import {z} from 'zod'

export type TrainingFile = {file_id: string, weight?: number | undefined};

export type GithubRepositoryIn = {owner: string, ref?: (string | null) | undefined, name: string, weight?: number | undefined, type?: 'github' | undefined, token: string};

export type TrainingParametersIn = {fim_ratio?: (number | null) | undefined, weight_decay?: (number | null) | undefined, training_steps?: (number | null) | undefined, learning_rate?: number | undefined, epochs?: (number | null) | undefined, seq_len?: (number | null) | undefined, warmup_fraction?: (number | null) | undefined};

export type FineTuneableModel = 'open-mistral-7b' | 'mistral-small-latest' | 'codestral-latest' | 'mistral-large-latest' | 'open-mistral-nemo' | 'ministral-3b-latest';

export type WandbIntegration = {api_key: string, name?: (string | null) | undefined, project: string, type?: 'wandb' | undefined, run_name?: (string | null) | undefined};

export type JobIn = {training_files?: Array<TrainingFile> | undefined, repositories?: Array<GithubRepositoryIn> | undefined, hyperparameters: TrainingParametersIn, model: FineTuneableModel, suffix?: (string | null) | undefined, integrations?: (Array<WandbIntegration> | null) | undefined, validation_files?: (Array<string> | null) | undefined, auto_start?: boolean | undefined};

export type CreateApiFineTuningJobsArgs = {dry_run?: (boolean | null) | undefined, body: JobIn};

export type CreateApiFineTuningJobsOptions = {baseUrl?: string | undefined, ApiKey?: string | undefined, fetch?: typeof fetch | undefined};

export const jobMetadataOut = z.object({data_tokens: z.number().int().nullable().optional(), train_tokens_per_step: z.number().int().nullable().optional(), cost: z.number().nullable().optional(), cost_currency: z.string().nullable().optional(), estimated_start_time: z.number().int().nullable().optional(), expected_duration_seconds: z.number().int().nullable().optional(), train_tokens: z.number().int().nullable().optional()});

export const githubRepositoryOut = z.object({owner: z.string(), ref: z.string().nullable().optional(), name: z.string(), weight: z.number().gt(0).optional(), type: z.literal("github").optional(), commit_id: z.string().min(40).max(40)});

export const trainingParameters = z.object({fim_ratio: z.number().gte(0).lte(1).nullable().optional(), weight_decay: z.number().gte(0).lte(1).nullable().optional(), training_steps: z.number().int().gte(1).nullable().optional(), learning_rate: z.number().gte(1e-8).lte(1).optional(), epochs: z.number().gt(0).nullable().optional(), seq_len: z.number().int().gte(100).nullable().optional(), warmup_fraction: z.number().gte(0).lte(1).nullable().optional()});

export const fineTuneableModel = z.enum(["open-mistral-7b", "mistral-small-latest", "codestral-latest", "mistral-large-latest", "open-mistral-nemo", "ministral-3b-latest"]);

export const wandbIntegrationOut = z.object({name: z.string().nullable().optional(), project: z.string(), type: z.literal("wandb").optional(), run_name: z.string().nullable().optional()});

export const jobOut = z.object({job_type: z.string(), metadata: jobMetadataOut.optional(), fine_tuned_model: z.string().nullable().optional(), created_at: z.number().int(), suffix: z.string().nullable().optional(), auto_start: z.boolean(), training_files: z.array(z.string()), repositories: z.array(githubRepositoryOut).optional(), hyperparameters: trainingParameters, model: fineTuneableModel, id: z.string(), trained_tokens: z.number().int().nullable().optional(), modified_at: z.number().int(), integrations: z.array(wandbIntegrationOut).nullable().optional(), status: z.enum(["QUEUED", "STARTED", "VALIDATING", "VALIDATED", "RUNNING", "FAILED_VALIDATION", "FAILED", "SUCCESS", "CANCELLED", "CANCELLATION_REQUESTED"]), validation_files: z.array(z.string()).nullable().optional(), object: z.literal("job").optional()});

export const legacyJobMetadataOut = z.object({data_tokens: z.number().int().nullable().optional(), train_tokens_per_step: z.number().int().nullable().optional(), cost: z.number().nullable().optional(), cost_currency: z.string().nullable().optional(), estimated_start_time: z.number().int().nullable().optional(), expected_duration_seconds: z.number().int().nullable().optional(), deprecated: z.boolean().optional(), details: z.string(), train_tokens: z.number().int().nullable().optional(), epochs: z.number().nullable().optional(), training_steps: z.number().int().nullable().optional(), object: z.literal("job.metadata").optional()});

export const createApiFineTuningJobsResponse = z.union([jobOut, legacyJobMetadataOut]);

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
};

/**
 * Create Fine Tuning Job
 * 
 * POST /fine_tuning/jobs
 */
export const createApiFineTuningJobs = async (args: CreateApiFineTuningJobsArgs, options?: CreateApiFineTuningJobsOptions) => {
const {baseUrl = "https://api.mistral.ai/v1", 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 (args.dry_run != null) query.append("dry_run", String(args.dry_run))
if (ApiKey !== undefined) headers.set('authorization', `Bearer ${ApiKey}`)

const url = `${baseUrl.replace(/\/+$/, '')}/fine_tuning/jobs${query.size > 0 ? `?${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(createApiFineTuningJobsResponse, await res.json())
};