import {z} from 'zod'

export type RLEncodedTextChunk = {tokens: Array<string | number>};

export type RLModelInputChunk = {encoded_text: RLEncodedTextChunk};

export type RLModelInput = {chunks: Array<RLModelInputChunk>};

export type RLTensorData = {data: Array<number>, dtype: 'int64' | 'float32', shape?: Array<number> | undefined, sparse_crow_indices?: Array<number> | undefined, sparse_col_indices?: Array<number> | undefined};

export type RLTrainingSample = {model_input: RLModelInput, loss_fn_inputs: {[key: string]: RLTensorData}, routed_experts_key?: string | undefined};

export type RLLossType = 'LOSS_TYPE_UNSPECIFIED' | 'LOSS_TYPE_CROSS_ENTROPY' | 'LOSS_TYPE_GRPO' | 'LOSS_TYPE_IMPORTANCE_SAMPLING' | 'LOSS_TYPE_PPO' | 'LOSS_TYPE_CISPO' | 'LOSS_TYPE_DRO' | 'LOSS_TYPE_DPPO';

export type RLCrossEntropyLossParams = Record<string, never>;

export type RLGRPOLossAggregationType = 'GRPO_LOSS_AGGREGATION_TYPE_UNSPECIFIED' | 'GRPO_LOSS_AGGREGATION_TYPE_FIXED_HORIZON' | 'GRPO_LOSS_AGGREGATION_TYPE_TOKEN_MEAN' | 'GRPO_LOSS_AGGREGATION_TYPE_SEQUENCE_MEAN';

export type RLGRPOLossRatioType = 'GRPO_LOSS_RATIO_TYPE_TOKEN' | 'GRPO_LOSS_RATIO_TYPE_SEQUENCE';

export type RLGRPOLossParams = {clip_low_threshold?: number | undefined, clip_high_threshold?: number | undefined, beta?: number | undefined, agg_type?: RLGRPOLossAggregationType | undefined, ratio_type?: RLGRPOLossRatioType | undefined};

export type RLPPOLossParams = {clip_low_threshold?: number | undefined, clip_high_threshold?: number | undefined};

export type RLCISPOLossParams = {clip_low_threshold?: number | undefined, clip_high_threshold?: number | undefined};

export type RLDROLossParams = {beta: number};

export type RLDPPOLossParams = {delta_low?: number | undefined, delta_high?: number | undefined};

export type RLLossConfig = {type: RLLossType, cross_entropy_params?: RLCrossEntropyLossParams | undefined, grpo_params?: RLGRPOLossParams | undefined, ppo_params?: RLPPOLossParams | undefined, cispo_params?: RLCISPOLossParams | undefined, dro_params?: RLDROLossParams | undefined, dppo_params?: RLDPPOLossParams | undefined};

export type RLForwardBackwardBody = {samples: Array<RLTrainingSample>, loss: RLLossConfig, return_loss_fn_outputs?: boolean | undefined, forward_only?: boolean | undefined};

export type CreateApiV1RlTrainingSessionsSessionIdOperationsForwardBackwardArgs = {session_id: string, 'Idempotency-Key': string, body: RLForwardBackwardBody};

export type CreateApiV1RlTrainingSessionsSessionIdOperationsForwardBackwardOptions = {baseUrl?: string | undefined, bearerAuth?: string | undefined, fetch?: typeof fetch | undefined};

export const rLTrainingOperationStatus = z.enum(["TRAINING_OPERATION_STATUS_UNSPECIFIED", "TRAINING_OPERATION_STATUS_PENDING", "TRAINING_OPERATION_STATUS_RUNNING", "TRAINING_OPERATION_STATUS_COMPLETED", "TRAINING_OPERATION_STATUS_FAILED"]);

export const rLTensorData = z.object({data: z.array(z.number()), dtype: z.enum(["int64", "float32"]), shape: z.array(z.number().int()).optional(), sparse_crow_indices: z.array(z.number().int()).optional(), sparse_col_indices: z.array(z.number().int()).optional()});

export const rLLossFnOutput = z.object({tensors: z.record(z.string(), rLTensorData)});

export const rLForwardBackwardResult = z.object({loss: z.number(), metrics: z.record(z.string(), z.number()).optional(), loss_fn_outputs: z.array(rLLossFnOutput).optional()});

export const rLTrainingOperationErrorCode = z.enum(["TRAINING_OPERATION_ERROR_CODE_UNSPECIFIED", "TRAINING_OPERATION_ERROR_CODE_RESOURCE_EXHAUSTED", "TRAINING_OPERATION_ERROR_CODE_TIMEOUT", "TRAINING_OPERATION_ERROR_CODE_INTERNAL_ERROR", "TRAINING_OPERATION_ERROR_CODE_SESSION_NOT_ACTIVE", "TRAINING_OPERATION_ERROR_CODE_INVALID_INPUT", "TRAINING_OPERATION_ERROR_CODE_NON_FINITE_LOSS"]);

export const rLTrainingOperationError = z.object({code: rLTrainingOperationErrorCode.optional(), message: z.string().optional()});

export const rLForwardBackwardOperation = z.object({id: z.string(), status: rLTrainingOperationStatus, output: rLForwardBackwardResult.optional(), error: rLTrainingOperationError.optional()});

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
};

/**
 * Forward-backward pass
 * 
 * POST /v1/rl/training-sessions/{session_id}/operations/forward-backward
 */
export const createApiV1RlTrainingSessionsSessionIdOperationsForwardBackward = async (args: CreateApiV1RlTrainingSessionsSessionIdOperationsForwardBackwardArgs, options?: CreateApiV1RlTrainingSessionsSessionIdOperationsForwardBackwardOptions) => {
const {baseUrl = "https://api.together.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 (args['Idempotency-Key'] != null) headers.set("Idempotency-Key", String(args['Idempotency-Key']))
if (bearerAuth !== undefined) headers.set('authorization', `Bearer ${bearerAuth}`)

const url = `${baseUrl.replace(/\/+$/, '')}/v1/rl/training-sessions/${encodeURIComponent(String(args.session_id))}/operations/forward-backward${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(rLForwardBackwardOperation, await res.json())
};