import { getClientConfig } from "../config/client";
import {
  ACCESS_CODE_PREFIX,
  Azure,
  ModelProvider,
  ServiceProvider,
} from "../constant";
import { ChatMessage, ModelType, useAccessStore, useChatStore } from "../store";
import { ChatGPTApi } from "./platforms/openai";
import { GeminiProApi } from "./platforms/google";
import { ClaudeApi } from "./platforms/anthropic";
export const ROLES = ["system", "user", "assistant"] as const;
export type MessageRole = (typeof ROLES)[number];

export const Models = ["gpt-3.5-turbo", "gpt-4"] as const;
export type ChatModel = ModelType;

export interface MultimodalContent {
  type: "text" | "image_url";
  text?: string;
  image_url?: {
    url: string;
  };
}

export interface RequestMessage {
  role: MessageRole;
  content: string | MultimodalContent[];
}

export interface LLMConfig {
  model: string;
  providerName?: string;
  temperature?: number;
  top_p?: number;
  stream?: boolean;
  presence_penalty?: number;
  frequency_penalty?: number;
}

export interface ChatOptions {
  messages: RequestMessage[];
  config: LLMConfig;

  onUpdate?: (message: string, chunk: string) => void;
  onFinish: (message: string) => void;
  onError?: (err: Error) => void;
  onController?: (controller: AbortController) => void;
}

export interface LLMUsage {
  used: number;
  total: number;
}

export interface LLMModel {
  name: string;
  displayName?: string;
  available: boolean;
  provider: LLMModelProvider;
}

export interface LLMModelProvider {
  id: string;
  providerName: string;
  providerType: string;
}

export abstract class LLMApi {
  abstract chat(options: ChatOptions): Promise<void>;
  abstract usage(): Promise<LLMUsage>;
  abstract models(): Promise<LLMModel[]>;
}

type ProviderName = "openai" | "azure" | "claude" | "palm";

interface Model {
  name: string;
  provider: ProviderName;
  ctxlen: number;
}

interface ChatProvider {
  name: ProviderName;
  apiConfig: {
    baseUrl: string;
    apiKey: string;
    summaryModel: Model;
  };
  models: Model[];

  chat: () => void;
  usage: () => void;
}

export class ClientApi {
  public llm: LLMApi;

  constructor(provider: ModelProvider = ModelProvider.GPT) {
    switch (provider) {
      case ModelProvider.GeminiPro:
        this.llm = new GeminiProApi();
        break;
      case ModelProvider.Claude:
        this.llm = new ClaudeApi();
        break;
      default:
        this.llm = new ChatGPTApi();
    }
  }

  config() {}

  prompts() {}

  masks() {}

  async share(messages: ChatMessage[], avatarUrl: string | null = null) {
    const msgs = messages
      .map((m) => ({
        from: m.role === "user" ? "human" : "gpt",
        value: m.content,
      }))
      .concat([
        {
          from: "human",
          value:
            "Share from [NextChat]: https://github.com/Yidadaa/ChatGPT-Next-Web",
        },
      ]);
    // 敬告二开开发者们，为了开源大模型的发展，请不要修改上述消息，此消息用于后续数据清洗使用
    // Please do not modify this message

    console.log("[Share]", messages, msgs);
    const clientConfig = getClientConfig();
    const proxyUrl = "/sharegpt";
    const rawUrl = "https://sharegpt.com/api/conversations";
    const shareUrl = clientConfig?.isApp ? rawUrl : proxyUrl;
    const res = await fetch(shareUrl, {
      body: JSON.stringify({
        avatarUrl,
        items: msgs,
      }),
      headers: {
        "Content-Type": "application/json",
      },
      method: "POST",
    });

    const resJson = await res.json();
    console.log("[Share]", resJson);
    if (resJson.id) {
      return `https://shareg.pt/${resJson.id}`;
    }
  }
}

export function getHeaders() {
  const accessStore = useAccessStore.getState();
  const chatStore = useChatStore.getState();
  const headers: Record<string, string> = {
    "Content-Type": "application/json",
    Accept: "application/json",
  };

  const clientConfig = getClientConfig();

  function getConfig() {
    const modelConfig = chatStore.currentSession().mask.modelConfig;
    const isGoogle = modelConfig.providerName == ServiceProvider.Google;
    const isAzure = modelConfig.providerName === ServiceProvider.Azure;
    const isAnthropic = modelConfig.providerName === ServiceProvider.Anthropic;
    const isEnabledAccessControl = accessStore.enabledAccessControl();
    const apiKey = isGoogle
      ? accessStore.googleApiKey
      : isAzure
      ? accessStore.azureApiKey
      : isAnthropic
      ? accessStore.anthropicApiKey
      : accessStore.openaiApiKey;
    return { isGoogle, isAzure, isAnthropic, apiKey, isEnabledAccessControl };
  }

  function getAuthHeader(): string {
    return isAzure ? "api-key" : isAnthropic ? "x-api-key" : "Authorization";
  }

  function getBearerToken(apiKey: string, noBearer: boolean = false): string {
    return validString(apiKey)
      ? `${noBearer ? "" : "Bearer "}${apiKey.trim()}`
      : "";
  }

  function validString(x: string): boolean {
    return x?.length > 0;
  }
  const { isGoogle, isAzure, isAnthropic, apiKey, isEnabledAccessControl } =
    getConfig();
  // when using google api in app, not set auth header
  if (isGoogle && clientConfig?.isApp) return headers;

  const authHeader = getAuthHeader();

  const bearerToken = getBearerToken(apiKey, isAzure || isAnthropic);

  if (bearerToken) {
    headers[authHeader] = bearerToken;
  } else if (isEnabledAccessControl && validString(accessStore.accessCode)) {
    headers["Authorization"] = getBearerToken(
      ACCESS_CODE_PREFIX + accessStore.accessCode,
    );
  }

  return headers;
}

export function getClientApi(provider: ServiceProvider): ClientApi {
  switch (provider) {
    case ServiceProvider.Google:
      return new ClientApi(ModelProvider.GeminiPro);
    case ServiceProvider.Anthropic:
      return new ClientApi(ModelProvider.Claude);
    default:
      return new ClientApi(ModelProvider.GPT);
  }
}