import {z} from 'zod'

export type AiAssistantCreateRequest = {name: string, description?: string | undefined, system_prompt?: string | undefined, llm: string, llm_args?: Record<string, never> | undefined, custom_tool_definition?: string | undefined, mcp_servers?: Array<Record<string, never>> | undefined, credential_ids?: Array<string> | undefined, memory_block_id?: string | undefined, notification_email?: string | undefined, history_management?: ('compactification' | 'truncation' | 'semantic_retrieval') | undefined, history_max_chars?: number | undefined, history_recent_chars?: number | undefined, history_retrieval_chars?: number | undefined, allowed_tool_actions?: (Array<string> | null) | undefined, allowed_trigger_types?: (Array<string> | null) | undefined, default_wake_period?: (number | null) | undefined};

export type CreateApiAiAssistantsArgs = {body: AiAssistantCreateRequest};

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

export const aiAssistant = z.object({id: z.string().optional(), name: z.string().optional(), description: z.string().optional(), system_prompt: z.string().optional(), llm: z.string().optional(), llm_args: z.object({}).optional(), status: z.enum(["stopped", "running", "sleeping", "error"]).optional(), custom_tool_definition: z.string().optional(), mcp_servers: z.array(z.object({})).optional(), credential_ids: z.array(z.string()).optional(), memory_block_id: z.string().optional(), notification_email: z.string().optional(), history_management: z.enum(["compactification", "truncation", "semantic_retrieval"]).optional(), history_max_chars: z.number().int().optional(), history_recent_chars: z.number().int().optional(), history_retrieval_chars: z.number().int().optional(), allowed_tool_actions: z.array(z.string()).nullable().optional(), allowed_trigger_types: z.array(z.string()).nullable().optional(), current_chat_session_id: z.string().optional(), wake_count: z.number().int().optional(), last_wake_at: z.string().optional(), last_sleep_at: z.string().optional(), error_message: z.string().optional(), user_id: z.string().optional(), username: z.string().optional(), created_at: z.string().optional(), updated_at: z.string().optional(), is_owner: z.boolean().optional(), user_access_mode: z.string().optional(), forum_count: z.number().int().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
};

/**
 * Create an AI assistant.
 * 
 * POST /ai_assistants
 */
export const createApiAiAssistants = async (args: CreateApiAiAssistantsArgs, options?: CreateApiAiAssistantsOptions) => {
const {baseUrl = "https://h2ogpte.genai.h2o.ai/api/v1", 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 (bearerAuth !== undefined) headers.set('authorization', `Bearer ${bearerAuth}`)

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