feat: add document OCR and offline model archives
This commit is contained in:
lofyer
@@ -0,0 +1,310 @@
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import { z } from 'zod'
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export const documentParsingPurposeSchema = z.enum([
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'chat-attachment',
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'knowledge-index',
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'diagnostic'
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])
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export const chatDocumentWorkflowSchema = z.enum([
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'auto',
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'fast-text',
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'high-fidelity'
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])
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export const knowledgeDocumentWorkflowSchema = z.enum([
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'complete-index',
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'fast-index',
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'high-fidelity'
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])
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export const pdfOcrModeSchema = z.enum([
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'auto',
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'always',
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'disabled'
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])
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export const documentOcrProviderSchema = z.literal('local')
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export const localOcrModelIdSchema = z
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.string()
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.min(1)
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.max(96)
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.regex(/^[a-z0-9]+(?:-[a-z0-9]+)*$/u)
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const documentOcrSha256Schema = z
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.string()
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.regex(/^[a-f0-9]{64}$/u)
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export const documentOcrModelFileRoleSchema = z.enum([
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'detection',
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'recognition',
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'dictionary'
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])
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export const documentOcrModelDownloadSchema = z
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.object({
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url: z.url().max(2_048),
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size: z.number().int().positive().safe(),
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sha256: documentOcrSha256Schema
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})
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.strict()
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export const documentOcrModelFileSchema = z
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.object({
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name: z
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.string()
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.min(1)
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.max(255)
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.regex(/^[^/\\\0]+$/u),
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role: documentOcrModelFileRoleSchema,
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download: documentOcrModelDownloadSchema
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})
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.strict()
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export const documentOcrModelCatalogEntrySchema = z
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.object({
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id: localOcrModelIdSchema,
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displayName: z.string().trim().min(1).max(120),
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description: z.string().trim().min(1).max(500),
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languages: z.array(z.string().trim().min(1).max(32)).min(1).max(32),
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runtime: z.literal('onnxruntime-web-wasm'),
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quality: z.enum(['basic', 'balanced', 'high']),
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speed: z.enum(['fast', 'balanced', 'slow']),
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recommended: z.boolean(),
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repositoryUrl: z.url().max(2_048),
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license: z
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.object({
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name: z.string().trim().min(1).max(120),
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notice: z.string().trim().min(1).max(1_000),
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url: z.url().max(2_048)
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})
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.strict(),
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files: z.array(documentOcrModelFileSchema).length(3)
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})
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.strict()
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.superRefine((entry, context) => {
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if (
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new Set(entry.files.map((file) => file.name)).size !==
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entry.files.length
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) {
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context.addIssue({
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code: 'custom',
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path: ['files'],
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message: 'OCR 模型文件名不能重复'
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})
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}
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if (
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new Set(entry.files.map((file) => file.role)).size !==
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entry.files.length
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) {
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context.addIssue({
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code: 'custom',
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path: ['files'],
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message: 'OCR 模型文件角色不能重复'
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})
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}
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})
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export const installedDocumentOcrModelSchema = z
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.object({
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id: localOcrModelIdSchema,
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displayName: z.string().trim().min(1).max(120),
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source: z.enum(['download', 'local']),
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installedAt: z.string().datetime(),
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files: z
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.array(
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z
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.object({
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name: z.string().min(1).max(255).regex(/^[^/\\\0]+$/u),
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role: documentOcrModelFileRoleSchema,
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size: z.number().int().positive().safe(),
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sha256: documentOcrSha256Schema
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})
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.strict()
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)
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.length(3)
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})
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.strict()
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export const documentOcrModelOperationSchema = z
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.object({
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modelId: localOcrModelIdSchema,
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kind: z.enum(['download', 'import']),
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phase: z.enum(['preparing', 'transferring', 'installing']),
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currentFile: z.string().min(1).max(255).nullable(),
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completedBytes: z.number().int().nonnegative().safe(),
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totalBytes: z.number().int().nonnegative().safe().nullable()
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})
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.strict()
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export const documentOcrModelSnapshotSchema = z
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.object({
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rootDirectory: z.string().min(1).max(32_768),
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catalog: z.array(documentOcrModelCatalogEntrySchema).max(16),
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installed: z.array(installedDocumentOcrModelSchema).max(16),
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operations: z.array(documentOcrModelOperationSchema).max(8)
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})
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.strict()
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export const documentOcrModelActionInputSchema = z
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.object({
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modelId: localOcrModelIdSchema
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})
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.strict()
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export const documentParsingSettingsSchema = z
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.object({
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chatWorkflow: chatDocumentWorkflowSchema,
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knowledgeWorkflow: knowledgeDocumentWorkflowSchema,
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pdfOcrMode: pdfOcrModeSchema,
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ocrProvider: documentOcrProviderSchema,
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localOcrEnabled: z.boolean(),
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localOcrModelId: localOcrModelIdSchema,
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maximumPages: z.number().int().min(1).max(500),
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ocrConcurrency: z.number().int().min(1).max(4),
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pageTimeoutSeconds: z.number().int().min(10).max(300)
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})
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.strict()
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export const documentParsingSettingsUpdateSchema =
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documentParsingSettingsSchema
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export const documentParsingModelStatusSchema = z
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.object({
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id: localOcrModelIdSchema,
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displayName: z.string().trim().min(1).max(120),
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available: z.boolean(),
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verified: z.boolean(),
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runtime: z.literal('onnxruntime-web-wasm'),
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detail: z.string().trim().min(1).max(500)
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})
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.strict()
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export const documentParsingStatusSchema = z
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.object({
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nativeParsingAvailable: z.literal(true),
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conversionAvailable: z.boolean(),
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localOcr: documentParsingModelStatusSchema
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})
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.strict()
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export const documentParsingSnapshotSchema = z
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.object({
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settings: documentParsingSettingsSchema,
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status: documentParsingStatusSchema,
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ocrModels: documentOcrModelSnapshotSchema
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})
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.strict()
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export const documentParsingTestInputSchema = z
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.object({
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purpose: documentParsingPurposeSchema.default('diagnostic')
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})
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.strict()
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export const documentParsingDiagnosticSchema = z
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.object({
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fileName: z.string().trim().min(1).max(500),
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sourceFormat: z.string().trim().min(1).max(32),
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pageCount: z.number().int().nonnegative().max(10_000),
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ocrPageCount: z.number().int().nonnegative().max(10_000),
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characterCount: z.number().int().nonnegative().safe(),
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method: z.enum(['native', 'ocr', 'mixed']),
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durationMs: z.number().int().nonnegative().safe(),
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preview: z.string().max(2_000),
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warnings: z.array(z.string().trim().min(1).max(500)).max(20)
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})
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.strict()
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export const documentOcrAssetsSchema = z
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.object({
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modelId: localOcrModelIdSchema,
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detection: z.instanceof(ArrayBuffer),
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recognition: z.instanceof(ArrayBuffer),
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dictionary: z.instanceof(ArrayBuffer)
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})
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.strict()
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export const documentOcrRequestSchema = z
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.object({
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requestId: z.string().uuid(),
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modelId: localOcrModelIdSchema,
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fileName: z.string().trim().min(1).max(500),
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mimeType: z.enum([
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'application/pdf',
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'image/jpeg',
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'image/png',
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'image/webp'
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]),
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data: z
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.instanceof(ArrayBuffer)
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.refine(
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(value) => value.byteLength > 0 && value.byteLength <= 20 * 1024 * 1024,
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'OCR 输入必须介于 1 字节和 20MB 之间'
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),
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maximumPages: z.number().int().min(1).max(500),
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pageNumbers: z
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.array(z.number().int().min(1).max(10_000))
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.min(1)
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.max(500)
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.optional(),
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pageTimeoutSeconds: z.number().int().min(10).max(300)
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})
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.strict()
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export const documentOcrSectionSchema = z
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.object({
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locator: z.string().trim().min(1).max(500),
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content: z.string().trim().min(1).max(1_000_000),
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confidence: z.number().min(0).max(1)
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})
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.strict()
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export const documentOcrResultSchema = z
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.object({
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requestId: z.string().uuid(),
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sections: z.array(documentOcrSectionSchema).max(500),
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pageCount: z.number().int().nonnegative().max(10_000),
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warnings: z.array(z.string().trim().min(1).max(500)).max(20)
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})
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.strict()
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export const documentOcrFailureSchema = z
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.object({
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requestId: z.string().uuid(),
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error: z.string().trim().min(1).max(1_000)
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})
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.strict()
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export type DocumentParsingPurpose = z.infer<
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typeof documentParsingPurposeSchema
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>
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export type DocumentParsingSettings = z.infer<
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typeof documentParsingSettingsSchema
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>
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export type DocumentParsingSnapshot = z.infer<
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typeof documentParsingSnapshotSchema
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>
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export type DocumentOcrModelFile = z.infer<
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typeof documentOcrModelFileSchema
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>
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export type DocumentOcrModelCatalogEntry = z.infer<
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typeof documentOcrModelCatalogEntrySchema
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>
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export type InstalledDocumentOcrModel = z.infer<
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typeof installedDocumentOcrModelSchema
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>
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export type DocumentOcrModelOperation = z.infer<
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typeof documentOcrModelOperationSchema
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>
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export type DocumentOcrModelSnapshot = z.infer<
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typeof documentOcrModelSnapshotSchema
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>
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export type DocumentParsingDiagnostic = z.infer<
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typeof documentParsingDiagnosticSchema
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>
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export type DocumentOcrAssets = z.infer<typeof documentOcrAssetsSchema>
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export type DocumentOcrRequest = z.infer<typeof documentOcrRequestSchema>
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export type DocumentOcrResult = z.infer<typeof documentOcrResultSchema>
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export type DocumentOcrFailure = z.infer<typeof documentOcrFailureSchema>
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