import {z} from 'zod'

export type ProjectSubsetEnum = 'All' | 'HasGT' | 'Sample' | 'Custom';

export type ModelRunRequestRequest = {filters_json: unknown, job_id?: (string | null) | undefined, only_missing_predictions?: boolean | undefined, organization?: (number | null) | undefined, predictions_updated_at?: (string | null) | undefined, project: number, project_subset?: ProjectSubsetEnum | undefined, sample_subset_size?: (number | null) | undefined, total_correct_predictions?: (number | null) | undefined, total_predictions?: (number | null) | undefined, total_tasks?: (number | null) | undefined};

export type CreateApiApiPromptsPromptIdVersionsVersionIdInferenceRunsArgs = {prompt_id: number, version_id: number, body: ModelRunRequestRequest};

export type CreateApiApiPromptsPromptIdVersionsVersionIdInferenceRunsOptions = {baseUrl?: string | undefined, Token?: string | undefined, fetch?: typeof fetch | undefined};

export const userSimple = z.object({avatar: z.string().nullable(), email: z.string().max(254).optional(), first_name: z.string().max(256).optional(), id: z.number().int(), last_name: z.string().max(256).optional(), username: z.string().max(256)});

export const projectSubsetEnum = z.enum(["All", "HasGT", "Sample", "Custom"]);

export const modelRunStatusEnum = z.enum(["Pending", "InProgress", "Completed", "Failed", "Canceled"]);

export const modelRun = z.object({completed_at: z.string().nullable(), created_at: z.string(), created_by: userSimple, filters_json: z.unknown(), id: z.number().int(), job_id: z.string().max(255).nullable().optional(), model_version: z.number().int(), organization: z.number().int().nullable().optional(), parent_model: z.number().int(), predictions_updated_at: z.string().nullable().optional(), project: z.number().int(), project_subset: projectSubsetEnum.optional(), sample_subset_size: z.number().int().gte(0).lte(2147483647).nullable().optional(), source_model_run: z.number().int().nullable(), status: modelRunStatusEnum, task_ids: z.unknown(), total_correct_predictions: z.number().int().gte(-2147483648).lte(2147483647).nullable().optional(), total_predictions: z.number().int().gte(-2147483648).lte(2147483647).nullable().optional(), total_tasks: z.number().int().gte(-2147483648).lte(2147483647).nullable().optional(), triggered_at: z.string().nullable()});

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
};

/**
 * ✨ Run prompt inference
 * 
 * POST /api/prompts/{prompt_id}/versions/{version_id}/inference-runs
 */
export const createApiApiPromptsPromptIdVersionsVersionIdInferenceRuns = async (args: CreateApiApiPromptsPromptIdVersionsVersionIdInferenceRunsArgs, options?: CreateApiApiPromptsPromptIdVersionsVersionIdInferenceRunsOptions) => {
const {baseUrl = "http://localhost:8000", fetch: fetchFn = fetch, Token} = options ?? {}

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

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

const url = `${baseUrl.replace(/\/+$/, '')}/api/prompts/${encodeURIComponent(String(args.prompt_id))}/versions/${encodeURIComponent(String(args.version_id))}/inference-runs${query.size > 0 ? `?${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(modelRun, await res.json())
};