update

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@kevisual/ai",
-  "version": "0.0.16",
+  "version": "0.0.17",
   "description": "AI Center Services",
   "main": "index.js",
   "basename": "/root/ai-center-services",
@@ -53,40 +53,27 @@
     }
   },
   "devDependencies": {
-    "@kevisual/code-center-module": "0.0.24",
+    "@kevisual/router": "0.0.36",
-    "@kevisual/mark": "0.0.7",
-    "@kevisual/router": "0.0.33",
     "@kevisual/types": "^0.0.10",
     "@kevisual/use-config": "^1.0.21",
-    "@types/bun": "^1.3.3",
+    "@types/bun": "^1.3.4",
     "@types/crypto-js": "^4.2.2",
     "@types/formidable": "^3.4.6",
-    "@types/lodash-es": "^4.17.12",
     "@types/node": "^24.10.1",
-    "@vitejs/plugin-basic-ssl": "^2.1.0",
-    "cookie": "^1.1.1",
     "cross-env": "^10.1.0",
     "crypto-js": "^4.2.0",
     "dayjs": "^1.11.19",
     "dotenv": "^17.2.3",
     "formidable": "^3.5.4",
-    "ioredis": "^5.8.2",
-    "json5": "^2.2.3",
-    "lodash-es": "^4.17.21",
     "openai": "6.10.0",
     "pm2": "^6.0.14",
     "rimraf": "^6.1.2",
-    "rollup": "^4.53.3",
-    "rollup-plugin-dts": "^6.3.0",
-    "sequelize": "^6.37.7",
-    "tape": "^5.9.0",
-    "tiktoken": "^1.0.22",
     "typescript": "^5.9.3",
     "vite": "^7.2.6"
   },
   "dependencies": {
     "@kevisual/logger": "^0.0.4",
     "@kevisual/permission": "^0.0.3",
-    "@kevisual/query": "^0.0.30"
+    "@kevisual/query": "^0.0.31"
   }
 }

src/provider/chat-adapter/kevisual.ts

@@ -0,0 +1,14 @@
+import { BaseChat, BaseChatOptions } from '../core/chat.ts';
+
+export type KevisualOptions = Partial<BaseChatOptions>;
+
+/**
+ * Kevisual Chat Adapter
+ */
+export class Kevisual extends BaseChat {
+  static BASE_URL = 'https://newapi.kevisual.cn/v1/';
+  constructor(options: KevisualOptions) {
+    const baseURL = options.baseURL || Kevisual.BASE_URL;
+    super({ ...(options as BaseChatOptions), baseURL: baseURL });
+  }
+}

src/provider/chat.ts

@@ -10,6 +10,7 @@ import { ModelScope } from './chat-adapter/model-scope.ts';
 import { BailianChat } from './chat-adapter/dashscope.ts';
 import { Zhipu } from './chat-adapter/zhipu.ts';
 import { Kimi } from './chat-adapter/kimi.ts';
+import { Kevisual } from './chat-adapter/kevisual.ts';
 
 import { ChatMessage } from './core/type.ts';
 
@@ -25,16 +26,19 @@ export {
   Zhipu,
   Kimi,
   ChatMessage,
+  Kevisual,
 }
-export const OllamaProvider = Ollama;
+export class OllamaProvider extends Ollama { }
-export const SiliconFlowProvider = SiliconFlow;
+export class SiliconFlowProvider extends SiliconFlow { }
-export const CustomProvider = Custom;
+export class CustomProvider extends Custom { }
-export const VolcesProvider = Volces;
+export class VolcesProvider extends Volces { }
-export const DeepSeekProvider = DeepSeek;
+export class DeepSeekProvider extends DeepSeek { }
-export const ModelScopeProvider = ModelScope;
+export class ModelScopeProvider extends ModelScope { }
-export const BailianProvider = BailianChat;
+export class BailianProvider extends BailianChat { }
-export const ZhipuProvider = Zhipu;
+export class ZhipuProvider extends Zhipu { }
-export const KimiProvider = Kimi;
+export class KimiProvider extends Kimi { }
+export class KevisualProvider extends Kevisual { }
+
 
 export const ChatProviderMap = {
   Ollama: OllamaProvider,

src/provider/utils/token.ts

@@ -1,34 +0,0 @@
-import { encoding_for_model, get_encoding } from 'tiktoken';
-
-
-const MODEL_TO_ENCODING = {
-  'gpt-4': 'cl100k_base',
-  'gpt-4-turbo': 'cl100k_base',
-  'gpt-3.5-turbo': 'cl100k_base',
-  'text-embedding-ada-002': 'cl100k_base',
-  'text-davinci-002': 'p50k_base',
-  'text-davinci-003': 'p50k_base',
-} as const;
-
-export function numTokensFromString(text: string, model: keyof typeof MODEL_TO_ENCODING = 'gpt-3.5-turbo'): number {
-  try {
-    // 对于特定模型使用专门的编码器
-    const encoder = encoding_for_model(model);
-    const tokens = encoder.encode(text);
-    const tokenCount = tokens.length;
-    encoder.free(); // 释放编码器
-    return tokenCount;
-  } catch (error) {
-    try {
-      // 如果模型特定的编码器失败，尝试使用基础编码器
-      const encoder = get_encoding(MODEL_TO_ENCODING[model]);
-      const tokens = encoder.encode(text);
-      const tokenCount = tokens.length;
-      encoder.free(); // 释放编码器
-      return tokenCount;
-    } catch (error) {
-      // 如果编码失败，使用一个粗略的估计：平均每个字符0.25个token
-      return Math.ceil(text.length * 0.25);
-    }
-  }
-}