refactor(*): 平台架构 - 拆分后端领域模块与画布前端组件并补充测试
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@@ -4,10 +4,7 @@ import (
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"encoding/json"
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"errors"
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"fmt"
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"sort"
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"strconv"
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"strings"
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"unicode/utf8"
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"infinite-canvas/backend/internal/model"
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)
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@@ -129,157 +126,6 @@ type VideoBooleanConfig struct {
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Default bool `json:"default"`
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}
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func DefaultModelCapabilityConfig(protocol string) *ModelCapabilityConfig {
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return DefaultModelCapabilityConfigForModel(protocol, "")
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}
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func videoDurationSupported(value *VideoCapabilityConfig) bool {
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return value == nil || value.DurationSupported == nil || *value.DurationSupported
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}
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func DefaultImageCapabilityConfig(protocol string, modelName string) *ImageCapabilityConfig {
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image := &ImageCapabilityConfig{
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References: ImageReferenceConfig{PromptMaxChars: 32000, MaxImages: 16, MaxImageBytes: 30 * 1024 * 1024, MaskSupported: true},
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Size: ImageSizeConfig{Parameter: "size", Values: defaultImageSizeValues(), Default: "1:1", AllowCustom: true},
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Quality: ImageQualityConfig{Supported: true, Values: []string{"auto", "low", "medium", "high"}, Default: "auto"},
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TransparentBackground: VideoBooleanConfig{Supported: true, Default: false},
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ResponseFormat: ParameterSupport{Supported: true},
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OutputFormat: ParameterSupport{Supported: true},
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MaxOutputs: 15,
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}
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switch model.ChannelInterfaceType(protocol) {
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case model.ChannelInterfaceGrokImage:
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image.References.MaxImages = 1
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image.References.MaskSupported = false
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// grok2api / xAI Imagine：size→aspect_ratio，quality→resolution(1k/2k)。
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image.Size = ImageSizeConfig{Parameter: "aspect_ratio", Values: []string{"1:1", "3:4", "4:3", "9:16", "16:9", "2:3", "3:2"}, Default: "1:1", AllowCustom: false}
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image.Quality = ImageQualityConfig{Supported: true, Values: []string{"1k", "2k"}, Default: "2k"}
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image.TransparentBackground = VideoBooleanConfig{Supported: false, Default: false}
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image.ResponseFormat = ParameterSupport{Supported: true}
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image.OutputFormat = ParameterSupport{Supported: false}
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image.MaxOutputs = 1
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case model.ChannelInterfaceVolcengineArkImage, model.ChannelInterfaceVolcengineArkAgentPlanImage:
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image.References.MaskSupported = false
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image.Quality.Supported = false
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image.TransparentBackground.Supported = false
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image.ResponseFormat.Supported = false
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image.OutputFormat.Supported = false
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case model.ChannelInterfaceVolcengineJiMengImage:
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image.References.MaxImages = 14
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image.References.MaskSupported = false
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image.Quality.Supported = false
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image.TransparentBackground.Supported = false
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image.ResponseFormat.Supported = false
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image.OutputFormat.Supported = false
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case model.ChannelInterfaceGeminiImage:
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image.References.MaskSupported = false
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// Gemini Images uses imageConfig.aspectRatio, not the OpenAI-style pixel size field.
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image.Size = ImageSizeConfig{Parameter: "aspect_ratio", Values: []string{"auto", "1:1", "2:3", "3:2", "3:4", "4:3", "9:16", "16:9", "21:9"}, Default: "1:1", AllowCustom: false}
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image.TransparentBackground.Supported = false
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image.ResponseFormat.Supported = false
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image.OutputFormat.Supported = false
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image.MaxOutputs = 4
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}
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if model.ChannelInterfaceType(protocol) != model.ChannelInterfaceGrokImage && strings.HasPrefix(strings.ToLower(strings.TrimSpace(modelName)), "grok-imagine-image") {
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image.References.MaxImages = 0
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image.References.MaskSupported = false
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image.Size = ImageSizeConfig{Parameter: "aspect_ratio", Values: []string{"1:1", "3:4", "4:3", "9:16", "16:9", "2:3", "3:2"}, Default: "1:1", AllowCustom: false}
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image.Quality = ImageQualityConfig{Supported: true, Values: []string{"1k", "2k"}, Default: "2k"}
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image.TransparentBackground = VideoBooleanConfig{Supported: false, Default: false}
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image.ResponseFormat = ParameterSupport{Supported: true}
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image.OutputFormat = ParameterSupport{Supported: false}
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image.MaxOutputs = 1
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}
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return image
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}
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func defaultImageSizeValues() []string {
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return []string{
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"auto", "1:1", "3:2", "2:3", "4:3", "3:4", "16:9", "21:9", "9:16",
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"1024x1024", "1360x1024", "1024x1360", "1536x1024", "1024x1536", "1024x1280", "1280x1024", "2048x878", "1824x1024", "1024x1824",
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"2048x2048", "2304x1728", "1728x2304", "2496x1664", "1664x2496", "1792x2240", "2240x1792", "3136x1344", "2752x1536", "1536x2752",
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"2880x2880", "3264x2448", "2448x3264", "3504x2336", "2336x3504", "2560x3200", "3200x2560", "3808x1632", "3840x2160", "2160x3840",
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}
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}
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// legacyImageSizeValues 用于修复旧数据中仅保存了 "*" 的图片尺寸能力。
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// 这组值是前后台共同展示的基础预设，不能让历史通配符配置继续污染用户生成参数。
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func legacyImageSizeValues() []string {
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return []string{
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"1:1", "3:2", "2:3", "4:3", "3:4", "16:9", "21:9", "9:16",
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"1024x1024", "1536x1024", "1024x1536",
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}
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}
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func DefaultModelCapabilityConfigForModel(protocol string, modelName string) *ModelCapabilityConfig {
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// 文本模型是否支持视觉输入不能从协议或模型名可靠推断，默认关闭，由管理员按真实上游能力开启。
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streaming := true
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text := &TextCapabilityConfig{Streaming: &streaming, ContextWindowTokens: 128000, MaxOutputTokens: 16384, References: TextReferenceConfig{PromptMaxChars: 32000}}
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video := &VideoCapabilityConfig{
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References: VideoReferenceConfig{PromptMaxChars: DefaultVideoPromptMaxChars, MinImages: 0, MaxImages: 9, MaxImageBytes: 30 * 1024 * 1024, MaxVideos: 0, MaxVideoBytes: 0, MaxVideoDuration: 0, MaxAudios: 0, MaxAudioBytes: 0, MaxAudioDuration: 0},
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Duration: VideoDurationConfig{Selection: "range", Min: 1, Max: 15, Step: 1, Default: 6},
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Ratios: []string{"16:9", "9:16", "1:1", "4:3", "3:4", "21:9"},
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DefaultRatio: "16:9",
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Resolutions: []string{"480p", "720p", "1080p", "1440p", "2160p"},
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DefaultResolution: "720p",
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GenerateAudio: VideoBooleanConfig{Supported: false, Default: false},
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Watermark: VideoBooleanConfig{Supported: false, Default: false},
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Operations: []string{"text_to_video", "image_to_video"},
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DefaultOperation: "text_to_video",
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}
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switch model.ChannelInterfaceType(protocol) {
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case model.ChannelInterfaceVolcengineJiMengVideo:
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video.Duration = VideoDurationConfig{Selection: "enum", Values: []int{5, 10}, Default: 5}
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video.Resolutions = []string{"720p"}
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case model.ChannelInterfaceGeminiVeo:
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video.Duration = VideoDurationConfig{Selection: "enum", Values: []int{4, 6, 8}, Default: 6}
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video.Resolutions = []string{"720p", "1080p"}
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case model.ChannelInterfaceVolcengineArkVideo, model.ChannelInterfaceVolcengineArkAgentPlanVideo:
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video.Operations = append(video.Operations, "reference_to_video", "audio_to_video")
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video.References.MaxVideos, video.References.MaxAudios = 3, 3
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video.References.MaxVideoBytes, video.References.MaxAudioBytes = 200*1024*1024, 15*1024*1024
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video.References.MaxVideoDuration, video.References.MaxAudioDuration = 15, 15
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video.GenerateAudio = VideoBooleanConfig{Supported: true, Default: true}
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video.Watermark = VideoBooleanConfig{Supported: true, Default: false}
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video.Resolutions = []string{"480p", "720p", "1080p"}
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case model.ChannelInterfaceNewAPIChannel1, model.ChannelInterfaceNewAPIChannel2:
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video.References.MaxVideos, video.References.MaxAudios = 3, 3
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video.References.MaxVideoBytes, video.References.MaxAudioBytes = 200*1024*1024, 15*1024*1024
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video.References.MaxVideoDuration, video.References.MaxAudioDuration = 15, 15
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video.GenerateAudio = VideoBooleanConfig{Supported: true, Default: true}
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if model.ChannelInterfaceType(protocol) == model.ChannelInterfaceNewAPIChannel1 {
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video.Resolutions = []string{"480p", "720p", "1080p"}
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}
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case model.ChannelInterfaceNewAPIVideo, model.ChannelInterfaceXAIVideo:
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video.GenerateAudio = VideoBooleanConfig{Supported: false, Default: false}
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case model.ChannelInterfaceNovitaVideo:
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video.References.MaxImages, video.References.MaxImageBytes = 1, 10*1024*1024
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video.Duration = VideoDurationConfig{Selection: "enum", Values: []int{5, 10}, Default: 5}
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video.Ratios = []string{"16:9", "9:16", "1:1"}
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video.Resolutions = []string{"1080p"}
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video.DefaultResolution = "1080p"
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case model.ChannelInterfaceMiniMaxVideo:
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video.Operations = append(video.Operations, "reference_to_video")
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video.References.MaxImages = 9
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video.References.MaxImageBytes = 30 * 1024 * 1024
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video.References.MaxVideos = 3
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video.References.MaxVideoBytes = 50 * 1024 * 1024
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video.References.MaxVideoDuration = 15
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video.References.MaxAudios = 3
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video.References.MaxAudioBytes = 15 * 1024 * 1024
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video.References.MaxAudioDuration = 15
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video.Duration = VideoDurationConfig{Selection: "enum", Values: []int{4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}, Default: 5}
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video.Ratios = []string{"adaptive", "21:9", "16:9", "4:3", "1:1", "3:4", "9:16"}
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video.DefaultRatio = "16:9"
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video.Resolutions = []string{"768P", "2K"}
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video.DefaultResolution = "768P"
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video.Watermark = VideoBooleanConfig{Supported: true, Default: false}
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case model.ChannelInterfaceAgnesVideo:
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video = applyModelSpecificVideoCapability(video, protocol, modelName)
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}
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return &ModelCapabilityConfig{Version: 1, Text: text, Image: DefaultImageCapabilityConfig(protocol, modelName), Video: video}
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}
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func DecodeModelCapabilityConfig(raw string) (*ModelCapabilityConfig, error) {
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if strings.TrimSpace(raw) == "" {
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return nil, nil
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@@ -543,536 +389,3 @@ func addInputConstraint(inputs map[string]InputConstraint, name string, min int,
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}
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inputs[name] = InputConstraint{Min: min, Max: max}
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}
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func validateTextCapabilityConfig(value *TextCapabilityConfig) error {
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if value.ContextWindowTokens < 4096 || value.ContextWindowTokens > 10000000 {
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return BadAuthRequest("文本模型上下文窗口必须在 4096-10000000 Token 之间")
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}
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if value.MaxOutputTokens < 256 || value.MaxOutputTokens > 1000000 || value.MaxOutputTokens >= value.ContextWindowTokens {
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return BadAuthRequest("文本模型最大输出 Token 必须小于上下文窗口且在 256-1000000 之间")
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}
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if value.References.PromptMaxChars < 1 || value.References.PromptMaxChars > 1000000 {
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return BadAuthRequest("提示词最大字符数必须在 1-1000000 之间")
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}
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for name, number := range map[string]int{"最大图片引用数": value.References.MaxImages, "最大视频引用数": value.References.MaxVideos} {
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if number < 0 || number > 100 {
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return BadAuthRequest(name + "必须在 0-100 之间")
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}
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}
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if value.References.MaxImageBytes < 0 || value.References.MaxVideoBytes < 0 {
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return BadAuthRequest("引用素材大小限制不能小于 0")
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}
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return nil
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}
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func validateImageCapabilityConfig(value *ImageCapabilityConfig) error {
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if value.References.PromptMaxChars < 1 || value.References.PromptMaxChars > 1000000 {
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return BadAuthRequest("提示词最大字符数必须在 1-1000000 之间")
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}
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if value.References.MaxImages < 0 || value.References.MaxImages > 100 || value.References.MaxImageBytes < 0 {
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return BadAuthRequest("图片引用限制无效")
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}
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if value.MaxOutputs < 1 || value.MaxOutputs > 100 {
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return BadAuthRequest("单次图片数量必须在 1-100 之间")
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}
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switch value.Size.Parameter {
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case "none":
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value.Size.Values = []string{}
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value.Size.Presets = nil
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value.Size.Default = "auto"
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value.Size.AllowCustom = false
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case "size", "aspect_ratio":
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if strings.TrimSpace(value.Size.Default) == "" {
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return BadAuthRequest("请配置默认图片尺寸或比例")
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}
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if !value.Size.AllowCustom && !containsCapabilityString(value.Size.Values, value.Size.Default) {
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return BadAuthRequest("默认图片尺寸必须属于支持值")
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}
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default:
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return BadAuthRequest("尺寸参数仅支持不发送、size 或 aspect_ratio")
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}
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seenPresets := make(map[string]bool)
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for _, preset := range value.Size.Presets {
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if preset.Tier != "1k" && preset.Tier != "2k" && preset.Tier != "4k" {
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return BadAuthRequest("图片分辨率档位仅支持 1K、2K、4K")
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}
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parts := strings.Split(preset.Ratio, ":")
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if len(parts) != 2 {
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return BadAuthRequest("图片预设比例格式无效")
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}
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w, ew := strconv.Atoi(parts[0])
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h, eh := strconv.Atoi(parts[1])
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if ew != nil || eh != nil || w <= 0 || h <= 0 || w > 100000 || h > 100000 || max(w, h) > min(w, h)*3 {
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return BadAuthRequest("图片预设比例无效")
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}
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if preset.Width <= 0 || preset.Height <= 0 || max(preset.Width, preset.Height) > 3840 || max(preset.Width, preset.Height) > min(preset.Width, preset.Height)*3 || preset.Width*preset.Height < 655360 || preset.Width*preset.Height > 8294400 || preset.Size != fmt.Sprintf("%dx%d", preset.Width, preset.Height) {
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return BadAuthRequest("图片预设像素尺寸无效")
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}
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// 容许像素取整误差，但不能将横屏尺寸标记成竖屏或其他比例。
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difference := preset.Width*h - preset.Height*w
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if difference < 0 {
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difference = -difference
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}
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if difference*1000 > preset.Height*w*25 {
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return BadAuthRequest("图片预设像素尺寸与宽高比不一致")
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}
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a, b := w, h
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for b != 0 {
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a, b = b, a%b
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}
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key := fmt.Sprintf("%s:%d:%d", preset.Tier, w/a, h/a)
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if seenPresets[key] {
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return BadAuthRequest("图片尺寸预设重复")
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}
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seenPresets[key] = true
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requestValue := preset.Size
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if value.Size.Parameter == "aspect_ratio" {
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requestValue = preset.Ratio
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}
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if !containsCapabilityString(value.Size.Values, requestValue) {
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return BadAuthRequest("图片预设必须包含在尺寸支持值中")
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}
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}
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if value.Quality.Supported {
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if len(value.Quality.Values) == 0 || strings.TrimSpace(value.Quality.Default) == "" || !containsCapabilityString(value.Quality.Values, value.Quality.Default) {
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return BadAuthRequest("请配置图片质量支持值和默认值")
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}
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} else {
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value.Quality.Values = []string{}
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value.Quality.Default = "auto"
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}
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if err := validateImagePresetSelection(value, value.Quality.Default, value.Size.Default); err != nil {
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return BadAuthRequest("默认图片分辨率与宽高比不在已配置的组合中")
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}
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if !value.TransparentBackground.Supported {
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value.TransparentBackground.Default = false
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}
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return nil
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}
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func validateVideoCapabilityConfig(value *VideoCapabilityConfig) error {
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if value.References.PromptMaxChars < 1 || value.References.PromptMaxChars > 1000000 {
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return BadAuthRequest("提示词最大字符数必须在 1-1000000 之间")
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}
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for name, number := range map[string]int{"最少图片引用数": value.References.MinImages, "最大图片引用数": value.References.MaxImages, "最大视频引用数": value.References.MaxVideos, "最大音频引用数": value.References.MaxAudios} {
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if number < 0 || number > 100 {
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return BadAuthRequest(name + "必须在 0-100 之间")
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}
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}
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if value.References.MinImages > value.References.MaxImages {
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return BadAuthRequest("最少图片引用数不能超过最大图片引用数")
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}
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if value.References.MaxImageBytes < 0 || value.References.MaxVideoBytes < 0 || value.References.MaxAudioBytes < 0 || value.References.MaxVideoDuration < 0 || value.References.MaxAudioDuration < 0 {
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return BadAuthRequest("引用素材限制不能小于 0")
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}
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if err := validateVideoDuration(value.Duration); err != nil {
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return err
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}
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if len(value.Ratios) == 0 {
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if strings.TrimSpace(value.DefaultRatio) != "" {
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return BadAuthRequest("未配置画面比例时不能设置默认比例")
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}
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} else if strings.TrimSpace(value.DefaultRatio) == "" || !containsCapabilityString(value.Ratios, value.DefaultRatio) {
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return BadAuthRequest("默认画面比例必须属于支持值")
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}
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if len(value.Resolutions) == 0 {
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if strings.TrimSpace(value.DefaultResolution) != "" {
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return BadAuthRequest("未配置输出分辨率时不能设置默认分辨率")
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}
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} else if strings.TrimSpace(value.DefaultResolution) == "" || !containsCapabilityString(value.Resolutions, value.DefaultResolution) {
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return BadAuthRequest("默认输出分辨率必须属于支持值")
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}
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if len(value.Operations) == 0 || strings.TrimSpace(value.DefaultOperation) == "" || !containsCapabilityString(value.Operations, value.DefaultOperation) {
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return BadAuthRequest("请至少配置一个生成模式，并选择默认模式")
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}
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return nil
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}
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func validateVideoDuration(value VideoDurationConfig) error {
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switch value.Selection {
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case "range":
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if value.Min < 1 || value.Max < value.Min || value.Max > 3600 || value.Step < 1 || value.Default < value.Min || value.Default > value.Max || (value.Default-value.Min)%value.Step != 0 {
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return BadAuthRequest("视频时长范围或默认值无效")
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}
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case "enum":
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if len(value.Values) == 0 || len(value.Values) > 100 {
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return BadAuthRequest("视频固定时长至少需要一个选项")
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}
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values := append([]int(nil), value.Values...)
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sort.Ints(values)
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for index, item := range values {
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if item < 1 || item > 3600 || (index > 0 && values[index-1] == item) {
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return BadAuthRequest("视频固定时长选项无效或重复")
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}
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}
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if !containsInt(values, value.Default) {
|
||||
return BadAuthRequest("视频默认时长必须属于固定时长选项")
|
||||
}
|
||||
default:
|
||||
return BadAuthRequest("视频时长选择方式仅支持范围或固定值")
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (s *Service) ValidateTaskCapability(input map[string]any) error {
|
||||
encoded, err := json.Marshal(input)
|
||||
if err != nil {
|
||||
return BadAuthRequest("任务输入格式无效")
|
||||
}
|
||||
var taskInput canvasGenerationInput
|
||||
if err := json.Unmarshal(encoded, &taskInput); err != nil || (taskInput.Mode != "image" && taskInput.Mode != "video" && taskInput.Mode != "audio") {
|
||||
return nil
|
||||
}
|
||||
if isWorkflowProviderInterface(taskInput.Config.InterfaceType) {
|
||||
if err := validateWorkflowProviderPromptLength(taskInput); err != nil {
|
||||
return err
|
||||
}
|
||||
return validateWorkflowProviderConfig(taskInput.Mode, taskInput.Config)
|
||||
}
|
||||
// 普通音频模型沿用主线的能力校验路径；当前专用能力表只覆盖图片和视频。
|
||||
if taskInput.Mode == "audio" {
|
||||
return nil
|
||||
}
|
||||
channelID := strings.TrimSpace(taskInput.Config.ChannelID)
|
||||
if channelID == "" {
|
||||
channelID = systemChannelIDFromBaseURL(taskInput.Config.BaseURL)
|
||||
}
|
||||
if channelID == "" {
|
||||
if taskInput.Mode == "image" {
|
||||
profile := DefaultImageCapabilityConfig(taskInput.Config.InterfaceType, taskInput.Config.Model)
|
||||
if taskInput.Config.CapabilityConfig != nil && taskInput.Config.CapabilityConfig.Image != nil {
|
||||
profile = taskInput.Config.CapabilityConfig.Image
|
||||
}
|
||||
return validateImageTask(profile, taskInput)
|
||||
}
|
||||
profile := taskInput.Config.CapabilityConfig
|
||||
if profile == nil || profile.Video == nil {
|
||||
if taskInput.Config.InterfaceType != string(model.ChannelInterfaceAgnesVideo) {
|
||||
return nil
|
||||
}
|
||||
profile = DefaultModelCapabilityConfigForModel(taskInput.Config.InterfaceType, taskInput.Config.Model)
|
||||
}
|
||||
normalized, normalizeErr := NormalizeModelCapabilityConfigForModel("video", taskInput.Config.InterfaceType, taskInput.Config.Model, profile)
|
||||
if normalizeErr != nil || normalized == nil || normalized.Video == nil {
|
||||
return BadAuthRequest("当前视频模型能力参数无效")
|
||||
}
|
||||
return validateVideoTask(normalized.Video, taskInput)
|
||||
}
|
||||
item, err := s.repo.ChannelModelByKey(channelID, providerChannelModelKey(taskInput.Config))
|
||||
if err != nil {
|
||||
return BadAuthRequest("当前系统渠道模型未配置或已停用")
|
||||
}
|
||||
profile, err := DecodeModelCapabilityConfig(item.CapabilityConfigJSON)
|
||||
if taskInput.Mode == "image" {
|
||||
if err != nil {
|
||||
return BadAuthRequest("当前图片模型能力参数无效")
|
||||
}
|
||||
imageProfile := DefaultImageCapabilityConfig(string(item.Protocol), firstNonEmpty(item.ProviderModelKey, item.ModelKey))
|
||||
if profile != nil && profile.Image != nil {
|
||||
imageProfile = profile.Image
|
||||
}
|
||||
return validateImageTask(applyModelSpecificImageCapability(imageProfile, string(item.Protocol), firstNonEmpty(item.ProviderModelKey, item.ModelKey), taskInput.Config.APIFormat), taskInput)
|
||||
}
|
||||
if err != nil || profile == nil || profile.Video == nil {
|
||||
return BadAuthRequest("当前视频模型尚未配置能力参数")
|
||||
}
|
||||
normalized, normalizeErr := NormalizeModelCapabilityConfigForModel("video", string(item.Protocol), firstNonEmpty(item.ProviderModelKey, item.ModelKey), profile)
|
||||
if normalizeErr != nil || normalized == nil || normalized.Video == nil {
|
||||
return BadAuthRequest("当前视频模型能力参数无效")
|
||||
}
|
||||
applyFixedVideoResolution(&taskInput, normalized.Video)
|
||||
if config, ok := input["config"].(map[string]any); ok {
|
||||
config["vquality"] = taskInput.Config.VQuality
|
||||
}
|
||||
return validateVideoTask(normalized.Video, taskInput)
|
||||
}
|
||||
|
||||
// applyModelSpecificImageCapability is retained as a narrow normalization hook
|
||||
// for provider-specific image validation. The stored capability profile is
|
||||
// already normalized when the channel model is saved, so no second override is
|
||||
// needed here.
|
||||
func applyModelSpecificImageCapability(profile *ImageCapabilityConfig, _ string, _ string, _ string) *ImageCapabilityConfig {
|
||||
return profile
|
||||
}
|
||||
|
||||
// applyFixedVideoResolution 让单档位 SKU 的预扣、恢复和上游请求保持同一分辨率。
|
||||
func applyFixedVideoResolution(input *canvasGenerationInput, profile *VideoCapabilityConfig) {
|
||||
if input == nil || profile == nil || len(profile.Resolutions) != 1 {
|
||||
return
|
||||
}
|
||||
if resolution := videoResolutionNameRequest(profile, profile.Resolutions[0]); resolution != "" {
|
||||
input.Config.VQuality = resolution
|
||||
}
|
||||
}
|
||||
|
||||
func validateVideoTask(profile *VideoCapabilityConfig, input canvasGenerationInput) error {
|
||||
if profile == nil {
|
||||
return BadAuthRequest("当前视频模型能力参数无效")
|
||||
}
|
||||
if err := validateModelPromptLength("视频", input.Prompt, profile.References.PromptMaxChars); err != nil {
|
||||
return err
|
||||
}
|
||||
if len(input.ReferenceImages) > profile.References.MaxImages || len(input.ReferenceVideos) > profile.References.MaxVideos || len(input.ReferenceAudios) > profile.References.MaxAudios {
|
||||
return BadAuthRequest("参考素材数量超过当前模型限制")
|
||||
}
|
||||
if model.IsVolcengineArkVideoProtocol(model.ChannelInterfaceType(input.Config.InterfaceType)) && len(input.ReferenceAudios) > 0 && len(input.ReferenceImages) == 0 && len(input.ReferenceVideos) == 0 {
|
||||
return BadAuthRequest("火山方舟全模态参考不支持纯音频或文本+音频，请同时添加参考图片或参考视频")
|
||||
}
|
||||
if len(input.ReferenceImages) < profile.References.MinImages {
|
||||
return BadAuthRequest(fmt.Sprintf("当前视频模型至少需要 %d 张参考图", profile.References.MinImages))
|
||||
}
|
||||
for _, media := range input.ReferenceImages {
|
||||
if profile.References.MaxImageBytes > 0 && media.Bytes > profile.References.MaxImageBytes {
|
||||
return BadAuthRequest("参考图片文件超过当前模型大小限制")
|
||||
}
|
||||
}
|
||||
for _, media := range input.ReferenceVideos {
|
||||
if profile.References.MaxVideoBytes > 0 && media.Bytes > profile.References.MaxVideoBytes {
|
||||
return BadAuthRequest("参考视频文件超过当前模型大小限制")
|
||||
}
|
||||
if profile.References.MaxVideoDuration > 0 && media.DurationMs > int64(profile.References.MaxVideoDuration)*1000 {
|
||||
return BadAuthRequest("参考视频时长超过当前模型限制")
|
||||
}
|
||||
}
|
||||
for _, media := range input.ReferenceAudios {
|
||||
if profile.References.MaxAudioBytes > 0 && media.Bytes > profile.References.MaxAudioBytes {
|
||||
return BadAuthRequest("参考音频文件超过当前模型大小限制")
|
||||
}
|
||||
if profile.References.MaxAudioDuration > 0 && media.DurationMs > int64(profile.References.MaxAudioDuration)*1000 {
|
||||
return BadAuthRequest("参考音频时长超过当前模型限制")
|
||||
}
|
||||
}
|
||||
seconds, err := strconv.Atoi(strings.TrimSpace(input.Config.VideoSeconds))
|
||||
if err != nil || !videoDurationAllowed(profile.Duration, seconds) {
|
||||
return BadAuthRequest("视频时长不在当前模型支持范围内")
|
||||
}
|
||||
if input.Config.Size != "" && !videoRatioAllowed(profile.Ratios, input.Config.Size) {
|
||||
return BadAuthRequest("画面比例不在当前模型支持范围内")
|
||||
}
|
||||
if len(profile.Resolutions) > 0 && !isAutomaticVideoResolution(input.Config.VQuality) && videoResolutionNameRequest(profile, input.Config.VQuality) == "" {
|
||||
return BadAuthRequest("输出分辨率不在当前模型支持范围内")
|
||||
}
|
||||
operation := metadataString(input.Metadata, "videoEditOperation")
|
||||
if operation == "" {
|
||||
if len(input.ReferenceImages) > 0 {
|
||||
operation = "image_to_video"
|
||||
} else {
|
||||
operation = profile.DefaultOperation
|
||||
}
|
||||
}
|
||||
if !containsCapabilityString(profile.Operations, operation) {
|
||||
return BadAuthRequest("当前视频模型不支持该生成模式")
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func validateImageTask(profile *ImageCapabilityConfig, input canvasGenerationInput) error {
|
||||
if profile == nil {
|
||||
return nil
|
||||
}
|
||||
modelName := strings.TrimPrefix(strings.ToLower(strings.TrimSpace(input.Config.Model)), "models/")
|
||||
if input.Config.InterfaceType == string(model.ChannelInterfaceGrokImage) && modelName == "grok-imagine-image-quality" {
|
||||
const maxPromptBytes = 8000
|
||||
promptBytes := len(withSystemPrompt(input.Config, input.Prompt))
|
||||
if promptBytes > maxPromptBytes {
|
||||
return BadAuthRequest(fmt.Sprintf("Grok 图片完整提示词为 %d UTF-8 字节，超过上游 %d 字节限制。系统不会自动删改；请精简当前输入、连线文本、角色卡、画风或模板内容后重试", promptBytes, maxPromptBytes))
|
||||
}
|
||||
}
|
||||
if len(input.ReferenceImages) > profile.References.MaxImages {
|
||||
return BadAuthRequest(fmt.Sprintf("当前图片模型最多支持 %d 张参考图", profile.References.MaxImages))
|
||||
}
|
||||
for _, media := range input.ReferenceImages {
|
||||
if profile.References.MaxImageBytes > 0 && media.Bytes > profile.References.MaxImageBytes {
|
||||
return BadAuthRequest("参考图片文件超过当前模型大小限制")
|
||||
}
|
||||
}
|
||||
if input.Mask != nil && !profile.References.MaskSupported {
|
||||
return BadAuthRequest("当前图片模型不支持蒙版编辑")
|
||||
}
|
||||
if profile.Size.Parameter != "none" && !profile.Size.AllowCustom && strings.TrimSpace(input.Config.Size) != "" && !containsCapabilityString(profile.Size.Values, input.Config.Size) {
|
||||
return BadAuthRequest("图片尺寸不在当前模型支持范围内")
|
||||
}
|
||||
if profile.Size.Parameter == "size" && profile.Size.AllowCustom && strings.HasPrefix(modelName, "gpt-image-2") && !containsCapabilityString(profile.Size.Values, input.Config.Size) {
|
||||
if err := validateGPTImage2CustomSize(input.Config.Size); err != nil {
|
||||
return BadAuthRequest(err.Error())
|
||||
}
|
||||
}
|
||||
quality := strings.TrimSpace(input.Config.Quality)
|
||||
if profile.Quality.Supported && quality != "" && !strings.EqualFold(quality, "auto") && !strings.EqualFold(quality, "any") && !containsCapabilityString(profile.Quality.Values, quality) {
|
||||
return BadAuthRequest("图片质量不在当前模型支持范围内")
|
||||
}
|
||||
if err := validateImagePresetSelection(profile, qualityForImageValidation(quality, profile.Quality.Default), firstNonEmpty(input.Config.Size, profile.Size.Default)); err != nil {
|
||||
return err
|
||||
}
|
||||
count, err := strconv.Atoi(strings.TrimSpace(input.Config.Count))
|
||||
if err == nil && count > profile.MaxOutputs {
|
||||
return BadAuthRequest(fmt.Sprintf("当前图片模型单次最多生成 %d 张", profile.MaxOutputs))
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func qualityForImageValidation(quality string, fallback string) string {
|
||||
if strings.EqualFold(quality, "auto") || strings.EqualFold(quality, "any") {
|
||||
return fallback
|
||||
}
|
||||
return firstNonEmpty(quality, fallback)
|
||||
}
|
||||
|
||||
func validateImagePresetSelection(profile *ImageCapabilityConfig, quality, ratio string) error {
|
||||
if profile.Size.Parameter != "aspect_ratio" || profile.Size.AllowCustom || len(profile.Size.Presets) == 0 || ratio == "auto" {
|
||||
return nil
|
||||
}
|
||||
tier := imageResolutionTier(quality)
|
||||
if tier == "" {
|
||||
return nil
|
||||
}
|
||||
for _, preset := range profile.Size.Presets {
|
||||
if preset.Tier == tier && preset.Ratio == ratio {
|
||||
return nil
|
||||
}
|
||||
}
|
||||
return BadAuthRequest("当前分辨率不支持所选图片宽高比")
|
||||
}
|
||||
|
||||
func imageResolutionTier(quality string) string {
|
||||
switch strings.ToLower(strings.TrimSpace(quality)) {
|
||||
case "1k", "low":
|
||||
return "1k"
|
||||
case "2k", "medium":
|
||||
return "2k"
|
||||
case "4k", "high":
|
||||
return "4k"
|
||||
default:
|
||||
return ""
|
||||
}
|
||||
}
|
||||
|
||||
func validateWorkflowProviderPromptLength(input canvasGenerationInput) error {
|
||||
profile := input.Config.CapabilityConfig
|
||||
if input.Mode != "video" || profile == nil || profile.Video == nil {
|
||||
return nil
|
||||
}
|
||||
return validateModelPromptLength("视频", input.Prompt, profile.Video.References.PromptMaxChars)
|
||||
}
|
||||
|
||||
func validateModelPromptLength(label string, prompt string, maxChars int) error {
|
||||
if maxChars <= 0 {
|
||||
return nil
|
||||
}
|
||||
actualChars := utf8.RuneCountInString(prompt)
|
||||
if actualChars <= maxChars {
|
||||
return nil
|
||||
}
|
||||
return BadAuthRequest(fmt.Sprintf("当前%s模型提示词最多 %d 个字符，完整提示词为 %d 个字符。系统不会自动截断，请精简当前输入、连线内容或技能上下文后重试", label, maxChars, actualChars))
|
||||
}
|
||||
|
||||
func validateGPTImage2CustomSize(value string) error {
|
||||
value = strings.ToLower(strings.TrimSpace(strings.ReplaceAll(value, "×", "x")))
|
||||
if value == "" || value == "auto" {
|
||||
return nil
|
||||
}
|
||||
parts := strings.Split(value, "x")
|
||||
if len(parts) != 2 {
|
||||
return errors.New("自定义图片尺寸请使用宽x高，例如 3840x1920")
|
||||
}
|
||||
width, widthErr := strconv.Atoi(parts[0])
|
||||
height, heightErr := strconv.Atoi(parts[1])
|
||||
if widthErr != nil || heightErr != nil || width <= 0 || height <= 0 {
|
||||
return errors.New("图片尺寸必须是正整数")
|
||||
}
|
||||
if width%16 != 0 || height%16 != 0 {
|
||||
return errors.New("图片尺寸宽高必须是 16 的倍数")
|
||||
}
|
||||
if max(width, height) > 3840 {
|
||||
return errors.New("图片尺寸最长边不能超过 3840px")
|
||||
}
|
||||
if max(width, height) > min(width, height)*3 {
|
||||
return errors.New("图片宽高比不能超过 3:1")
|
||||
}
|
||||
pixels := int64(width) * int64(height)
|
||||
if pixels < 655360 || pixels > 8294400 {
|
||||
return errors.New("图片总像素需在 655360 到 8294400 之间")
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func videoDurationAllowed(value VideoDurationConfig, seconds int) bool {
|
||||
if value.Selection == "enum" {
|
||||
return containsInt(value.Values, seconds)
|
||||
}
|
||||
return seconds >= value.Min && seconds <= value.Max && value.Step > 0 && (seconds-value.Min)%value.Step == 0
|
||||
}
|
||||
|
||||
func videoRatioAllowed(options []string, value string) bool {
|
||||
value = strings.TrimSpace(strings.ToLower(strings.ReplaceAll(value, "×", "x")))
|
||||
if containsCapabilityString(options, value) {
|
||||
return true
|
||||
}
|
||||
parts := strings.Split(value, "x")
|
||||
if len(parts) != 2 {
|
||||
return false
|
||||
}
|
||||
width, widthErr := strconv.ParseFloat(parts[0], 64)
|
||||
height, heightErr := strconv.ParseFloat(parts[1], 64)
|
||||
if widthErr != nil || heightErr != nil || width <= 0 || height <= 0 {
|
||||
return false
|
||||
}
|
||||
actual := width / height
|
||||
for _, option := range options {
|
||||
candidate := ratioValue(option)
|
||||
if candidate > 0 && absFloat(candidate-actual)/candidate < 0.01 {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func ratioValue(value string) float64 {
|
||||
parts := strings.Split(strings.TrimSpace(value), ":")
|
||||
if len(parts) != 2 {
|
||||
return 0
|
||||
}
|
||||
width, widthErr := strconv.ParseFloat(parts[0], 64)
|
||||
height, heightErr := strconv.ParseFloat(parts[1], 64)
|
||||
if widthErr != nil || heightErr != nil || width <= 0 || height <= 0 {
|
||||
return 0
|
||||
}
|
||||
return width / height
|
||||
}
|
||||
|
||||
func normalizeResolution(value string) string {
|
||||
value = strings.ToLower(strings.TrimSpace(value))
|
||||
value = strings.TrimSuffix(value, "p")
|
||||
if value == "2k" {
|
||||
return "1440p"
|
||||
}
|
||||
if value == "4k" {
|
||||
return "2160p"
|
||||
}
|
||||
return value + "p"
|
||||
}
|
||||
|
||||
func containsCapabilityString(values []string, target string) bool {
|
||||
for _, value := range values {
|
||||
if strings.EqualFold(strings.TrimSpace(value), strings.TrimSpace(target)) {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func containsInt(values []int, target int) bool {
|
||||
for _, value := range values {
|
||||
if value == target {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func absFloat(value float64) float64 {
|
||||
if value < 0 {
|
||||
return -value
|
||||
}
|
||||
return value
|
||||
}
|
||||
Reference in new issue
Block a user