import {z} from 'zod'

export type BatchAIMetadataRequest = {document_ids: Array<string>, field_keys?: Array<string> | undefined};

export type CreateApiPublicBetaDocumentsAiMetadataArgs = {body: BatchAIMetadataRequest};

export type CreateApiPublicBetaDocumentsAiMetadataOptions = {baseUrl?: string | undefined, apiKey?: string | undefined, fetch?: typeof fetch | undefined};

export const aIMetadataFieldType = z.enum(["single_line", "multi_line", "date", "number", "dropdown", "checkbox", "url", "duration", "percent", "currency", "signature_info"]);

export const aIMetadataAcceptanceStatus = z.enum(["pending", "accepted"]);

export const aIMetadataValue = z.object({value: z.string(), acceptance_status: aIMetadataAcceptanceStatus});

export const aIMetadataField = z.object({id: z.string().max(22), key: z.string(), field_type: aIMetadataFieldType, settings: z.record(z.string(), z.unknown()), value: aIMetadataValue.nullable().optional()});

export const aIMetadataResponse = z.object({count: z.number().int().gte(0), results: z.array(aIMetadataField)});

export const batchAIMetadataResult = z.discriminatedUnion("status", [z.object({document_id: z.string().max(22), status: z.literal("ok"), ai_metadata: aIMetadataResponse}), z.object({document_id: z.string().max(22), status: z.literal("extraction_pending"), retry_after: z.number().int().gte(1), description: z.string()}), z.object({document_id: z.string().max(22), status: z.literal("extraction_failed"), description: z.string()}), z.object({document_id: z.string().max(22), status: z.literal("extraction_not_started"), description: z.string()}), z.object({document_id: z.string().max(22), status: z.literal("not_found"), description: z.string()}), z.object({document_id: z.string().max(22), status: z.literal("access_denied"), description: z.string()}), z.object({document_id: z.string().max(22), status: z.literal("internal_error"), description: z.string()})]);

export const batchAIMetadataResponse = z.object({count: z.number().int().gte(0), results: z.array(batchAIMetadataResult)});

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
};

/**
 * [Beta] Get AI Metadata for Multiple Documents
 * 
 * POST /public/beta/documents/ai-metadata
 * 
 * Also accepts auth: oauth2
 */
export const createApiPublicBetaDocumentsAiMetadata = async (args: CreateApiPublicBetaDocumentsAiMetadataArgs, options?: CreateApiPublicBetaDocumentsAiMetadataOptions) => {
const {baseUrl = "https://api.pandadoc.com", fetch: fetchFn = fetch, apiKey} = options ?? {}

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

if (apiKey !== undefined) headers.set("Authorization", apiKey)

const url = `${baseUrl.replace(/\/+$/, '')}/public/beta/documents/ai-metadata${query.size > 0 ? `?${query}` : ''}`

const res = await fetchFn(url, {method: "POST", 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(batchAIMetadataResponse, await res.json())
};