import {z} from 'zod'

export type EncodingFormat = 'float' | 'base64';

export type InputType = string | Array<number>;

export type Input = InputType | Array<InputType>;

export type OpenAICompatRequest = {encoding_format?: EncodingFormat | undefined, input: Input, model?: (string | null) | undefined, user?: (string | null) | undefined};

export type CreateApiV1EmbeddingsArgs = {body: OpenAICompatRequest};

export type CreateApiV1EmbeddingsOptions = {baseUrl: string, fetch?: typeof fetch | undefined};

export const embedding = z.union([z.array(z.number()), z.string()]);

export const openAICompatEmbedding = z.object({embedding: embedding, index: z.number().int().gte(0), object: z.string()});

export const openAICompatUsage = z.object({prompt_tokens: z.number().int().gte(0), total_tokens: z.number().int().gte(0)});

export const openAICompatResponse = z.object({data: z.array(openAICompatEmbedding), model: z.string(), object: z.string(), usage: openAICompatUsage});

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
};

/**
 * OpenAI compatible route. Returns a 424 status code if the model is not an embedding model.
 * 
 * POST /v1/embeddings
 */
export const createApiV1Embeddings = async (args: CreateApiV1EmbeddingsArgs, options: CreateApiV1EmbeddingsOptions) => {
const {baseUrl, fetch: fetchFn = fetch} = options ?? {}

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

const url = `${baseUrl.replace(/\/+$/, '')}/v1/embeddings${query.size > 0 ? `?${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(openAICompatResponse, await res.json())
};