Merge 69fcb92a3b into 995bef73de

add: model gpt-5

README.md

@@ -313,12 +313,15 @@ If you want to disable parse settings from url, set this to 1.
 
 To control custom models, use `+` to add a custom model, use `-` to hide a model, use `name=displayName` to customize model name, separated by comma.
 
-User `-all` to disable all default models, `+all` to enable all default models.
+Use `-all` to disable all default models, `+all` to enable all default models.
+Use `-*provider` to disable specified models. 
+Current valid providers: `openai,azure,google,anthropic,baidu,bytedance,alibaba,tencent,moonshot,iflytek,xai,chatglm` and more to come.
 
 For Azure: use `modelName@Azure=deploymentName` to customize model name and deployment name.
 
 > Example: `+gpt-3.5-turbo@Azure=gpt35` will show option `gpt35(Azure)` in model list.
 > If you only can use Azure model, `-all,+gpt-3.5-turbo@Azure=gpt35` will `gpt35(Azure)` the only option in model list.
+> If you don't want to use Azure model, using `-*azure` will prevent Azure models from appearing in the model list.
 
 For ByteDance: use `modelName@bytedance=deploymentName` to customize model name and deployment name.
 

app/client/platforms/openai.ts

@@ -200,6 +200,7 @@ export class ChatGPTApi implements LLMApi {
       options.config.model.startsWith("o1") ||
       options.config.model.startsWith("o3") ||
       options.config.model.startsWith("o4-mini");
+    const isGpt5 =  options.config.model.startsWith("gpt-5");
     if (isDalle3) {
       const prompt = getMessageTextContent(
         options.messages.slice(-1)?.pop() as any,
@@ -230,7 +231,7 @@ export class ChatGPTApi implements LLMApi {
         messages,
         stream: options.config.stream,
         model: modelConfig.model,
-        temperature: !isO1OrO3 ? modelConfig.temperature : 1,
+        temperature: (!isO1OrO3 && !isGpt5) ? modelConfig.temperature : 1,
         presence_penalty: !isO1OrO3 ? modelConfig.presence_penalty : 0,
         frequency_penalty: !isO1OrO3 ? modelConfig.frequency_penalty : 0,
         top_p: !isO1OrO3 ? modelConfig.top_p : 1,
@@ -238,7 +239,13 @@ export class ChatGPTApi implements LLMApi {
         // Please do not ask me why not send max_tokens, no reason, this param is just shit, I dont want to explain anymore.
       };
 
-      if (isO1OrO3) {
+      if (isGpt5) {
+  	// Remove max_tokens if present
+  	delete requestPayload.max_tokens;
+  	// Add max_completion_tokens (or max_completion_tokens if that's what you meant)
+  	requestPayload["max_completion_tokens"] = modelConfig.max_tokens;
+
+      } else if (isO1OrO3) {
         // by default the o1/o3 models will not attempt to produce output that includes markdown formatting
         // manually add "Formatting re-enabled" developer message to encourage markdown inclusion in model responses
         // (https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/reasoning?tabs=python-secure#markdown-output)
@@ -251,8 +258,9 @@ export class ChatGPTApi implements LLMApi {
         requestPayload["max_completion_tokens"] = modelConfig.max_tokens;
       }
 
+
       // add max_tokens to vision model
-      if (visionModel && !isO1OrO3) {
+      if (visionModel && !isO1OrO3 && ! isGpt5) {
         requestPayload["max_tokens"] = Math.max(modelConfig.max_tokens, 4000);
       }
     }

app/constant.ts

@@ -493,6 +493,7 @@ export const VISION_MODEL_REGEXES = [
   /o3/,
   /o4-mini/,
   /grok-4/i,
+  /gpt-5/
 ];
 
 export const EXCLUDE_VISION_MODEL_REGEXES = [/claude-3-5-haiku-20241022/];
@@ -517,6 +518,11 @@ const openaiModels = [
   "gpt-4.1-nano-2025-04-14",
   "gpt-4.5-preview",
   "gpt-4.5-preview-2025-02-27",
+  "gpt-5-chat",
+  "gpt-5-mini",
+  "gpt-5-nano",
+  "gpt-5",
+  "gpt-5-chat-2025-01-01-preview",
   "gpt-4o",
   "gpt-4o-2024-05-13",
   "gpt-4o-2024-08-06",

app/utils/model.ts

@@ -76,6 +76,7 @@ export function collectModelTable(
   // server custom models
   customModels
     .split(",")
+    .map((v) => v.trim())
     .filter((v) => !!v && v.length > 0)
     .forEach((m) => {
       const available = !m.startsWith("-");
@@ -88,6 +89,13 @@ export function collectModelTable(
         Object.values(modelTable).forEach(
           (model) => (model.available = available),
         );
+      } else if (name.startsWith("*")) {
+        const modelId = name.substring(1).toLowerCase();
+        Object.values(modelTable).forEach((model) => {
+          if (model?.provider?.id === modelId) {
+            model.available = available;
+          }
+        });
       } else {
         // 1. find model by name, and set available value
         const [customModelName, customProviderName] = getModelProvider(name);

test/model.test.ts

@@ -0,0 +1,142 @@
+import { collectModelTable } from "@/app/utils/model"
+import { LLMModel,LLMModelProvider } from "@/app/client/api";
+
+describe('collectModelTable', () => {
+  const mockModels: readonly LLMModel[] = [
+    {
+      name: 'gpt-3.5-turbo',
+      available: true,
+      provider: {
+        id: 'openai',
+        providerName: 'OpenAI',
+        providerType: 'openai',
+      } as LLMModelProvider,
+      sorted: 1,
+    },
+    {
+      name: 'gpt-4',
+      available: true,
+      provider: {
+        id: 'openai',
+        providerName: 'OpenAI',
+        providerType: 'openai',
+      } as LLMModelProvider,
+      sorted: 1,
+    },
+    {
+      name: 'gpt-3.5-turbo',
+      available: true,
+      provider: {
+        id: 'azure',
+        providerName: 'Azure',
+        providerType: 'azure',
+      } as LLMModelProvider,
+      sorted: 2,
+    },
+    {
+      name: 'gpt-4',
+      available: true,
+      provider: {
+        id: 'azure',
+        providerName: 'Azure',
+        providerType: 'azure',
+      } as LLMModelProvider,
+      sorted: 2,
+    },
+    {
+      name: 'gemini-pro',
+      available: true,
+      provider: {
+        id: 'google',
+        providerName: 'Google',
+        providerType: 'google',
+      } as LLMModelProvider,
+      sorted: 3,
+    },
+    {
+      name: 'claude-3-haiku-20240307',
+      available: true,
+      provider: {
+        id: 'anthropic',
+        providerName: 'Anthropic',
+        providerType: 'anthropic',
+      } as LLMModelProvider,
+      sorted: 4,
+    },
+    {
+      name: 'grok-beta',
+      available: true,
+      provider: {
+        id: 'xai',
+        providerName: 'XAI',
+        providerType: 'xai',
+      } as LLMModelProvider,
+      sorted: 11,
+    },
+  ];
+
+  test('all models shoule be available', () => {
+    const customModels = '';
+    const result = collectModelTable(mockModels, customModels);
+
+    expect(result['gpt-3.5-turbo@openai'].available).toBe(true);
+    expect(result['gpt-4@openai'].available).toBe(true);
+    expect(result['gpt-3.5-turbo@azure'].available).toBe(true);
+    expect(result['gpt-4@azure'].available).toBe(true);
+    expect(result['gemini-pro@google'].available).toBe(true);
+    expect(result['claude-3-haiku-20240307@anthropic'].available).toBe(true);
+    expect(result['grok-beta@xai'].available).toBe(true);
+  });
+  test('should exclude all models when custom is "-all"', () => {
+    const customModels = '-all';
+    const result = collectModelTable(mockModels, customModels);
+
+    expect(result['gpt-3.5-turbo@openai'].available).toBe(false);
+    expect(result['gpt-4@openai'].available).toBe(false);
+    expect(result['gpt-3.5-turbo@azure'].available).toBe(false);
+    expect(result['gpt-4@azure'].available).toBe(false);
+    expect(result['gemini-pro@google'].available).toBe(false);
+    expect(result['claude-3-haiku-20240307@anthropic'].available).toBe(false);
+    expect(result['grok-beta@xai'].available).toBe(false);
+  });
+
+  test('should exclude all Azure models when custom is "-*azure"', () => {
+    const customModels = '-*azure';
+    const result = collectModelTable(mockModels, customModels);
+
+    expect(result['gpt-3.5-turbo@openai'].available).toBe(true);
+    expect(result['gpt-4@openai'].available).toBe(true);
+    expect(result['gpt-3.5-turbo@azure'].available).toBe(false);
+    expect(result['gpt-4@azure'].available).toBe(false);
+    expect(result['gemini-pro@google'].available).toBe(true);
+    expect(result['claude-3-haiku-20240307@anthropic'].available).toBe(true);
+    expect(result['grok-beta@xai'].available).toBe(true);
+  });
+
+  test('should exclude Google and XAI models when custom is "-*google,-*xai"', () => {
+    const customModels = '-*google,-*xai';
+    const result = collectModelTable(mockModels, customModels);
+
+    expect(result['gpt-3.5-turbo@openai'].available).toBe(true);
+    expect(result['gpt-4@openai'].available).toBe(true);
+    expect(result['gpt-3.5-turbo@azure'].available).toBe(true);
+    expect(result['gpt-4@azure'].available).toBe(true);
+    expect(result['gemini-pro@google'].available).toBe(false);
+    expect(result['claude-3-haiku-20240307@anthropic'].available).toBe(true);
+    expect(result['grok-beta@xai'].available).toBe(false);
+  });
+
+  test('All models except OpenAI should be excluded, and additional models should be added when customized as "-all, +*openai,gpt-4o@azure"', () => {
+    const customModels = '-all,+*openai,gpt-4o@azure';
+    const result = collectModelTable(mockModels, customModels);
+
+    expect(result['gpt-3.5-turbo@openai'].available).toBe(true);
+    expect(result['gpt-4@openai'].available).toBe(true);
+    expect(result['gpt-3.5-turbo@azure'].available).toBe(false);
+    expect(result['gpt-4@azure'].available).toBe(false);
+    expect(result['gemini-pro@google'].available).toBe(false);
+    expect(result['claude-3-haiku-20240307@anthropic'].available).toBe(false);
+    expect(result['grok-beta@xai'].available).toBe(false);
+    expect(result['gpt-4o@azure'].available).toBe(true);
+  });
+});