: true, proMode: true, requiresPrompt: true },\n };\n\n private createEffectsRequest(params: Kling.EffectParams): CreateTaskRequest {\n // 验证必需参数\n if (!params.image_url) {\n throw new Error(\"image_url is required\");\n }\n\n if (!params.effect) {\n throw new Error(\"effect is required\");\n }\n\n // 验证 effect 是否有效\n const effectConfig = KlingEffectsAPI.EFFECTS_CONFIG[params.effect];\n if (!effectConfig) {\n throw new Error(`Invalid effect: ${params.effect}`);\n }\n\n const isProfessionalMode = params.professional_mode || false;\n\n // 验证模式兼容性\n if (isProfessionalMode && !effectConfig.proMode) {\n throw new Error(`Effect \"${params.effect}\" is not available in professional mode`);\n }\n\n if (!isProfessionalMode && !effectConfig.stdMode) {\n throw new Error(`Effect \"${params.effect}\" is only available in professional mode`);\n }\n\n // 验证 prompt 要求\n if (effectConfig.requiresPrompt && !params.prompt) {\n throw new Error(`Effect \"${params.effect}\" requires a prompt`);\n }\n\n const request: CreateTaskRequest = {\n model: \"kling\",\n task_type: \"effects\",\n input: {\n image_url: params.image_url,\n effect: params.effect,\n ...(params.prompt && { prompt: params.prompt }),\n ...(params.professional_mode && { professional_mode: params.professional_mode }),\n },\n };\n\n if (this.config.webhookUrl && this.config.webhookSecret) {\n request.config = {\n webhook_config: {\n endpoint: this.config.webhookUrl,\n secret: this.config.webhookSecret,\n },\n };\n }\n\n return request;\n }\n\n async applyEffect(params: Kling.EffectParams): Promise<TaskResponse<Kling.EffectOutput>> {\n const request = this.createEffectsRequest(params);\n return this.createTask<Kling.EffectOutput>(request);\n }\n\n async applyEffectAndWait(params: Kling.EffectParams, options?: {\n maxAttempts?: number;\n interval?: number;\n }): Promise<TaskResponse<Kling.EffectOutput>> {\n const request = this.createEffectsRequest(params);\n return this.createTaskAndWait<Kling.EffectOutput>(request, options);\n }\n\n // 获取特定 effect 任务状态\n async getEffectTask(taskId: string): Promise<TaskResponse<Kling.EffectOutput>> {\n return this.getTask<Kling.EffectOutput>(taskId);\n }\n\n // 静态方法：获取指定 effect 的配置信息\n static getEffectConfig(effect: Kling.EffectName) {\n return KlingEffectsAPI.EFFECTS_CONFIG[effect];\n }\n\n // 静态方法：获取所有可用的 effects\n static getAvailableEffects(): Kling.EffectName[] {\n return Object.keys(KlingEffectsAPI.EFFECTS_CONFIG) as Kling.EffectName[];\n }\n\n // 静态方法：根据模式筛选可用的 effects\n static getEffectsByMode(professionalMode: boolean = false): Kling.EffectName[] {\n return Object.entries(KlingEffectsAPI.EFFECTS_CONFIG)\n .filter(([_, config]) => professionalMode ? config.proMode : config.stdMode)\n .map(([effect]) => effect as Kling.EffectName);\n }\n} ","import { PIAPI } from '@core/base';\nimport { defu } from 'defu';\nimport { CreateTaskRequest, TaskResponse } from '@core/types';\nimport { LumaBaseParams, LumaConfig } from './types';\n\nexport class LumaAPI extends PIAPI {\n private config: LumaConfig;\n\n constructor(apiKey: string, config: LumaConfig = {}, baseUrl?: string) {\n super(apiKey, baseUrl);\n this.config = config;\n }\n\n private static DEFAULT_PARAMS = {\n expand_prompt: true,\n loop: true,\n };\n\n private createLumaRequest(params: LumaBaseParams): CreateTaskRequest {\n const finalInput = defu(params, LumaAPI.DEFAULT_PARAMS);\n\n const request: CreateTaskRequest = {\n model: \"luma\",\n task_type: \"video_generation\",\n input: finalInput,\n };\n\n if (this.config.webhookUrl && this.config.webhookSecret) {\n request.config = {\n webhook_config: {\n endpoint: this.config.webhookUrl,\n secret: this.config.webhookSecret,\n },\n };\n }\n\n return request;\n }\n\n async createVideo(params: LumaBaseParams): Promise<TaskResponse> {\n const request = this.createLumaRequest(params);\n return this.createTask(request);\n }\n} ","import { PIAPI } from '@core/base';\nimport { CreateTaskRequest, TaskResponse } from '@core/types';\nimport { FaceSwapConfig, FaceSwapParams, FaceSwapOutput } from './types';\n\nexport class FaceSwapAPI extends PIAPI {\n private config: FaceSwapConfig;\n\n constructor(apiKey: string, config: FaceSwapConfig = {}, baseUrl?: string) {\n super(apiKey, baseUrl);\n this.config = config;\n }\n\n private createFaceSwapRequest(params: FaceSwapParams): CreateTaskRequest {\n if (!params.target_image) {\n throw new Error(\"target_image is required\");\n }\n if (!params.swap_image) {\n throw new Error(\"swap_image is required\");\n }\n\n const request: CreateTaskRequest = {\n model: \"Qubico/image-toolkit\",\n task_type: \"face-swap\",\n input: params,\n };\n\n return request;\n }\n\n async faceSwap(params: FaceSwapParams): Promise<TaskResponse<FaceSwapOutput>> {\n const request = this.createFaceSwapRequest(params);\n return this.createTask<FaceSwapOutput>(request);\n }\n\n async faceSwapAndWait(params: FaceSwapParams, options?: {\n maxAttempts?: number;\n interval?: number;\n }): Promise<TaskResponse<FaceSwapOutput>> {\n const request = this.createFaceSwapRequest(params);\n return this.createTaskAndWait<FaceSwapOutput>(request, options);\n }\n\n async getFaceSwapTask(taskId: string): Promise<TaskResponse<FaceSwapOutput>> {\n return this.getTask<FaceSwapOutput>(taskId);\n }\n}\n","import { PIAPI } from '@core/base';\nimport { CreateTaskRequest, TaskResponse, HailuoTaskOutput } from '@core/types';\nimport { HailuoConfig, HailuoVideoParams } from './types';\n\nexport class HailuoAPI extends PIAPI {\n private config: HailuoConfig;\n\n constructor(apiKey: string, config: HailuoConfig = {}, baseUrl?: string) {\n super(apiKey, baseUrl);\n this.config = config;\n }\n\n private validateImageUrl(imageUrl?: string) {\n if (!imageUrl) return;\n\n // Add URL format validation if needed\n const url = new URL(imageUrl);\n const extension = url.pathname.split('.').pop()?.toLowerCase();\n\n if (!extension || !['jpg', 'jpeg', 'png'].includes(extension)) {\n throw new Error('Image URL must point to a JPG or PNG file');\n }\n }\n\n private createHailuoRequest(params: HailuoVideoParams): CreateTaskRequest {\n // Validate prompt length\n if (params.prompt && params.prompt.length > 2000) {\n throw new Error('Prompt must not exceed 2000 characters');\n }\n\n // Validate image URL if present\n this.validateImageUrl(params.image_url);\n\n const request: CreateTaskRequest = {\n model: 'hailuo',\n task_type: 'video_generation',\n input: {\n ...params,\n },\n config: {\n service_mode: 'public',\n },\n };\n\n if (this.config.webhookUrl && this.config.webhookSecret) {\n request.config = {\n ...request.config,\n webhook_config: {\n endpoint: this.config.webhookUrl,\n secret: this.config.webhookSecret,\n },\n };\n }\n\n return request;\n }\n\n async generateVideo(\n params: HailuoVideoParams\n ): Promise<TaskResponse<HailuoTaskOutput>> {\n const request = this.createHailuoRequest(params);\n return this.createTask<HailuoTaskOutput>(request);\n }\n\n async getVideoTask(taskId: string): Promise<TaskResponse<HailuoTaskOutput>> {\n return this.getTask<HailuoTaskOutput>(taskId);\n }\n}\n","import { PIAPI } from '@core/base';\nimport { CreateTaskRequest, TaskResponse } from '@core/types';\nimport { AIHugConfig, AIHugVideoParams, AIHugTaskOutput } from './types';\n\nexport class AIHugAPI extends PIAPI {\n private config: AIHugConfig;\n\n constructor(apiKey: string, config: AIHugConfig = {}, baseUrl?: string) {\n super(apiKey, baseUrl);\n this.config = config;\n }\n\n private validateImageUrl(imageUrl: string) {\n try {\n new URL(imageUrl);\n } catch (error) {\n throw new Error('Invalid image URL format');\n }\n }\n\n private createAIHugRequest(params: AIHugVideoParams): CreateTaskRequest {\n // Validate image URL\n this.validateImageUrl(params.image_url);\n\n const request: CreateTaskRequest = {\n model: 'Qubico/hug-video',\n task_type: 'image_to_video',\n input: {\n image_url: params.image_url,\n duration: params.duration?.toString() ?? '5',\n },\n config: {\n service_mode: 'public',\n },\n };\n\n if (this.config.webhookUrl && this.config.webhookSecret) {\n request.config = {\n ...request.config,\n webhook_config: {\n endpoint: this.config.webhookUrl,\n secret: this.config.webhookSecret,\n },\n };\n }\n\n return request;\n }\n\n async generateVideo(\n params: AIHugVideoParams\n ): Promise<TaskResponse<AIHugTaskOutput>> {\n const request = this.createAIHugRequest(params);\n return this.createTask<AIHugTaskOutput>(request);\n }\n\n async getVideoTask(taskId: string): Promise<TaskResponse<AIHugTaskOutput>> {\n return this.getTask<AIHugTaskOutput>(taskId);\n }\n} ","import { PIAPI } from '@core/base';\nimport { CreateTaskRequest, TaskResponse } from '@core/types';\nimport { Wanx } from './types';\n\nexport class WanxAPI extends PIAPI {\n private config: Wanx.Config;\n private static readonly MODEL_NAME = 'Qubico/wanx';\n\n constructor(apiKey: string, config: Wanx.Config = {}, baseUrl?: string) {\n super(apiKey, baseUrl);\n this.config = config;\n }\n\n private createWanxRequest(\n taskType: Wanx.TaskType,\n params: Wanx.TextToVideoParams | Wanx.ImageToVideoParams\n ): CreateTaskRequest {\n this.logger.debug('Creating Wanx request with params:', params);\n\n const request: CreateTaskRequest = {\n model: WanxAPI.MODEL_NAME,\n task_type: taskType,\n input: {\n ...params,\n },\n };\n\n // Add webhook configuration if provided\n if (this.config.webhookUrl && this.config.webhookSecret) {\n request.config = {\n webhook_config: {\n endpoint: this.config.webhookUrl,\n secret: this.config.webhookSecret,\n },\n };\n }\n\n return request;\n }\n\n async textToVideo(\n params: Wanx.TextToVideoParams,\n modelSize: '1.3b' | '14b' = '14b'\n ): Promise<TaskResponse<Wanx.VideoTaskOutput>> {\n this.logger.info('Starting Wanx text-to-video generation', { prompt: params.prompt });\n \n const taskType: Wanx.TaskType = modelSize === '1.3b' ? 'txt2video-1.3b' : 'txt2video-14b';\n const request = this.createWanxRequest(taskType, params);\n \n return this.createTask<Wanx.VideoTaskOutput>(request);\n }\n\n async imageToVideo(\n params: Wanx.ImageToVideoParams\n ): Promise<TaskResponse<Wanx.VideoTaskOutput>> {\n this.logger.info('Starting Wanx image-to-video generation', { prompt: params.prompt, image: params.image });\n \n if (!params.image) {\n throw new Error('Image URL is required for image-to-video generation');\n }\n \n const request = this.createWanxRequest('img2video-14b', params);\n \n return this.createTask<Wanx.VideoTaskOutput>(request);\n }\n\n async getVideoTask(taskId: string): Promise<TaskResponse<Wanx.VideoTaskOutput>> {\n return this.getTask<Wanx.VideoTaskOutput>(taskId);\n }\n} "]}