import {z} from 'zod'

export type GetApiDocumentsV1JobsJobIdArgs = {job_id: string};

export type GetApiDocumentsV1JobsJobIdOptions = {baseUrl?: string | undefined, bearerAuth?: string | undefined, fetch?: typeof fetch | undefined};

export const chunk = z.object({content: z.string(), page_number: z.number().int().gte(0)});

export const chunkOrString = z.union([z.array(chunk), z.array(z.string())]);

export const oneOrManyI32 = z.union([z.number().int(), z.array(z.number().int())]);

export const structuredDataPage = z.object({page_number: oneOrManyI32.optional(), json_result: z.unknown()});

export const structuredDataResponse = z.object({pages: z.array(structuredDataPage).optional()});

export const outputErrorResponse = z.object({context: z.string(), err_message: z.string()});

export const outputErrorsResponse = z.object({errors: z.array(outputErrorResponse).optional()});

export const parsedJobOutput = z.object({chunks: chunkOrString.optional(), pages: z.unknown(), num_pages: z.number().int().nullable().optional(), structured_data: structuredDataResponse.nullable().optional(), errors: outputErrorsResponse.nullable().optional()});

export const jobStatus = z.enum(["failure", "pending", "processing", "successful"]);

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 jobResponse = z.object({message: z.string().nullable().optional(), jobId: z.string(), fileId: z.string().nullable().optional(), fileName: z.string().nullable().optional(), traceId: z.string().nullable().optional(), pageRange: z.string().nullable().optional(), parsedPages: z.number().int().nullable().optional(), outputs: parsedJobOutput.nullable().optional(), chunks: z.array(chunk).nullable().optional(), document: z.unknown(), structuredOutput: z.unknown(), status: jobStatus, settings: settings, tasksCompleted: z.number().int().nullable().optional(), tasksTotal: z.number().int().nullable().optional(), createdAt: z.string(), finishedAt: z.string().nullable().optional(), labels: z.record(z.string(), z.unknown()).optional()});

export const validateResponse = async <Output>(
  schema: {
    readonly '~standard': {
      readonly validate: (value: unknown) => ({ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }) | Promise<{ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }>
    }
  },
  value: unknown
): Promise<Output> => {
  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/jobs/{job_id}
 */
export const getApiDocumentsV1JobsJobId = async (args: GetApiDocumentsV1JobsJobIdArgs, options?: GetApiDocumentsV1JobsJobIdOptions) => {
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/jobs/${encodeURIComponent(String(args.job_id))}${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(jobResponse, await res.json())
};