import {z} from 'zod' export type GetApiDocumentsV1DatasetsDatasetNameArgs = {dataset_name: string}; export type GetApiDocumentsV1DatasetsDatasetNameOptions = {baseUrl?: string | undefined, bearerAuth?: string | undefined, fetch?: typeof fetch | undefined}; export const tableParsingStrategy = z.enum(["tsr", "vlm", "unknown"]); export const tableOutputMode = z.enum(["markdown", "html"]); export const formDetectionMode = z.enum(["vlm", "tsr", "unknown"]); export const chunkStrategy = z.enum(["page", "section", "fragment"]); export const modelProvider = z.enum(["tensorlake", "claude-3-5-sonnet-latest", "gpt-4o-mini"]); export const settings = z.object({tableParsingMode: tableParsingStrategy.optional(), tableOutputMode: tableOutputMode.optional(), tableSummarization: z.boolean().optional(), tableSummarizationPrompt: z.string().nullable().optional(), figureSummarization: z.boolean().optional(), figureSummarizationPrompt: z.string().nullable().optional(), formDetectionMode: formDetectionMode.optional(), chunkStrategy: chunkStrategy.nullable().optional(), jsonSchema: z.unknown(), structuredExtractionPrompt: z.string().nullable().optional(), modelProvider: modelProvider.nullable().optional(), deliverWebhook: z.boolean().optional(), detectSignature: z.boolean().optional(), skewCorrection: z.boolean().optional(), disableLayoutDetection: z.boolean().optional(), structuredExtractionSkipOcr: z.boolean().optional(), detectStrikethrough: z.boolean().optional()}); export const datasetStatus = z.enum(["idle", "processing"]); export const jobStatus = z.enum(["failure", "pending", "processing", "successful"]); export const pageDatasetJobItem = z.object({items: z.array(z.object({id: z.string(), datasetId: z.string(), fileId: z.string().nullable().optional(), fileName: z.string().nullable().optional(), outputsUrl: z.string().nullable().optional(), status: jobStatus, errorMessage: z.string().nullable().optional(), createdAt: z.string(), updatedAt: z.string()})), hasMore: z.boolean(), prevCursor: z.string().nullable().optional(), nextCursor: z.string().nullable().optional()}); export const datasetAnalytics = z.object({totalJobs: z.number().int().gte(0), totalProcessingJobs: z.number().int().gte(0), totalErrorJobs: z.number().int().gte(0), totalSuccessfulJobs: z.number().int().gte(0), totalPendingJobs: z.number().int().gte(0)}); export const datasetResponse = z.object({id: z.string(), name: z.string(), description: z.string().nullable().optional(), settings: settings, status: datasetStatus.optional(), createdAt: z.string(), jobs: pageDatasetJobItem.optional(), analytics: datasetAnalytics}); export const validateResponse = async ( schema: { readonly '~standard': { readonly validate: (value: unknown) => ({ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray | undefined }> }) | Promise<{ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray | undefined }> }> } }, value: unknown ): Promise => { const result = await schema['~standard'].validate(value) if (result.issues !== undefined) { const detail = result.issues .map(({ message, path }) => path?.length ? `${path.map((segment) => String(typeof segment === 'object' ? segment.key : segment)).join('.')}: ${message}` : message ) .join('; ') throw new Error(`Response does not match the schema: ${detail}`, { cause: { issues: result.issues } }) } return result.value }; /** * GET /documents/v1/datasets/{dataset_name} */ export const getApiDocumentsV1DatasetsDatasetName = async (args: GetApiDocumentsV1DatasetsDatasetNameArgs, options?: GetApiDocumentsV1DatasetsDatasetNameOptions) => { const {baseUrl = "https://api.tensorlake.ai", fetch: fetchFn = fetch, bearerAuth} = options ?? {} const query = new URLSearchParams() const headers = new Headers() headers.set('accept', "application/json") if (bearerAuth !== undefined) headers.set('authorization', `Bearer ${bearerAuth}`) const url = `${baseUrl.replace(/\/+$/, '')}/documents/v1/datasets/${encodeURIComponent(String(args.dataset_name))}${query.size > 0 ? `?${query}` : ''}` const res = await fetchFn(url, {method: "GET", headers}) if (!res.ok) throw new Error(`Request failed with status ${res.status}`, {cause: {status: res.status, body: await res.text()}}) return validateResponse(datasetResponse, await res.json()) };