import {z} from 'zod'

export type GetApiGenerativeAiArgs = {search?: string | undefined};

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

export const getAllAssistantExternal = z.object({assistants: z.array(z.object({_id: z.string().optional(), name: z.string().optional(), assistant_type: z.string().optional(), query_condensation: z.object({instructions_choice: z.string().optional(), custom_instructions: z.string().optional(), messages_to_condensate: z.number().int().optional(), chat_model: z.object({model_name: z.string().optional(), model_id: z.string().optional(), _id: z.string().optional(), name: z.string().optional(), provider: z.string().optional(), model: z.object({_id: z.string().optional(), provider: z.string().optional(), name: z.string().optional(), model_name: z.string().optional()}).optional(), config: z.object({}).optional()}).optional()}).optional(), query_expansion: z.object({instructions_choice: z.string().optional(), custom_instructions: z.string().optional(), messages_to_generate: z.number().int().optional(), llm_model: z.object({model_name: z.string().optional(), model_id: z.string().optional(), _id: z.string().optional(), name: z.string().optional(), provider: z.string().optional(), model: z.object({_id: z.string().optional(), provider: z.string().optional(), name: z.string().optional(), model_name: z.string().optional()}).optional(), config: z.object({}).optional()}).optional()}).optional(), reranking: z.object({algorithm: z.string().optional(), llm_reranking_instructions: z.string().optional(), llm_model: z.object({model_name: z.string().optional(), model_id: z.string().optional(), _id: z.string().optional(), name: z.string().optional(), provider: z.string().optional(), model: z.object({_id: z.string().optional(), provider: z.string().optional(), name: z.string().optional(), model_name: z.string().optional()}).optional(), config: z.object({}).optional()}).optional()}).optional(), answer_generation: z.object({instructions_choice: z.enum(["both", "semantic", "hybrid", "custom"]).optional(), main_instructions: z.string().optional(), formatting_instructions: z.string().optional(), no_document_instructions: z.string().optional(), maximum_answer_length: z.number().int().optional(), llm_model: z.object({model_name: z.string().optional(), model_id: z.string().optional(), _id: z.string().optional(), name: z.string().optional(), provider: z.string().optional(), model: z.object({_id: z.string().optional(), provider: z.string().optional(), name: z.string().optional(), model_name: z.string().optional()}).optional(), config: z.object({}).optional()}).optional()}).optional(), post_processing: z.object({is_activated: z.boolean().optional(), custom_instructions: z.string().optional(), llm_model: z.object({model_name: z.string().optional(), model_id: z.string().optional(), _id: z.string().optional(), name: z.string().optional(), provider: z.string().optional(), model: z.object({_id: z.string().optional(), provider: z.string().optional(), name: z.string().optional(), model_name: z.string().optional()}).optional(), config: z.object({}).optional()}).optional(), always_show_sources: z.boolean().optional(), max_sources_to_show: z.number().int().optional(), surveys: z.object({activation: z.boolean().optional(), survey: z.object({_id: z.string().optional(), name: z.string().optional()}).optional(), instructions: z.string().optional()}).optional(), topic_detection: z.object({activation: z.boolean().optional(), instructions: z.string().optional()}).optional(), auto_eval: z.object({activation: z.boolean().optional()}).optional(), anonymization: z.object({activation: z.boolean().optional(), instructions: z.string().optional()}).optional()}).optional(), answer_formatting: z.object({waiting_messages_for_answer_generation: z.string().optional(), waiting_messages_for_search: z.string().optional(), waiting_messages_for_analysis: z.string().optional()}).optional(), is_archived: z.boolean().optional(), is_shared: z.boolean().optional(), source: z.object({sources: z.array(z.object({name: z.string().optional(), _id: z.string().optional()})).optional()}).optional(), search: z.object({strategy: z.string().optional(), llm_model: z.object({model_id: z.string().optional(), model_name: z.string().optional(), _id: z.string().optional(), name: z.string().optional(), provider: z.string().optional(), model: z.object({_id: z.string().optional(), provider: z.string().optional(), name: z.string().optional(), model_name: z.string().optional()}).optional(), config: z.object({}).optional()}).optional(), custom_instructions: z.string().optional(), is_smart_filtering_activated: z.boolean().optional(), similarity_threshold: z.number().optional(), number_best_results_llm_context: z.number().int().optional(), search_results_per_query: z.number().int().optional(), weights: z.object({semantic: z.number().optional(), keyword: z.number().optional()}).optional()}).optional(), LLM: z.object({model_id: z.string().optional(), model_name: z.string().optional(), reuse_these_models: z.boolean().optional()}).optional(), company: z.object({contact_mail: z.string().optional(), contact_page: z.string().optional(), phone_number: z.string().optional(), location: z.string().optional(), website: z.string().optional(), description: z.string().optional(), name: z.string().optional()}).optional(), tools: z.array(z.object({_id: z.string().optional(), name: z.string().optional()})).optional(), user_id: z.string().optional(), collaborators: z.array(z.string()).optional(), type: z.string().optional(), createdAt: z.string().optional(), updatedAt: z.string().optional(), __v: z.number().int().optional()})).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
};

/**
 * Get all assistants
 * 
 * GET /generative_ai
 */
export const getApiGenerativeAi = async (args: GetApiGenerativeAiArgs, options?: GetApiGenerativeAiOptions) => {
const {baseUrl = "https://apis.smartly.ai", fetch: fetchFn = fetch, Bearer} = options ?? {}

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

if (args.search != null) query.append("search", String(args.search))
if (Bearer !== undefined) headers.set("Authorization", Bearer)

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