import {z} from 'zod'

export type GetApiV1ProjectsProjectIdImprovementTimeseriesArgs = {project_id: string};

export type GetApiV1ProjectsProjectIdImprovementTimeseriesOptions = {baseUrl: string, ApiKeyAuth?: string | undefined, fetch?: typeof fetch | undefined};

export const customMetricValue = z.object({name: z.string(), value: z.number(), source: z.enum(["user", "external"]), unverified: z.boolean().optional()});

export const evaluationResponse = z.object({id: z.string(), user_id: z.string(), project_id: z.string().nullable().optional(), model_id: z.string(), dataset_name: z.string(), dataset_version: z.string(), model_name: z.string().nullable().optional(), incumbent_model_id: z.string().nullable().optional(), f1_score: z.number().nullable().optional(), precision_score: z.number().nullable().optional(), recall_score: z.number().nullable().optional(), accuracy: z.number().nullable().optional(), validation_loss: z.number().nullable().optional(), subset_accuracy: z.number().nullable().optional(), hamming_loss: z.number().nullable().optional(), exact_match: z.number().nullable().optional(), bleu_score: z.number().nullable().optional(), rouge_l_score: z.number().nullable().optional(), total_tokens: z.number().int().nullable().optional(), total_cost_usd: z.number().nullable().optional(), total_latency_ms: z.number().int().nullable().optional(), max_examples: z.number().int().nullable().optional(), max_tokens: z.number().int().nullable().optional(), seed: z.number().int().nullable().optional(), config: z.record(z.string(), z.unknown()).nullable().optional(), metrics: z.record(z.string(), z.unknown()).nullable().optional(), custom_metrics: z.array(customMetricValue).nullable().optional(), status: z.string(), job_reference: z.string().nullable().optional(), error_message: z.string().nullable().optional(), error_count: z.number().int().nullable().optional(), error_sample: z.string().nullable().optional(), progress: z.number().int().nullable().optional(), total_examples: z.number().int().nullable().optional(), sample_count: z.number().int().nullable().optional(), evaluation_time_ms: z.number().int().nullable().optional(), created_at: z.string(), completed_at: z.string().nullable().optional(), failed_examples: z.array(z.record(z.string(), z.unknown())).nullable().optional(), predictions: z.array(z.record(z.string(), z.unknown())).nullable().optional(), confirmation_read_count: z.number().int().nullable().optional(), confirmation_read_experiment_ids: z.array(z.string()).nullable().optional(), confirmation_rotation_required: z.boolean().nullable().optional()});

export const datasetReference = z.object({name: z.string(), version: z.string().nullable().optional()});

export const trainingJobResponse = z.object({id: z.string(), user_id: z.string(), project_id: z.string().nullable().optional(), experiment_id: z.string().nullable().optional(), model_name: z.string().nullable().optional(), datasets: z.array(datasetReference), base_model: z.string(), validation_data_percentage: z.number(), nr_epochs: z.number().int(), learning_rate: z.number(), batch_size: z.number().int(), seed: z.number().int().nullable().optional(), resolved_recipe: z.record(z.string(), z.unknown()).nullable().optional(), trained_model_path: z.string().nullable().optional(), hub_model_id: z.string().nullable().optional(), hub_model_private: z.boolean().nullable().optional(), job_reference: z.string().nullable().optional(), instance_type: z.string().nullable().optional(), status: z.string(), normalized_status: z.string().nullable().optional(), is_terminal_status: z.boolean().nullable().optional(), error_message: z.string().nullable().optional(), created_at: z.string(), updated_at: z.string(), started_at: z.string().nullable().optional(), completed_at: z.string().nullable().optional(), model_auto_selected: z.boolean().nullable().optional(), model_selection_reason: z.string().nullable().optional(), task_type: z.string().nullable().optional(), training_type: z.string().nullable().optional(), model_kind: z.enum(["lora", "full"]).nullable().optional(), artifact_ready: z.boolean().nullable().optional(), provider_ready: z.boolean().nullable().optional(), is_deployable: z.boolean().nullable().optional(), deployability_reason: z.string().nullable().optional(), labels: z.array(z.string()).nullable().optional(), example: z.string().nullable().optional(), metrics: z.record(z.string(), z.unknown()).nullable().optional(), version_number: z.string().nullable().optional(), root_job_id: z.string().nullable().optional(), provider_deployments: z.record(z.string(), z.unknown()).nullable().optional(), provider_name: z.string().nullable().optional(), progress_percent: z.number().int().nullable().optional(), current_epoch: z.number().int().nullable().optional(), deployment_status: z.string().nullable()});

export const adapterTimeseriesEntry = z.object({training_job: trainingJobResponse, latest_eval: evaluationResponse.nullable().optional(), all_evals: z.array(evaluationResponse)});

export const improvementTimeseriesResponse = z.object({base_model_id: z.string().nullable().optional(), base_model_eval: evaluationResponse.nullable().optional(), adapters: z.array(adapterTimeseriesEntry)});

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
};

/**
 * Grouped training-job + evals + base-model-eval for a project
 * 
 * GET /v1/projects/{project_id}/improvement-timeseries
 * 
 * Also accepts auth: BearerAuth
 */
export const getApiV1ProjectsProjectIdImprovementTimeseries = async (args: GetApiV1ProjectsProjectIdImprovementTimeseriesArgs, options: GetApiV1ProjectsProjectIdImprovementTimeseriesOptions) => {
const {baseUrl, fetch: fetchFn = fetch, ApiKeyAuth} = options ?? {}

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

if (ApiKeyAuth !== undefined) headers.set("X-API-Key", ApiKeyAuth)

const url = `${baseUrl.replace(/\/+$/, '')}/v1/projects/${encodeURIComponent(String(args.project_id))}/improvement-timeseries${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(improvementTimeseriesResponse, await res.json())
};