import {z} from 'zod'

export type GetApiApiProjectIdClassifyV2SampleIdRawDataWindowIndexArgs = {projectId: number, sampleId: number, windowIndex: number, datastreamIndex?: number | undefined, impulseId?: number | undefined, truncateStructuredLabels?: boolean | undefined};

export type GetApiApiProjectIdClassifyV2SampleIdRawDataWindowIndexOptions = {baseUrl?: string | undefined, ApiKeyAuthentication?: string | undefined, fetch?: typeof fetch | undefined};

export const rawDataCategory = z.enum(["training", "testing", "validation", "post-processing"]);

export const sensor = z.object({index: z.number().int(), name: z.string(), units: z.string()});

export const boundingBox = z.object({label: z.string(), x: z.number().int(), y: z.number().int(), width: z.number().int(), height: z.number().int()});

export const projectLabelingMethod = z.enum(["single_label", "object_detection", "label_map"]);

export const sampleLabelMapLabels = z.object({type: z.literal("key-values"), labels: z.record(z.string(), z.string())});

export const structuredLabel = z.object({startIndex: z.number().int(), endIndex: z.number().int(), label: z.string(), labelMap: sampleLabelMapLabels.optional()});

export const lastUpdatedByUser = z.object({type: z.literal("user"), id: z.number().int()});

export const lastUpdatedByProjectApiKey = z.object({type: z.literal("projectApiKey"), id: z.number().int()});

export const lastUpdatedByOAuthClient = z.object({type: z.literal("oauthClient"), oauthClientId: z.string(), userId: z.number().int().optional()});

export const lastUpdatedByDatasetVersionRestore = z.object({type: z.literal("datasetVersionRestore"), datasetVersionId: z.number().int(), groupKey: z.string(), actor: z.union([z.object({type: z.literal("user"), id: z.number().int()}), z.object({type: z.literal("projectApiKey"), id: z.number().int()}), z.object({type: z.literal("oauthClient"), oauthClientId: z.string(), userId: z.number().int().optional()})]).optional()});

export const sampleDatastream = z.object({index: z.number().int(), chartType: z.enum(["chart", "image", "video", "table"]), intervalMs: z.number(), frequencyHz: z.number(), sensors: z.array(sensor), valuesCount: z.number().int(), imageDimensions: z.object({width: z.number().int(), height: z.number().int()}).optional(), totalLengthMs: z.number()});

export const sample = z.object({id: z.number().int(), filename: z.string(), signatureValidate: z.boolean(), signatureMethod: z.string().optional(), signatureKey: z.string().optional(), created: z.string(), lastModified: z.string(), category: rawDataCategory, coldstorageFilename: z.string(), label: z.string(), intervalMs: z.number(), frequency: z.number(), originalIntervalMs: z.number(), originalFrequency: z.number(), deviceName: z.string().optional(), deviceType: z.string(), sensors: z.array(sensor), valuesCount: z.number().int(), totalLengthMs: z.number().optional(), added: z.string(), boundingBoxes: z.array(boundingBox), boundingBoxesType: z.enum(["object_detection", "constrained_object_detection"]), chartType: z.enum(["chart", "image", "video", "table"]), thumbnailVideo: z.string().optional(), thumbnailVideoFull: z.string().optional(), isDisabled: z.boolean(), isProcessing: z.boolean(), processingJobId: z.number().int().optional(), processingError: z.boolean(), processingErrorString: z.string().optional(), isCropped: z.boolean(), metadata: z.record(z.string(), z.string()).optional(), projectId: z.number().int(), projectOwnerName: z.string().optional(), projectName: z.string().optional(), projectLabelingMethod: projectLabelingMethod.optional(), sha256Hash: z.string(), structuredLabels: z.array(structuredLabel).optional(), structuredLabelsList: z.array(z.string()).optional(), createdBySyntheticDataJobId: z.number().int().optional(), imageDimensions: z.object({width: z.number().int(), height: z.number().int()}).optional(), videoUrl: z.string().optional(), videoUrlFull: z.string().optional(), labelMap: sampleLabelMapLabels.optional(), lastUpdatedBy: z.discriminatedUnion("type", [lastUpdatedByUser, lastUpdatedByProjectApiKey, lastUpdatedByOAuthClient, lastUpdatedByDatasetVersionRestore]).optional(), datastreams: z.array(sampleDatastream)});

export const rawSamplePayload = z.object({device_name: z.string().optional(), device_type: z.string(), sensors: z.array(sensor), values: z.array(z.array(z.number())), cropStart: z.number().int().optional(), cropEnd: z.number().int().optional(), intervalMs: z.number(), frequencyHz: z.number()});

export const getSampleDspResponse = z.object({success: z.boolean(), error: z.string().optional(), sample: sample, payload: rawSamplePayload, totalPayloadLength: z.number().int()});

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
};

/**
 * Get a window of raw sample features from cache, after a live classification job has completed.
 * 
 * GET /api/{projectId}/classify/v2/{sampleId}/raw-data/{windowIndex}
 * 
 * Also accepts auth: JWTAuthentication, JWTHttpHeaderAuthentication, OAuth2
 */
export const getApiApiProjectIdClassifyV2SampleIdRawDataWindowIndex = async (args: GetApiApiProjectIdClassifyV2SampleIdRawDataWindowIndexArgs, options?: GetApiApiProjectIdClassifyV2SampleIdRawDataWindowIndexOptions) => {
const {baseUrl = "https://studio.edgeimpulse.com/v1", fetch: fetchFn = fetch, ApiKeyAuthentication} = options ?? {}

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

if (args.datastreamIndex != null) query.append("datastreamIndex", String(args.datastreamIndex))
if (args.impulseId != null) query.append("impulseId", String(args.impulseId))
if (args.truncateStructuredLabels != null) query.append("truncateStructuredLabels", String(args.truncateStructuredLabels))
if (ApiKeyAuthentication !== undefined) headers.set("x-api-key", ApiKeyAuthentication)

const url = `${baseUrl.replace(/\/+$/, '')}/api/${encodeURIComponent(String(args.projectId))}/classify/v2/${encodeURIComponent(String(args.sampleId))}/raw-data/${encodeURIComponent(String(args.windowIndex))}${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(getSampleDspResponse, await res.json())
};