🤖 feat: Claude Opus 4.6 - 1M Context, Premium Pricing, Adaptive Thinking (#11670)

* feat: Implement new features for Claude Opus 4.6 model

- Added support for tiered pricing based on input token count for the Claude Opus 4.6 model.
- Updated token value calculations to include inputTokenCount for accurate pricing.
- Enhanced transaction handling to apply premium rates when input tokens exceed defined thresholds.
- Introduced comprehensive tests to validate pricing logic for both standard and premium rates across various scenarios.
- Updated related utility functions and models to accommodate new pricing structure.

This change improves the flexibility and accuracy of token pricing for the Claude Opus 4.6 model, ensuring users are charged appropriately based on their usage.

* feat: Add effort field to conversation and preset schemas

- Introduced a new optional `effort` field of type `String` in both the `IPreset` and `IConversation` interfaces.
- Updated the `conversationPreset` schema to include the `effort` field, enhancing the data structure for better context management.

* chore: Clean up unused variable and comments in initialize function

* chore: update dependencies and SDK versions

- Updated @anthropic-ai/sdk to version 0.73.0 in package.json and overrides.
- Updated @anthropic-ai/vertex-sdk to version 0.14.3 in packages/api/package.json.
- Updated @librechat/agents to version 3.1.34 in packages/api/package.json.
- Refactored imports in packages/api/src/endpoints/anthropic/vertex.ts for consistency.

* chore: remove postcss-loader from dependencies

* feat: Bedrock model support for adaptive thinking configuration

- Updated .env.example to include new Bedrock model IDs for Claude Opus 4.6.
- Refactored bedrockInputParser to support adaptive thinking for Opus models, allowing for dynamic thinking configurations.
- Introduced a new function to check model compatibility with adaptive thinking.
- Added an optional `effort` field to the input schemas and updated related configurations.
- Enhanced tests to validate the new adaptive thinking logic and model configurations.

* feat: Add tests for Opus 4.6 adaptive thinking configuration

* feat: Update model references for Opus 4.6 by removing version suffix

* feat: Update @librechat/agents to version 3.1.35 in package.json and package-lock.json

* chore: @librechat/agents to version 3.1.36 in package.json and package-lock.json

* feat: Normalize inputTokenCount for spendTokens and enhance transaction handling

- Introduced normalization for promptTokens to ensure inputTokenCount does not go negative.
- Updated transaction logic to reflect normalized inputTokenCount in pricing calculations.
- Added comprehensive tests to validate the new normalization logic and its impact on transaction rates for both standard and premium models.
- Refactored related functions to improve clarity and maintainability of token value calculations.

* chore: Simplify adaptive thinking configuration in helpers.ts

- Removed unnecessary type casting for the thinking property in updatedOptions.
- Ensured that adaptive thinking is directly assigned when conditions are met, improving code clarity.

* refactor: Replace hard-coded token values with dynamic retrieval from maxTokensMap in model tests

* fix: Ensure non-negative token values in spendTokens calculations

- Updated token value retrieval to use Math.max for prompt and completion tokens, preventing negative values.
- Enhanced clarity in token calculations for both prompt and completion transactions.

* test: Add test for normalization of negative structured token values in spendStructuredTokens

- Implemented a test to ensure that negative structured token values are normalized to zero during token spending.
- Verified that the transaction rates remain consistent with the expected standard values after normalization.

* refactor: Bedrock model support for adaptive thinking and context handling

- Added tests for various alternate naming conventions of Claude models to validate adaptive thinking and context support.
- Refactored `supportsAdaptiveThinking` and `supportsContext1m` functions to utilize new parsing methods for model version extraction.
- Updated `bedrockInputParser` to handle effort configurations more effectively and strip unnecessary fields for non-adaptive models.
- Improved handling of anthropic model configurations in the input parser.

* fix: Improve token value retrieval in getMultiplier function

- Updated the token value retrieval logic to use optional chaining for better safety against undefined values.
- Added a test case to ensure that the function returns the default rate when the provided valueKey does not exist in tokenValues.

api/models/tx.spec.js

@@ -1,3 +1,4 @@
+/** Note: No hard-coded values should be used in this file. */
 const { maxTokensMap } = require('@librechat/api');
 const { EModelEndpoint } = require('librechat-data-provider');
 const {
@@ -5,8 +6,10 @@ const {
   tokenValues,
   getValueKey,
   getMultiplier,
+  getPremiumRate,
   cacheTokenValues,
   getCacheMultiplier,
+  premiumTokenValues,
 } = require('./tx');
 
 describe('getValueKey', () => {
@@ -239,6 +242,15 @@ describe('getMultiplier', () => {
     expect(getMultiplier({ valueKey: '8k', tokenType: 'unknownType' })).toBe(defaultRate);
   });
 
+  it('should return defaultRate if valueKey does not exist in tokenValues', () => {
+    expect(getMultiplier({ valueKey: 'non-existent-model', tokenType: 'prompt' })).toBe(
+      defaultRate,
+    );
+    expect(getMultiplier({ valueKey: 'non-existent-model', tokenType: 'completion' })).toBe(
+      defaultRate,
+    );
+  });
+
   it('should derive the valueKey from the model if not provided', () => {
     expect(getMultiplier({ tokenType: 'prompt', model: 'gpt-4-some-other-info' })).toBe(
       tokenValues['8k'].prompt,
@@ -334,8 +346,6 @@ describe('getMultiplier', () => {
     expect(getMultiplier({ model: 'openai/gpt-5.1', tokenType: 'prompt' })).toBe(
       tokenValues['gpt-5.1'].prompt,
     );
-    expect(tokenValues['gpt-5.1'].prompt).toBe(1.25);
-    expect(tokenValues['gpt-5.1'].completion).toBe(10);
   });
 
   it('should return the correct multiplier for gpt-5.2', () => {
@@ -348,8 +358,6 @@ describe('getMultiplier', () => {
     expect(getMultiplier({ model: 'openai/gpt-5.2', tokenType: 'prompt' })).toBe(
       tokenValues['gpt-5.2'].prompt,
     );
-    expect(tokenValues['gpt-5.2'].prompt).toBe(1.75);
-    expect(tokenValues['gpt-5.2'].completion).toBe(14);
   });
 
   it('should return the correct multiplier for gpt-4o', () => {
@@ -815,8 +823,6 @@ describe('Deepseek Model Tests', () => {
     expect(getMultiplier({ model: 'deepseek-chat', tokenType: 'completion' })).toBe(
       tokenValues['deepseek-chat'].completion,
     );
-    expect(tokenValues['deepseek-chat'].prompt).toBe(0.28);
-    expect(tokenValues['deepseek-chat'].completion).toBe(0.42);
   });
 
   it('should return correct pricing for deepseek-reasoner', () => {
@@ -826,8 +832,6 @@ describe('Deepseek Model Tests', () => {
     expect(getMultiplier({ model: 'deepseek-reasoner', tokenType: 'completion' })).toBe(
       tokenValues['deepseek-reasoner'].completion,
     );
-    expect(tokenValues['deepseek-reasoner'].prompt).toBe(0.28);
-    expect(tokenValues['deepseek-reasoner'].completion).toBe(0.42);
   });
 
   it('should handle DeepSeek model name variations with provider prefixes', () => {
@@ -840,8 +844,8 @@ describe('Deepseek Model Tests', () => {
     modelVariations.forEach((model) => {
       const promptMultiplier = getMultiplier({ model, tokenType: 'prompt' });
       const completionMultiplier = getMultiplier({ model, tokenType: 'completion' });
-      expect(promptMultiplier).toBe(0.28);
-      expect(completionMultiplier).toBe(0.42);
+      expect(promptMultiplier).toBe(tokenValues['deepseek-chat'].prompt);
+      expect(completionMultiplier).toBe(tokenValues['deepseek-chat'].completion);
     });
   });
 
@@ -860,13 +864,13 @@ describe('Deepseek Model Tests', () => {
     );
   });
 
-  it('should return correct cache pricing values for DeepSeek models', () => {
-    expect(cacheTokenValues['deepseek-chat'].write).toBe(0.28);
-    expect(cacheTokenValues['deepseek-chat'].read).toBe(0.028);
-    expect(cacheTokenValues['deepseek-reasoner'].write).toBe(0.28);
-    expect(cacheTokenValues['deepseek-reasoner'].read).toBe(0.028);
-    expect(cacheTokenValues['deepseek'].write).toBe(0.28);
-    expect(cacheTokenValues['deepseek'].read).toBe(0.028);
+  it('should have consistent cache pricing across DeepSeek model variants', () => {
+    expect(cacheTokenValues['deepseek'].write).toBe(cacheTokenValues['deepseek-chat'].write);
+    expect(cacheTokenValues['deepseek'].read).toBe(cacheTokenValues['deepseek-chat'].read);
+    expect(cacheTokenValues['deepseek-reasoner'].write).toBe(
+      cacheTokenValues['deepseek-chat'].write,
+    );
+    expect(cacheTokenValues['deepseek-reasoner'].read).toBe(cacheTokenValues['deepseek-chat'].read);
   });
 
   it('should handle DeepSeek cache multipliers with model variations', () => {
@@ -875,8 +879,8 @@ describe('Deepseek Model Tests', () => {
     modelVariations.forEach((model) => {
       const writeMultiplier = getCacheMultiplier({ model, cacheType: 'write' });
       const readMultiplier = getCacheMultiplier({ model, cacheType: 'read' });
-      expect(writeMultiplier).toBe(0.28);
-      expect(readMultiplier).toBe(0.028);
+      expect(writeMultiplier).toBe(cacheTokenValues['deepseek-chat'].write);
+      expect(readMultiplier).toBe(cacheTokenValues['deepseek-chat'].read);
     });
   });
 });
@@ -1876,6 +1880,201 @@ describe('Claude Model Tests', () => {
       );
     });
   });
+
+  it('should return correct prompt and completion rates for Claude Opus 4.6', () => {
+    expect(getMultiplier({ model: 'claude-opus-4-6', tokenType: 'prompt' })).toBe(
+      tokenValues['claude-opus-4-6'].prompt,
+    );
+    expect(getMultiplier({ model: 'claude-opus-4-6', tokenType: 'completion' })).toBe(
+      tokenValues['claude-opus-4-6'].completion,
+    );
+  });
+
+  it('should handle Claude Opus 4.6 model name variations', () => {
+    const modelVariations = [
+      'claude-opus-4-6',
+      'claude-opus-4-6-20250801',
+      'claude-opus-4-6-latest',
+      'anthropic/claude-opus-4-6',
+      'claude-opus-4-6/anthropic',
+      'claude-opus-4-6-preview',
+    ];
+
+    modelVariations.forEach((model) => {
+      const valueKey = getValueKey(model);
+      expect(valueKey).toBe('claude-opus-4-6');
+      expect(getMultiplier({ model, tokenType: 'prompt' })).toBe(
+        tokenValues['claude-opus-4-6'].prompt,
+      );
+      expect(getMultiplier({ model, tokenType: 'completion' })).toBe(
+        tokenValues['claude-opus-4-6'].completion,
+      );
+    });
+  });
+
+  it('should return correct cache rates for Claude Opus 4.6', () => {
+    expect(getCacheMultiplier({ model: 'claude-opus-4-6', cacheType: 'write' })).toBe(
+      cacheTokenValues['claude-opus-4-6'].write,
+    );
+    expect(getCacheMultiplier({ model: 'claude-opus-4-6', cacheType: 'read' })).toBe(
+      cacheTokenValues['claude-opus-4-6'].read,
+    );
+  });
+
+  it('should handle Claude Opus 4.6 cache rates with model name variations', () => {
+    const modelVariations = [
+      'claude-opus-4-6',
+      'claude-opus-4-6-20250801',
+      'claude-opus-4-6-latest',
+      'anthropic/claude-opus-4-6',
+      'claude-opus-4-6/anthropic',
+      'claude-opus-4-6-preview',
+    ];
+
+    modelVariations.forEach((model) => {
+      expect(getCacheMultiplier({ model, cacheType: 'write' })).toBe(
+        cacheTokenValues['claude-opus-4-6'].write,
+      );
+      expect(getCacheMultiplier({ model, cacheType: 'read' })).toBe(
+        cacheTokenValues['claude-opus-4-6'].read,
+      );
+    });
+  });
+});
+
+describe('Premium Token Pricing', () => {
+  const premiumModel = 'claude-opus-4-6';
+  const premiumEntry = premiumTokenValues[premiumModel];
+  const { threshold } = premiumEntry;
+  const belowThreshold = threshold - 1;
+  const aboveThreshold = threshold + 1;
+  const wellAboveThreshold = threshold * 2;
+
+  it('should have premium pricing defined for claude-opus-4-6', () => {
+    expect(premiumEntry).toBeDefined();
+    expect(premiumEntry.threshold).toBeDefined();
+    expect(premiumEntry.prompt).toBeDefined();
+    expect(premiumEntry.completion).toBeDefined();
+    expect(premiumEntry.prompt).toBeGreaterThan(tokenValues[premiumModel].prompt);
+    expect(premiumEntry.completion).toBeGreaterThan(tokenValues[premiumModel].completion);
+  });
+
+  it('should return null from getPremiumRate when inputTokenCount is below threshold', () => {
+    expect(getPremiumRate(premiumModel, 'prompt', belowThreshold)).toBeNull();
+    expect(getPremiumRate(premiumModel, 'completion', belowThreshold)).toBeNull();
+    expect(getPremiumRate(premiumModel, 'prompt', threshold)).toBeNull();
+  });
+
+  it('should return premium rate from getPremiumRate when inputTokenCount exceeds threshold', () => {
+    expect(getPremiumRate(premiumModel, 'prompt', aboveThreshold)).toBe(premiumEntry.prompt);
+    expect(getPremiumRate(premiumModel, 'completion', aboveThreshold)).toBe(
+      premiumEntry.completion,
+    );
+    expect(getPremiumRate(premiumModel, 'prompt', wellAboveThreshold)).toBe(premiumEntry.prompt);
+  });
+
+  it('should return null from getPremiumRate when inputTokenCount is undefined or null', () => {
+    expect(getPremiumRate(premiumModel, 'prompt', undefined)).toBeNull();
+    expect(getPremiumRate(premiumModel, 'prompt', null)).toBeNull();
+  });
+
+  it('should return null from getPremiumRate for models without premium pricing', () => {
+    expect(getPremiumRate('claude-opus-4-5', 'prompt', wellAboveThreshold)).toBeNull();
+    expect(getPremiumRate('claude-sonnet-4', 'prompt', wellAboveThreshold)).toBeNull();
+    expect(getPremiumRate('gpt-4o', 'prompt', wellAboveThreshold)).toBeNull();
+  });
+
+  it('should return standard rate from getMultiplier when inputTokenCount is below threshold', () => {
+    expect(
+      getMultiplier({
+        model: premiumModel,
+        tokenType: 'prompt',
+        inputTokenCount: belowThreshold,
+      }),
+    ).toBe(tokenValues[premiumModel].prompt);
+    expect(
+      getMultiplier({
+        model: premiumModel,
+        tokenType: 'completion',
+        inputTokenCount: belowThreshold,
+      }),
+    ).toBe(tokenValues[premiumModel].completion);
+  });
+
+  it('should return premium rate from getMultiplier when inputTokenCount exceeds threshold', () => {
+    expect(
+      getMultiplier({
+        model: premiumModel,
+        tokenType: 'prompt',
+        inputTokenCount: aboveThreshold,
+      }),
+    ).toBe(premiumEntry.prompt);
+    expect(
+      getMultiplier({
+        model: premiumModel,
+        tokenType: 'completion',
+        inputTokenCount: aboveThreshold,
+      }),
+    ).toBe(premiumEntry.completion);
+  });
+
+  it('should return standard rate from getMultiplier when inputTokenCount is exactly at threshold', () => {
+    expect(
+      getMultiplier({ model: premiumModel, tokenType: 'prompt', inputTokenCount: threshold }),
+    ).toBe(tokenValues[premiumModel].prompt);
+  });
+
+  it('should return premium rate from getMultiplier when inputTokenCount is one above threshold', () => {
+    expect(
+      getMultiplier({ model: premiumModel, tokenType: 'prompt', inputTokenCount: aboveThreshold }),
+    ).toBe(premiumEntry.prompt);
+  });
+
+  it('should not apply premium pricing to models without premium entries', () => {
+    expect(
+      getMultiplier({
+        model: 'claude-opus-4-5',
+        tokenType: 'prompt',
+        inputTokenCount: wellAboveThreshold,
+      }),
+    ).toBe(tokenValues['claude-opus-4-5'].prompt);
+    expect(
+      getMultiplier({
+        model: 'claude-sonnet-4',
+        tokenType: 'prompt',
+        inputTokenCount: wellAboveThreshold,
+      }),
+    ).toBe(tokenValues['claude-sonnet-4'].prompt);
+  });
+
+  it('should use standard rate when inputTokenCount is not provided', () => {
+    expect(getMultiplier({ model: premiumModel, tokenType: 'prompt' })).toBe(
+      tokenValues[premiumModel].prompt,
+    );
+    expect(getMultiplier({ model: premiumModel, tokenType: 'completion' })).toBe(
+      tokenValues[premiumModel].completion,
+    );
+  });
+
+  it('should apply premium pricing through getMultiplier with valueKey path', () => {
+    const valueKey = getValueKey(premiumModel);
+    expect(getMultiplier({ valueKey, tokenType: 'prompt', inputTokenCount: aboveThreshold })).toBe(
+      premiumEntry.prompt,
+    );
+    expect(
+      getMultiplier({ valueKey, tokenType: 'completion', inputTokenCount: aboveThreshold }),
+    ).toBe(premiumEntry.completion);
+  });
+
+  it('should apply standard pricing through getMultiplier with valueKey path when below threshold', () => {
+    const valueKey = getValueKey(premiumModel);
+    expect(getMultiplier({ valueKey, tokenType: 'prompt', inputTokenCount: belowThreshold })).toBe(
+      tokenValues[premiumModel].prompt,
+    );
+    expect(
+      getMultiplier({ valueKey, tokenType: 'completion', inputTokenCount: belowThreshold }),
+    ).toBe(tokenValues[premiumModel].completion);
+  });
 });
 
 describe('tokens.ts and tx.js sync validation', () => {