import { HF_ACCESS_TOKEN, MODELS, OLD_MODELS, TASK_MODEL } from "$env/static/private";
import type { ChatTemplateInput } from "$lib/types/Template";
import { compileTemplate } from "$lib/utils/template";
import { z } from "zod";

type Optional<T, K extends keyof T> = Pick<Partial<T>, K> & Omit<T, K>;

const sagemakerEndpoint = z.object({
	host: z.literal("sagemaker"),
	url: z.string().url(),
	accessKey: z.string().min(1),
	secretKey: z.string().min(1),
	sessionToken: z.string().optional(),
});

const tgiEndpoint = z.object({
	host: z.union([z.literal("tgi"), z.undefined()]),
	url: z.string().url(),
	authorization: z.string().min(1).default(`Bearer ${HF_ACCESS_TOKEN}`),
});

const commonEndpoint = z.object({
	weight: z.number().int().positive().default(1),
});

const endpoint = z.lazy(() =>
	z.union([sagemakerEndpoint.merge(commonEndpoint), tgiEndpoint.merge(commonEndpoint)])
);

const combinedEndpoint = endpoint.transform((data) => {
	if (data.host === "tgi" || data.host === undefined) {
		return tgiEndpoint.merge(commonEndpoint).parse(data);
	} else if (data.host === "sagemaker") {
		return sagemakerEndpoint.merge(commonEndpoint).parse(data);
	} else {
		throw new Error(`Invalid host: ${data.host}`);
	}
});

const modelConfig = z.object({
	/** Used as an identifier in DB */
	id: z.string().optional(),
	/** Used to link to the model page, and for inference */
	name: z.string().min(1),
	displayName: z.string().min(1).optional(),
	description: z.string().min(1).optional(),
	websiteUrl: z.string().url().optional(),
	modelUrl: z.string().url().optional(),
	datasetName: z.string().min(1).optional(),
	datasetUrl: z.string().url().optional(),
	userMessageToken: z.string().default(""),
	userMessageEndToken: z.string().default(""),
	assistantMessageToken: z.string().default(""),
	assistantMessageEndToken: z.string().default(""),
	messageEndToken: z.string().default(""),
	preprompt: z.string().default(""),
	prepromptUrl: z.string().url().optional(),
	chatPromptTemplate: z
		.string()
		.default(
			"{{preprompt}}" +
				"{{#each messages}}" +
				"{{#ifUser}}{{@root.userMessageToken}}{{content}}{{@root.userMessageEndToken}}{{/ifUser}}" +
				"{{#ifAssistant}}{{@root.assistantMessageToken}}{{content}}{{@root.assistantMessageEndToken}}{{/ifAssistant}}" +
				"{{/each}}" +
				"{{assistantMessageToken}}"
		),
	promptExamples: z
		.array(
			z.object({
				title: z.string().min(1),
				prompt: z.string().min(1),
			})
		)
		.optional(),
	endpoints: z.array(combinedEndpoint).optional(),
	parameters: z
		.object({
			temperature: z.number().min(0).max(1),
			truncate: z.number().int().positive(),
			max_new_tokens: z.number().int().positive(),
			stop: z.array(z.string()).optional(),
		})
		.passthrough()
		.optional(),
});

const modelsRaw = z.array(modelConfig).parse(JSON.parse(MODELS));

const processModel = async (m: z.infer<typeof modelConfig>) => ({
	...m,
	userMessageEndToken: m?.userMessageEndToken || m?.messageEndToken,
	assistantMessageEndToken: m?.assistantMessageEndToken || m?.messageEndToken,
	chatPromptRender: compileTemplate<ChatTemplateInput>(m.chatPromptTemplate, m),
	id: m.id || m.name,
	displayName: m.displayName || m.name,
	preprompt: m.prepromptUrl ? await fetch(m.prepromptUrl).then((r) => r.text()) : m.preprompt,
	parameters: { ...m.parameters, stop_sequences: m.parameters?.stop },
});

export const models = await Promise.all(modelsRaw.map(processModel));

// Models that have been deprecated
export const oldModels = OLD_MODELS
	? z
			.array(
				z.object({
					id: z.string().optional(),
					name: z.string().min(1),
					displayName: z.string().min(1).optional(),
				})
			)
			.parse(JSON.parse(OLD_MODELS))
			.map((m) => ({ ...m, id: m.id || m.name, displayName: m.displayName || m.name }))
	: [];

export const defaultModel = models[0];

export const validateModel = (_models: BackendModel[]) => {
	// Zod enum function requires 2 parameters
	return z.enum([_models[0].id, ..._models.slice(1).map((m) => m.id)]);
};

// if `TASK_MODEL` is the name of a model we use it, else we try to parse `TASK_MODEL` as a model config itself
export const smallModel = TASK_MODEL
	? models.find((m) => m.name === TASK_MODEL) ||
	  (await processModel(modelConfig.parse(JSON.parse(TASK_MODEL))))
	: defaultModel;

export type BackendModel = Optional<(typeof models)[0], "preprompt" | "parameters">;
export type Endpoint = z.infer<typeof endpoint>;