🎭 feat: Override Custom Endpoint Schema with Specified Params Endpoint (#11788)

* 🔧 refactor: Simplify payload parsing and enhance getSaveOptions logic

- Removed unused bedrockInputSchema from payloadParser, streamlining the function.
- Updated payloadParser to handle optional chaining for model parameters.
- Enhanced getSaveOptions to ensure runOptions defaults to an empty object if parsing fails, improving robustness.
- Adjusted the assignment of maxContextTokens to use the instance variable for consistency.

* 🔧 fix: Update maxContextTokens assignment logic in initializeAgent function

- Enhanced the maxContextTokens assignment to allow for user-defined values, ensuring it defaults to a calculated value only when not provided or invalid. This change improves flexibility in agent initialization.

* 🧪 test: Add unit tests for initializeAgent function

- Introduced comprehensive unit tests for the initializeAgent function, focusing on maxContextTokens behavior.
- Tests cover scenarios for user-defined values, fallback calculations, and edge cases such as zero and negative values, enhancing overall test coverage and reliability of agent initialization logic.

* refactor: default params Endpoint Configuration Handling

- Integrated `getEndpointsConfig` to fetch endpoint configurations, allowing for dynamic handling of `defaultParamsEndpoint`.
- Updated `buildEndpointOption` to pass `defaultParamsEndpoint` to `parseCompactConvo`, ensuring correct parameter handling based on endpoint type.
- Added comprehensive unit tests for `buildDefaultConvo` and `cleanupPreset` to validate behavior with `defaultParamsEndpoint`, covering various scenarios and edge cases.
- Refactored related hooks and utility functions to support the new configuration structure, improving overall flexibility and maintainability.

* refactor: Centralize defaultParamsEndpoint retrieval

- Introduced `getDefaultParamsEndpoint` function to streamline the retrieval of `defaultParamsEndpoint` across various hooks and middleware.
- Updated multiple files to utilize the new function, enhancing code consistency and maintainability.
- Removed redundant logic for fetching `defaultParamsEndpoint`, simplifying the codebase.

client/src/hooks/Chat/useAddedResponse.ts

@@ -1,7 +1,12 @@
 import { useCallback } from 'react';
 import { useRecoilValue } from 'recoil';
 import { useGetModelsQuery } from 'librechat-data-provider/react-query';
-import { getEndpointField, LocalStorageKeys, isAssistantsEndpoint } from 'librechat-data-provider';
+import {
+  getEndpointField,
+  LocalStorageKeys,
+  isAssistantsEndpoint,
+  getDefaultParamsEndpoint,
+} from 'librechat-data-provider';
 import type { TEndpointsConfig, EModelEndpoint, TConversation } from 'librechat-data-provider';
 import type { AssistantListItem, NewConversationParams } from '~/common';
 import useAssistantListMap from '~/hooks/Assistants/useAssistantListMap';
@@ -84,11 +89,13 @@ export default function useAddedResponse() {
       }
 
       const models = modelsConfig?.[defaultEndpoint ?? ''] ?? [];
+      const defaultParamsEndpoint = getDefaultParamsEndpoint(endpointsConfig, defaultEndpoint);
       newConversation = buildDefaultConvo({
         conversation: newConversation,
         lastConversationSetup: preset as TConversation,
         endpoint: defaultEndpoint ?? ('' as EModelEndpoint),
         models,
+        defaultParamsEndpoint,
       });
 
       if (preset?.title != null && preset.title !== '') {

client/src/hooks/Chat/useChatFunctions.ts

@@ -13,6 +13,7 @@ import {
   parseCompactConvo,
   replaceSpecialVars,
   isAssistantsEndpoint,
+  getDefaultParamsEndpoint,
 } from 'librechat-data-provider';
 import type {
   TMessage,
@@ -173,12 +174,14 @@ export default function useChatFunctions({
     const startupConfig = queryClient.getQueryData<TStartupConfig>([QueryKeys.startupConfig]);
     const endpointType = getEndpointField(endpointsConfig, endpoint, 'type');
     const iconURL = conversation?.iconURL;
+    const defaultParamsEndpoint = getDefaultParamsEndpoint(endpointsConfig, endpoint);
 
     /** This becomes part of the `endpointOption` */
     const convo = parseCompactConvo({
       endpoint: endpoint as EndpointSchemaKey,
       endpointType: endpointType as EndpointSchemaKey,
       conversation: conversation ?? {},
+      defaultParamsEndpoint,
     });
 
     const { modelDisplayLabel } = endpointsConfig?.[endpoint ?? ''] ?? {};

client/src/hooks/Conversations/useDefaultConvo.ts

@@ -1,5 +1,5 @@
-import { excludedKeys } from 'librechat-data-provider';
 import { useGetModelsQuery } from 'librechat-data-provider/react-query';
+import { excludedKeys, getDefaultParamsEndpoint } from 'librechat-data-provider';
 import type {
   TEndpointsConfig,
   TModelsConfig,
@@ -47,11 +47,14 @@ const useDefaultConvo = () => {
       }
     }
 
+    const defaultParamsEndpoint = getDefaultParamsEndpoint(endpointsConfig, endpoint);
+
     const defaultConvo = buildDefaultConvo({
       conversation: conversation as TConversation,
       endpoint,
       lastConversationSetup: preset as TConversation,
       models,
+      defaultParamsEndpoint,
     });
 
     if (!cleanOutput) {

client/src/hooks/Conversations/useGenerateConvo.ts

@@ -1,7 +1,12 @@
 import { useRecoilValue } from 'recoil';
 import { useCallback, useRef, useEffect } from 'react';
 import { useGetModelsQuery } from 'librechat-data-provider/react-query';
-import { getEndpointField, LocalStorageKeys, isAssistantsEndpoint } from 'librechat-data-provider';
+import {
+  getEndpointField,
+  LocalStorageKeys,
+  isAssistantsEndpoint,
+  getDefaultParamsEndpoint,
+} from 'librechat-data-provider';
 import type {
   TEndpointsConfig,
   EModelEndpoint,
@@ -117,11 +122,13 @@ const useGenerateConvo = ({
       }
 
       const models = modelsConfig?.[defaultEndpoint ?? ''] ?? [];
+      const defaultParamsEndpoint = getDefaultParamsEndpoint(endpointsConfig, defaultEndpoint);
       conversation = buildDefaultConvo({
         conversation,
         lastConversationSetup: preset as TConversation,
         endpoint: defaultEndpoint ?? ('' as EModelEndpoint),
         models,
+        defaultParamsEndpoint,
       });
 
       if (preset?.title != null && preset.title !== '') {

client/src/hooks/Conversations/useNavigateToConvo.tsx

@@ -2,7 +2,13 @@ import { useCallback } from 'react';
 import { useSetRecoilState } from 'recoil';
 import { useNavigate } from 'react-router-dom';
 import { useQueryClient } from '@tanstack/react-query';
-import { QueryKeys, Constants, dataService, getEndpointField } from 'librechat-data-provider';
+import {
+  QueryKeys,
+  Constants,
+  dataService,
+  getEndpointField,
+  getDefaultParamsEndpoint,
+} from 'librechat-data-provider';
 import type {
   TEndpointsConfig,
   TStartupConfig,
@@ -106,11 +112,13 @@ const useNavigateToConvo = (index = 0) => {
 
       const models = modelsConfig?.[defaultEndpoint ?? ''] ?? [];
 
+      const defaultParamsEndpoint = getDefaultParamsEndpoint(endpointsConfig, defaultEndpoint);
       convo = buildDefaultConvo({
         models,
         conversation,
         endpoint: defaultEndpoint,
         lastConversationSetup: conversation,
+        defaultParamsEndpoint,
       });
     }
     clearAllConversations(true);

client/src/hooks/useNewConvo.ts

@@ -14,6 +14,7 @@ import {
   LocalStorageKeys,
   isEphemeralAgentId,
   isAssistantsEndpoint,
+  getDefaultParamsEndpoint,
 } from 'librechat-data-provider';
 import type {
   TPreset,
@@ -191,11 +192,13 @@ const useNewConvo = (index = 0) => {
           }
 
           const models = modelsConfig?.[defaultEndpoint] ?? [];
+          const defaultParamsEndpoint = getDefaultParamsEndpoint(endpointsConfig, defaultEndpoint);
           conversation = buildDefaultConvo({
             conversation,
             lastConversationSetup: activePreset as TConversation,
             endpoint: defaultEndpoint,
             models,
+            defaultParamsEndpoint,
           });
         }
 

client/src/utils/__tests__/buildDefaultConvo.test.ts

@@ -0,0 +1,202 @@
+import { EModelEndpoint } from 'librechat-data-provider';
+import type { TConversation } from 'librechat-data-provider';
+import buildDefaultConvo from '../buildDefaultConvo';
+
+jest.mock('../localStorage', () => ({
+  getLocalStorageItems: jest.fn(() => ({
+    lastSelectedModel: {},
+    lastSelectedTools: [],
+    lastConversationSetup: {},
+  })),
+}));
+
+const baseConversation: TConversation = {
+  conversationId: 'test-convo-id',
+  title: 'Test Conversation',
+  createdAt: '2024-01-01T00:00:00Z',
+  updatedAt: '2024-01-01T00:00:00Z',
+  endpoint: null,
+};
+
+describe('buildDefaultConvo - defaultParamsEndpoint', () => {
+  describe('custom endpoint with defaultParamsEndpoint: anthropic', () => {
+    const models = ['anthropic/claude-opus-4.5', 'anthropic/claude-sonnet-4'];
+
+    it('should preserve maxOutputTokens from model spec preset', () => {
+      const preset: TConversation = {
+        ...baseConversation,
+        endpoint: 'AnthropicClaude' as EModelEndpoint,
+        endpointType: EModelEndpoint.custom,
+        model: 'anthropic/claude-opus-4.5',
+        temperature: 0.7,
+        maxOutputTokens: 8192,
+        topP: 0.9,
+        maxContextTokens: 50000,
+      };
+
+      const result = buildDefaultConvo({
+        models,
+        conversation: baseConversation,
+        endpoint: 'AnthropicClaude' as EModelEndpoint,
+        lastConversationSetup: preset,
+        defaultParamsEndpoint: EModelEndpoint.anthropic,
+      });
+
+      expect(result.maxOutputTokens).toBe(8192);
+      expect(result.topP).toBe(0.9);
+      expect(result.temperature).toBe(0.7);
+      expect(result.maxContextTokens).toBe(50000);
+      expect(result.model).toBe('anthropic/claude-opus-4.5');
+    });
+
+    it('should strip maxOutputTokens without defaultParamsEndpoint', () => {
+      const preset: TConversation = {
+        ...baseConversation,
+        endpoint: 'AnthropicClaude' as EModelEndpoint,
+        endpointType: EModelEndpoint.custom,
+        model: 'anthropic/claude-opus-4.5',
+        temperature: 0.7,
+        maxOutputTokens: 8192,
+      };
+
+      const result = buildDefaultConvo({
+        models,
+        conversation: baseConversation,
+        endpoint: 'AnthropicClaude' as EModelEndpoint,
+        lastConversationSetup: preset,
+      });
+
+      expect(result.maxOutputTokens).toBeUndefined();
+      expect(result.temperature).toBe(0.7);
+    });
+
+    it('should strip OpenAI-specific fields when using anthropic params', () => {
+      const preset: TConversation = {
+        ...baseConversation,
+        endpoint: 'AnthropicClaude' as EModelEndpoint,
+        endpointType: EModelEndpoint.custom,
+        model: 'anthropic/claude-opus-4.5',
+        max_tokens: 4096,
+        top_p: 0.9,
+        presence_penalty: 0.5,
+        frequency_penalty: 0.3,
+      };
+
+      const result = buildDefaultConvo({
+        models,
+        conversation: baseConversation,
+        endpoint: 'AnthropicClaude' as EModelEndpoint,
+        lastConversationSetup: preset,
+        defaultParamsEndpoint: EModelEndpoint.anthropic,
+      });
+
+      expect(result.max_tokens).toBeUndefined();
+      expect(result.top_p).toBeUndefined();
+      expect(result.presence_penalty).toBeUndefined();
+      expect(result.frequency_penalty).toBeUndefined();
+    });
+  });
+
+  describe('custom endpoint without defaultParamsEndpoint (OpenAI default)', () => {
+    const models = ['gpt-4o', 'gpt-4.1'];
+
+    it('should preserve OpenAI fields and strip anthropic fields', () => {
+      const preset: TConversation = {
+        ...baseConversation,
+        endpoint: 'MyOpenRouterEndpoint' as EModelEndpoint,
+        endpointType: EModelEndpoint.custom,
+        model: 'gpt-4o',
+        temperature: 0.7,
+        max_tokens: 4096,
+        top_p: 0.9,
+        maxOutputTokens: 8192,
+      };
+
+      const result = buildDefaultConvo({
+        models,
+        conversation: baseConversation,
+        endpoint: 'MyOpenRouterEndpoint' as EModelEndpoint,
+        lastConversationSetup: preset,
+      });
+
+      expect(result.max_tokens).toBe(4096);
+      expect(result.top_p).toBe(0.9);
+      expect(result.temperature).toBe(0.7);
+      expect(result.maxOutputTokens).toBeUndefined();
+    });
+  });
+
+  describe('custom endpoint with defaultParamsEndpoint: google', () => {
+    const models = ['gemini-pro', 'gemini-1.5-pro'];
+
+    it('should preserve Google-specific fields', () => {
+      const preset: TConversation = {
+        ...baseConversation,
+        endpoint: 'MyGoogleEndpoint' as EModelEndpoint,
+        endpointType: EModelEndpoint.custom,
+        model: 'gemini-pro',
+        temperature: 0.7,
+        maxOutputTokens: 8192,
+        topP: 0.9,
+        topK: 40,
+      };
+
+      const result = buildDefaultConvo({
+        models,
+        conversation: baseConversation,
+        endpoint: 'MyGoogleEndpoint' as EModelEndpoint,
+        lastConversationSetup: preset,
+        defaultParamsEndpoint: EModelEndpoint.google,
+      });
+
+      expect(result.maxOutputTokens).toBe(8192);
+      expect(result.topP).toBe(0.9);
+      expect(result.topK).toBe(40);
+    });
+  });
+
+  describe('cross-endpoint field isolation', () => {
+    it('should not carry bedrock region to a custom endpoint', () => {
+      const preset: TConversation = {
+        ...baseConversation,
+        endpoint: 'MyChatEndpoint' as EModelEndpoint,
+        endpointType: EModelEndpoint.custom,
+        model: 'gpt-4o',
+        temperature: 0.7,
+        region: 'us-east-1',
+      };
+
+      const result = buildDefaultConvo({
+        models: ['gpt-4o'],
+        conversation: baseConversation,
+        endpoint: 'MyChatEndpoint' as EModelEndpoint,
+        lastConversationSetup: preset,
+      });
+
+      expect(result.region).toBeUndefined();
+      expect(result.temperature).toBe(0.7);
+    });
+
+    it('should not carry bedrock region even with anthropic defaultParamsEndpoint', () => {
+      const preset: TConversation = {
+        ...baseConversation,
+        endpoint: 'MyChatEndpoint' as EModelEndpoint,
+        endpointType: EModelEndpoint.custom,
+        model: 'claude-3-opus',
+        region: 'us-east-1',
+        maxOutputTokens: 8192,
+      };
+
+      const result = buildDefaultConvo({
+        models: ['claude-3-opus'],
+        conversation: baseConversation,
+        endpoint: 'MyChatEndpoint' as EModelEndpoint,
+        lastConversationSetup: preset,
+        defaultParamsEndpoint: EModelEndpoint.anthropic,
+      });
+
+      expect(result.region).toBeUndefined();
+      expect(result.maxOutputTokens).toBe(8192);
+    });
+  });
+});

client/src/utils/__tests__/cleanupPreset.integration.test.ts

@@ -0,0 +1,119 @@
+import { EModelEndpoint } from 'librechat-data-provider';
+import cleanupPreset from '../cleanupPreset';
+
+/**
+ * Integration tests for cleanupPreset — NO mocks.
+ * Uses the real parseConvo to verify actual schema behavior
+ * with defaultParamsEndpoint for custom endpoints.
+ */
+describe('cleanupPreset - real parsing with defaultParamsEndpoint', () => {
+  it('should preserve maxOutputTokens when defaultParamsEndpoint is anthropic', () => {
+    const preset = {
+      presetId: 'test-id',
+      title: 'Claude Opus',
+      endpoint: 'AnthropicClaude',
+      endpointType: EModelEndpoint.custom,
+      model: 'anthropic/claude-opus-4.5',
+      temperature: 0.7,
+      maxOutputTokens: 8192,
+      topP: 0.9,
+      maxContextTokens: 50000,
+    };
+
+    const result = cleanupPreset({
+      preset,
+      defaultParamsEndpoint: EModelEndpoint.anthropic,
+    });
+
+    expect(result.maxOutputTokens).toBe(8192);
+    expect(result.topP).toBe(0.9);
+    expect(result.temperature).toBe(0.7);
+    expect(result.maxContextTokens).toBe(50000);
+    expect(result.model).toBe('anthropic/claude-opus-4.5');
+  });
+
+  it('should strip maxOutputTokens without defaultParamsEndpoint (OpenAI schema)', () => {
+    const preset = {
+      presetId: 'test-id',
+      title: 'GPT Custom',
+      endpoint: 'MyOpenRouter',
+      endpointType: EModelEndpoint.custom,
+      model: 'gpt-4o',
+      temperature: 0.7,
+      maxOutputTokens: 8192,
+      max_tokens: 4096,
+    };
+
+    const result = cleanupPreset({ preset });
+
+    expect(result.maxOutputTokens).toBeUndefined();
+    expect(result.max_tokens).toBe(4096);
+    expect(result.temperature).toBe(0.7);
+  });
+
+  it('should strip OpenAI-specific fields when using anthropic params', () => {
+    const preset = {
+      presetId: 'test-id',
+      title: 'Claude Custom',
+      endpoint: 'AnthropicClaude',
+      endpointType: EModelEndpoint.custom,
+      model: 'anthropic/claude-3-opus',
+      max_tokens: 4096,
+      top_p: 0.9,
+      presence_penalty: 0.5,
+      frequency_penalty: 0.3,
+      temperature: 0.7,
+    };
+
+    const result = cleanupPreset({
+      preset,
+      defaultParamsEndpoint: EModelEndpoint.anthropic,
+    });
+
+    expect(result.max_tokens).toBeUndefined();
+    expect(result.top_p).toBeUndefined();
+    expect(result.presence_penalty).toBeUndefined();
+    expect(result.frequency_penalty).toBeUndefined();
+    expect(result.temperature).toBe(0.7);
+  });
+
+  it('should not carry bedrock region to custom endpoint', () => {
+    const preset = {
+      presetId: 'test-id',
+      title: 'Custom',
+      endpoint: 'MyEndpoint',
+      endpointType: EModelEndpoint.custom,
+      model: 'gpt-4o',
+      temperature: 0.7,
+      region: 'us-east-1',
+    };
+
+    const result = cleanupPreset({ preset });
+
+    expect(result.region).toBeUndefined();
+    expect(result.temperature).toBe(0.7);
+  });
+
+  it('should preserve Google-specific fields when defaultParamsEndpoint is google', () => {
+    const preset = {
+      presetId: 'test-id',
+      title: 'Gemini Custom',
+      endpoint: 'MyGoogleEndpoint',
+      endpointType: EModelEndpoint.custom,
+      model: 'gemini-pro',
+      temperature: 0.7,
+      maxOutputTokens: 8192,
+      topP: 0.9,
+      topK: 40,
+    };
+
+    const result = cleanupPreset({
+      preset,
+      defaultParamsEndpoint: EModelEndpoint.google,
+    });
+
+    expect(result.maxOutputTokens).toBe(8192);
+    expect(result.topP).toBe(0.9);
+    expect(result.topK).toBe(40);
+  });
+});

client/src/utils/__tests__/cleanupPreset.test.ts

@@ -1,12 +1,9 @@
-import { EModelEndpoint } from 'librechat-data-provider';
+import { EModelEndpoint, parseConvo } from 'librechat-data-provider';
 import cleanupPreset from '../cleanupPreset';
-import type { TPreset } from 'librechat-data-provider';
-
 // Mock parseConvo since we're focusing on testing the chatGptLabel migration logic
 jest.mock('librechat-data-provider', () => ({
   ...jest.requireActual('librechat-data-provider'),
   parseConvo: jest.fn((input) => {
-    // Return a simplified mock that passes through most properties
     const { conversation } = input;
     return {
       ...conversation,
@@ -221,4 +218,41 @@ describe('cleanupPreset', () => {
       expect(result.presetId).toBeNull();
     });
   });
+
+  describe('defaultParamsEndpoint threading', () => {
+    it('should pass defaultParamsEndpoint to parseConvo', () => {
+      const preset = {
+        ...basePreset,
+        endpoint: 'MyCustomEndpoint',
+        endpointType: EModelEndpoint.custom,
+      };
+
+      cleanupPreset({
+        preset,
+        defaultParamsEndpoint: EModelEndpoint.anthropic,
+      });
+
+      expect(parseConvo).toHaveBeenCalledWith(
+        expect.objectContaining({
+          defaultParamsEndpoint: EModelEndpoint.anthropic,
+        }),
+      );
+    });
+
+    it('should pass undefined defaultParamsEndpoint when not provided', () => {
+      const preset = {
+        ...basePreset,
+        endpoint: 'MyCustomEndpoint',
+        endpointType: EModelEndpoint.custom,
+      };
+
+      cleanupPreset({ preset });
+
+      expect(parseConvo).toHaveBeenCalledWith(
+        expect.objectContaining({
+          defaultParamsEndpoint: undefined,
+        }),
+      );
+    });
+  });
 });

client/src/utils/buildDefaultConvo.ts

@@ -14,11 +14,13 @@ const buildDefaultConvo = ({
   conversation,
   endpoint = null,
   lastConversationSetup,
+  defaultParamsEndpoint,
 }: {
   models: string[];
   conversation: TConversation;
   endpoint?: EModelEndpoint | null;
   lastConversationSetup: TConversation | null;
+  defaultParamsEndpoint?: string | null;
 }): TConversation => {
   const { lastSelectedModel, lastSelectedTools } = getLocalStorageItems();
   const endpointType = lastConversationSetup?.endpointType ?? conversation.endpointType;
@@ -49,6 +51,7 @@ const buildDefaultConvo = ({
     possibleValues: {
       models: possibleModels,
     },
+    defaultParamsEndpoint,
   });
 
   const defaultConvo = {

client/src/utils/cleanupPreset.ts

@@ -4,9 +4,10 @@ import type { TPreset } from 'librechat-data-provider';
 type UIPreset = Partial<TPreset> & { presetOverride?: Partial<TPreset> };
 type TCleanupPreset = {
   preset?: UIPreset;
+  defaultParamsEndpoint?: string | null;
 };
 
-const cleanupPreset = ({ preset: _preset }: TCleanupPreset): TPreset => {
+const cleanupPreset = ({ preset: _preset, defaultParamsEndpoint }: TCleanupPreset): TPreset => {
   const { endpoint, endpointType } = _preset ?? ({} as UIPreset);
   if (endpoint == null || endpoint === '') {
     console.error(`Unknown endpoint ${endpoint}`, _preset);
@@ -35,8 +36,13 @@ const cleanupPreset = ({ preset: _preset }: TCleanupPreset): TPreset => {
     delete preset.chatGptLabel;
   }
 
-  /* @ts-ignore: endpoint can be a custom defined name */
-  const parsedPreset = parseConvo({ endpoint, endpointType, conversation: preset });
+  const parsedPreset = parseConvo({
+    /* @ts-ignore: endpoint can be a custom defined name */
+    endpoint,
+    endpointType,
+    conversation: preset,
+    defaultParamsEndpoint,
+  });
 
   return {
     presetId: _preset?.presetId ?? null,