import {z} from 'zod'

export type TableOutputMode = 'markdown' | 'html';

export type TableParsingFormat = 'tsr' | 'vlm';

export type ChunkingStrategy = 'none' | 'page' | 'section' | 'fragment';

export type PageFragmentType = 'section_header' | 'title' | 'text' | 'table' | 'figure' | 'formula' | 'form' | 'key_value_region' | 'document_index' | 'list_item' | 'table_caption' | 'figure_caption' | 'formula_caption' | 'page_footer' | 'page_header' | 'page_number' | 'signature' | 'strikethrough';

export type ParsingOptions = {table_output_mode?: TableOutputMode | undefined, table_parsing_format?: TableParsingFormat | undefined, chunking_strategy?: ChunkingStrategy | undefined, signature_detection?: boolean | undefined, remove_strikethrough_lines?: boolean | undefined, skew_detection?: boolean | undefined, disable_layout_detection?: boolean | undefined, ignore_sections?: Array<PageFragmentType> | undefined};

export type Model = 'tensorlake' | 'sonnet' | 'gpt4o_mini';

export type StructuredExtractionOptions = {schema_name: string, json_schema: unknown, skip_ocr?: boolean | undefined, prompt?: (string | null) | undefined, model_provider?: Model | undefined, partition_strategy?: ChunkingStrategy | undefined, page_classes?: (Array<string> | null) | undefined};

export type PageClassConfig = {name: string, description: string};

export type EnrichmentOptions = {table_summarization?: boolean | undefined, table_summarization_prompt?: (string | null) | undefined, figure_summarization?: boolean | undefined, figure_summarization_prompt?: (string | null) | undefined};

export type DatasetUpdateRequest = {parsing_options?: ParsingOptions | undefined, structured_extraction_options?: (Array<StructuredExtractionOptions> | null) | undefined, page_classifications?: (Array<PageClassConfig> | null) | undefined, enrichment_options?: EnrichmentOptions | undefined, description?: (string | null) | undefined};

export type UpdateApiDocumentsV2DatasetsDatasetIdArgs = {dataset_id: string, body: DatasetUpdateRequest};

export type UpdateApiDocumentsV2DatasetsDatasetIdOptions = {baseUrl?: string | undefined, bearerAuth?: string | undefined, fetch?: typeof fetch | undefined};

export const datasetStatus = z.enum(["idle", "processing"]);

export const dataset = z.object({name: z.string(), dataset_id: z.string(), description: z.string().nullable().optional(), status: datasetStatus, created_at: z.string(), updated_at: z.string()});

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
};

/**
 * PUT /documents/v2/datasets/{dataset_id}
 */
export const updateApiDocumentsV2DatasetsDatasetId = async (args: UpdateApiDocumentsV2DatasetsDatasetIdArgs, options?: UpdateApiDocumentsV2DatasetsDatasetIdOptions) => {
const {baseUrl = "https://api.tensorlake.ai", fetch: fetchFn = fetch, bearerAuth} = options ?? {}

const query = new URLSearchParams()
const headers = new Headers()
headers.set('content-type', "application/json")
headers.set('accept', "application/json")

if (bearerAuth !== undefined) headers.set('authorization', `Bearer ${bearerAuth}`)

const url = `${baseUrl.replace(/\/+$/, '')}/documents/v2/datasets/${encodeURIComponent(String(args.dataset_id))}${query.size > 0 ? `?${query}` : ''}`

const res = await fetchFn(url, {method: "PUT", headers, body: JSON.stringify(args.body)})

if (!res.ok) throw new Error(`Request failed with status ${res.status}`, {cause: {status: res.status, body: await res.text()}})

return validateResponse(dataset, await res.json())
};