test: add unit test for src/store/user/slices/modelList/selectors/keyVaults.ts

Dockerfile

@@ -212,7 +212,7 @@ ENV \
     # Upstage
     UPSTAGE_API_KEY="" UPSTAGE_MODEL_LIST="" \
     # Wenxin
-    WENXIN_ACCESS_KEY="" WENXIN_SECRET_KEY="" WENXIN_MODEL_LIST="" \
+    WENXIN_API_KEY="" WENXIN_MODEL_LIST="" \
     # xAI
     XAI_API_KEY="" XAI_MODEL_LIST="" XAI_PROXY_URL="" \
     # 01.AI

Dockerfile.database

@@ -247,7 +247,7 @@ ENV \
     # Upstage
     UPSTAGE_API_KEY="" UPSTAGE_MODEL_LIST="" \
     # Wenxin
-    WENXIN_ACCESS_KEY="" WENXIN_SECRET_KEY="" WENXIN_MODEL_LIST="" \
+    WENXIN_API_KEY="" WENXIN_MODEL_LIST="" \
     # xAI
     XAI_API_KEY="" XAI_MODEL_LIST="" XAI_PROXY_URL="" \
     # 01.AI

package.json

@@ -111,7 +111,6 @@
     "@aws-sdk/s3-request-presigner": "^3.723.0",
     "@azure/core-rest-pipeline": "1.16.0",
     "@azure/openai": "1.0.0-beta.12",
-    "@baiducloud/qianfan": "^0.1.9",
     "@cfworker/json-schema": "^4.1.0",
     "@clerk/localizations": "^3.9.6",
     "@clerk/nextjs": "^6.10.6",

src/app/(main)/settings/llm/ProviderList/providers.tsx

@@ -27,6 +27,7 @@ import {
   TaichuProviderCard,
   TogetherAIProviderCard,
   UpstageProviderCard,
+  WenxinProviderCard,
   XAIProviderCard,
   ZeroOneProviderCard,
   ZhiPuProviderCard,
@@ -40,7 +41,6 @@ import { useGithubProvider } from './Github';
 import { useHuggingFaceProvider } from './HuggingFace';
 import { useOllamaProvider } from './Ollama';
 import { useOpenAIProvider } from './OpenAI';
-import { useWenxinProvider } from './Wenxin';
 
 export const useProviderList = (): ProviderItem[] => {
   const AzureProvider = useAzureProvider();
@@ -50,7 +50,6 @@ export const useProviderList = (): ProviderItem[] => {
   const CloudflareProvider = useCloudflareProvider();
   const GithubProvider = useGithubProvider();
   const HuggingFaceProvider = useHuggingFaceProvider();
-  const WenxinProvider = useWenxinProvider();
 
   return useMemo(
     () => [
@@ -75,7 +74,7 @@ export const useProviderList = (): ProviderItem[] => {
       UpstageProviderCard,
       XAIProviderCard,
       QwenProviderCard,
-      WenxinProvider,
+      WenxinProviderCard,
       HunyuanProviderCard,
       SparkProviderCard,
       ZhiPuProviderCard,
@@ -99,7 +98,6 @@ export const useProviderList = (): ProviderItem[] => {
       BedrockProvider,
       CloudflareProvider,
       GithubProvider,
-      WenxinProvider,
       HuggingFaceProvider,
     ],
   );

src/config/aiModels/wenxin.ts

@@ -7,7 +7,7 @@ const wenxinChatModels: AIChatModelCard[] = [
       '百度自研的旗舰级大规模⼤语⾔模型，覆盖海量中英文语料，具有强大的通用能力，可满足绝大部分对话问答、创作生成、插件应用场景要求；支持自动对接百度搜索插件，保障问答信息时效。',
     displayName: 'ERNIE 3.5 8K',
     enabled: true,
-    id: 'ERNIE-3.5-8K',
+    id: 'ernie-3.5-8k',
     pricing: {
       currency: 'CNY',
       input: 0.8,
@@ -20,7 +20,7 @@ const wenxinChatModels: AIChatModelCard[] = [
     description:
       '百度自研的旗舰级大规模⼤语⾔模型，覆盖海量中英文语料，具有强大的通用能力，可满足绝大部分对话问答、创作生成、插件应用场景要求；支持自动对接百度搜索插件，保障问答信息时效。',
     displayName: 'ERNIE 3.5 8K Preview',
-    id: 'ERNIE-3.5-8K-Preview',
+    id: 'ernie-3.5-8k-preview',
     pricing: {
       currency: 'CNY',
       input: 0.8,
@@ -34,7 +34,7 @@ const wenxinChatModels: AIChatModelCard[] = [
       '百度自研的旗舰级大规模⼤语⾔模型，覆盖海量中英文语料，具有强大的通用能力，可满足绝大部分对话问答、创作生成、插件应用场景要求；支持自动对接百度搜索插件，保障问答信息时效。',
     displayName: 'ERNIE 3.5 128K',
     enabled: true,
-    id: 'ERNIE-3.5-128K',
+    id: 'ernie-3.5-128k',
     pricing: {
       currency: 'CNY',
       input: 0.8,
@@ -48,7 +48,7 @@ const wenxinChatModels: AIChatModelCard[] = [
       '百度自研的旗舰级超大规模⼤语⾔模型，相较ERNIE 3.5实现了模型能力全面升级，广泛适用于各领域复杂任务场景；支持自动对接百度搜索插件，保障问答信息时效。',
     displayName: 'ERNIE 4.0 8K',
     enabled: true,
-    id: 'ERNIE-4.0-8K-Latest',
+    id: 'ernie-4.0-8k-latest',
     pricing: {
       currency: 'CNY',
       input: 30,
@@ -61,7 +61,7 @@ const wenxinChatModels: AIChatModelCard[] = [
     description:
       '百度自研的旗舰级超大规模⼤语⾔模型，相较ERNIE 3.5实现了模型能力全面升级，广泛适用于各领域复杂任务场景；支持自动对接百度搜索插件，保障问答信息时效。',
     displayName: 'ERNIE 4.0 8K Preview',
-    id: 'ERNIE-4.0-8K-Preview',
+    id: 'ernie-4.0-8k-preview',
     pricing: {
       currency: 'CNY',
       input: 30,
@@ -75,7 +75,7 @@ const wenxinChatModels: AIChatModelCard[] = [
       '百度自研的旗舰级超大规模⼤语⾔模型，综合效果表现出色，广泛适用于各领域复杂任务场景；支持自动对接百度搜索插件，保障问答信息时效。相较于ERNIE 4.0在性能表现上更优秀',
     displayName: 'ERNIE 4.0 Turbo 8K',
     enabled: true,
-    id: 'ERNIE-4.0-Turbo-8K-Latest',
+    id: 'ernie-4.0-turbo-8k-latest',
     pricing: {
       currency: 'CNY',
       input: 20,
@@ -89,7 +89,7 @@ const wenxinChatModels: AIChatModelCard[] = [
       '百度自研的旗舰级超大规模⼤语⾔模型，综合效果表现出色，广泛适用于各领域复杂任务场景；支持自动对接百度搜索插件，保障问答信息时效。相较于ERNIE 4.0在性能表现上更优秀',
     displayName: 'ERNIE 4.0 Turbo 128K',
     enabled: true,
-    id: 'ERNIE-4.0-Turbo-128K',
+    id: 'ernie-4.0-turbo-128k',
     pricing: {
       currency: 'CNY',
       input: 20,
@@ -102,7 +102,7 @@ const wenxinChatModels: AIChatModelCard[] = [
     description:
       '百度自研的旗舰级超大规模⼤语⾔模型，综合效果表现出色，广泛适用于各领域复杂任务场景；支持自动对接百度搜索插件，保障问答信息时效。相较于ERNIE 4.0在性能表现上更优秀',
     displayName: 'ERNIE 4.0 Turbo 8K Preview',
-    id: 'ERNIE-4.0-Turbo-8K-Preview',
+    id: 'ernie-4.0-turbo-8k-preview',
     pricing: {
       currency: 'CNY',
       input: 20,
@@ -116,7 +116,7 @@ const wenxinChatModels: AIChatModelCard[] = [
       '百度自研的轻量级大语言模型，兼顾优异的模型效果与推理性能，效果比ERNIE Lite更优，适合低算力AI加速卡推理使用。',
     displayName: 'ERNIE Lite Pro 128K',
     enabled: true,
-    id: 'ERNIE-Lite-Pro-128K',
+    id: 'ernie-lite-pro-128k',
     pricing: {
       currency: 'CNY',
       input: 0.2,
@@ -130,7 +130,7 @@ const wenxinChatModels: AIChatModelCard[] = [
       '百度2024年最新发布的自研高性能大语言模型，通用能力优异，效果比ERNIE Speed更优，适合作为基座模型进行精调，更好地处理特定场景问题，同时具备极佳的推理性能。',
     displayName: 'ERNIE Speed Pro 128K',
     enabled: true,
-    id: 'ERNIE-Speed-Pro-128K',
+    id: 'ernie-speed-pro-128k',
     pricing: {
       currency: 'CNY',
       input: 0.3,
@@ -143,7 +143,7 @@ const wenxinChatModels: AIChatModelCard[] = [
     description:
       '百度2024年最新发布的自研高性能大语言模型，通用能力优异，适合作为基座模型进行精调，更好地处理特定场景问题，同时具备极佳的推理性能。',
     displayName: 'ERNIE Speed 128K',
-    id: 'ERNIE-Speed-128K',
+    id: 'ernie-speed-128k',
     pricing: {
       currency: 'CNY',
       input: 0,
@@ -156,7 +156,7 @@ const wenxinChatModels: AIChatModelCard[] = [
     description:
       '百度自研的垂直场景大语言模型，适合游戏NPC、客服对话、对话角色扮演等应用场景，人设风格更为鲜明、一致，指令遵循能力更强，推理性能更优。',
     displayName: 'ERNIE Character 8K',
-    id: 'ERNIE-Character-8K',
+    id: 'ernie-character-8k',
     pricing: {
       currency: 'CNY',
       input: 4,

src/config/llm.ts

@@ -64,8 +64,7 @@ export const getLLMConfig = () => {
       AWS_SESSION_TOKEN: z.string().optional(),
 
       ENABLED_WENXIN: z.boolean(),
-      WENXIN_ACCESS_KEY: z.string().optional(),
-      WENXIN_SECRET_KEY: z.string().optional(),
+      WENXIN_API_KEY: z.string().optional(),
 
       ENABLED_OLLAMA: z.boolean(),
 
@@ -186,9 +185,8 @@ export const getLLMConfig = () => {
       AWS_SECRET_ACCESS_KEY: process.env.AWS_SECRET_ACCESS_KEY,
       AWS_SESSION_TOKEN: process.env.AWS_SESSION_TOKEN,
 
-      ENABLED_WENXIN: !!process.env.WENXIN_ACCESS_KEY && !!process.env.WENXIN_SECRET_KEY,
-      WENXIN_ACCESS_KEY: process.env.WENXIN_ACCESS_KEY,
-      WENXIN_SECRET_KEY: process.env.WENXIN_SECRET_KEY,
+      ENABLED_WENXIN: !!process.env.WENXIN_API_KEY,
+      WENXIN_API_KEY: process.env.WENXIN_API_KEY,
 
       ENABLED_OLLAMA: process.env.ENABLED_OLLAMA !== '0',