feat: add claude and bard

app/store/access.ts

@@ -1,7 +1,7 @@
-import { REMOTE_API_HOST, DEFAULT_MODELS, StoreKey } from "../constant";
+import { REMOTE_API_HOST, StoreKey } from "../constant";
 import { getClientConfig } from "../config/client";
 import { createPersistStore } from "../utils/store";
-import { getAuthHeaders } from "../client/common/auth";
+import { getAuthKey } from "../client/common/auth";
 
 let fetchState = 0; // 0 not fetch, 1 fetching, 2 done
 
@@ -39,7 +39,7 @@ export const useAccessStore = createPersistStore(
         method: "post",
         body: null,
         headers: {
-          ...getAuthHeaders(),
+          Authorization: getAuthKey(),
         },
       })
         .then((res) => res.json())
@@ -48,9 +48,7 @@ export const useAccessStore = createPersistStore(
           set(() => ({ ...res }));
 
           if (res.disableGPT4) {
-            DEFAULT_MODELS.forEach(
-              (m: any) => (m.available = !m.name.startsWith("gpt-4")),
-            );
+            // disable model
           }
         })
         .catch(() => {

app/store/chat.ts

@@ -2,20 +2,9 @@ import { trimTopic } from "../utils";
 
 import Locale, { getLang } from "../locales";
 import { showToast } from "../components/ui-lib";
-import {
-  LLMProvider,
-  MaskConfig,
-  ModelConfig,
-  ModelType,
-  useAppConfig,
-} from "./config";
+import { MaskConfig, useAppConfig } from "./config";
 import { createEmptyMask, Mask } from "./mask";
-import {
-  DEFAULT_INPUT_TEMPLATE,
-  DEFAULT_SYSTEM_TEMPLATE,
-  StoreKey,
-  SUMMARIZE_MODEL,
-} from "../constant";
+import { DEFAULT_INPUT_TEMPLATE, StoreKey } from "../constant";
 import { ChatControllerPool } from "../client/common/controller";
 import { prettyObject } from "../utils/format";
 import { estimateTokenLength } from "../utils/token";
@@ -85,11 +74,6 @@ function createEmptySession(): ChatSession {
   };
 }
 
-function getSummarizeModel(currentModel: string) {
-  // if it is using gpt-* models, force to use 3.5 to summarize
-  return currentModel.startsWith("gpt") ? SUMMARIZE_MODEL : currentModel;
-}
-
 function countMessages(msgs: ChatMessage[]) {
   return msgs.reduce((pre, cur) => pre + estimateTokenLength(cur.content), 0);
 }
@@ -291,6 +275,18 @@ export const useChatStore = createPersistStore(
         return this.extractModelConfig(maskConfig);
       },
 
+      getMaxTokens() {
+        const maskConfig = this.getCurrentMaskConfig();
+
+        if (maskConfig.provider === "openai") {
+          return maskConfig.modelConfig.openai.max_tokens;
+        } else if (maskConfig.provider === "anthropic") {
+          return maskConfig.modelConfig.anthropic.max_tokens_to_sample;
+        }
+
+        return 8192;
+      },
+
       getClient() {
         const appConfig = useAppConfig.getState();
         const currentMaskConfig = get().getCurrentMaskConfig();
@@ -463,7 +459,7 @@ export const useChatStore = createPersistStore(
           : shortTermMemoryStartIndex;
         // and if user has cleared history messages, we should exclude the memory too.
         const contextStartIndex = Math.max(clearContextIndex, memoryStartIndex);
-        const maxTokenThreshold = modelConfig.max_tokens;
+        const maxTokenThreshold = this.getMaxTokens();
 
         // get recent messages as much as possible
         const reversedRecentMessages = [];
@@ -546,7 +542,6 @@ export const useChatStore = createPersistStore(
           });
         }
 
-        const modelConfig = this.getCurrentModelConfig();
         const summarizeIndex = Math.max(
           session.lastSummarizeIndex,
           session.clearContextIndex ?? 0,
@@ -557,7 +552,7 @@ export const useChatStore = createPersistStore(
 
         const historyMsgLength = countMessages(toBeSummarizedMsgs);
 
-        if (historyMsgLength > modelConfig?.max_tokens ?? 4000) {
+        if (historyMsgLength > this.getMaxTokens()) {
           const n = toBeSummarizedMsgs.length;
           toBeSummarizedMsgs = toBeSummarizedMsgs.slice(
             Math.max(0, n - chatConfig.historyMessageCount),

app/store/config.ts

@@ -2,7 +2,6 @@ import { isMacOS } from "../utils";
 import { getClientConfig } from "../config/client";
 import {
   DEFAULT_INPUT_TEMPLATE,
-  DEFAULT_MODELS,
   DEFAULT_SIDEBAR_WIDTH,
   StoreKey,
 } from "../constant";
@@ -10,8 +9,7 @@ import { createPersistStore } from "../utils/store";
 import { OpenAIConfig } from "../client/openai/config";
 import { api } from "../client";
 import { SubmitKey, Theme } from "../typing";
-
-export type ModelType = (typeof DEFAULT_MODELS)[number]["name"];
+import { AnthropicConfig } from "../client/anthropic/config";
 
 export const DEFAULT_CHAT_CONFIG = {
   enableAutoGenerateTitle: true,
@@ -25,17 +23,13 @@ export type ChatConfig = typeof DEFAULT_CHAT_CONFIG;
 
 export const DEFAULT_PROVIDER_CONFIG = {
   openai: OpenAIConfig.provider,
+  anthropic: AnthropicConfig.provider,
   // azure: {
   //   endpoint: "https://api.openai.com",
   //   apiKey: "",
   //   version: "",
   //   ...COMMON_PROVIDER_CONFIG,
   // },
-  // claude: {
-  //   endpoint: "https://api.anthropic.com",
-  //   apiKey: "",
-  //   ...COMMON_PROVIDER_CONFIG,
-  // },
   // google: {
   //   endpoint: "https://api.anthropic.com",
   //   apiKey: "",
@@ -45,6 +39,7 @@ export const DEFAULT_PROVIDER_CONFIG = {
 
 export const DEFAULT_MODEL_CONFIG = {
   openai: OpenAIConfig.model,
+  anthropic: AnthropicConfig.model,
   // azure: {
   //   model: "gpt-3.5-turbo" as string,
   //   summarizeModel: "gpt-3.5-turbo",
@@ -55,15 +50,6 @@ export const DEFAULT_MODEL_CONFIG = {
   //   presence_penalty: 0,
   //   frequency_penalty: 0,
   // },
-  // claude: {
-  //   model: "claude-2",
-  //   summarizeModel: "claude-2",
-  //
-  //   max_tokens_to_sample: 100000,
-  //   temperature: 1,
-  //   top_p: 0.7,
-  //   top_k: 1,
-  // },
   // google: {
   //   model: "chat-bison-001",
   //   summarizeModel: "claude-2",
@@ -125,7 +111,7 @@ export function limitNumber(
 
 export const ModalConfigValidator = {
   model(x: string) {
-    return x as ModelType;
+    return x as string;
   },
   max_tokens(x: number) {
     return limitNumber(x, 0, 100000, 2000);