Better thonk effort for Gem 3

83ea6e5cbf20f919c3d5add2ec65cfdd9faf2197

Cohee <18619528+Cohee1207@users.noreply.github.com>

Parents: 6fccccca6d7911555aba55e9b555f48ec925e0c5

public/index.html+7 -1 Viewed

                                             <div class="toggle-description justifyLeft marginBot5" data-source="claude" data-i18n="Allocates a portion of the response length for thinking (min: 1024 tokens, low: 10%, medium: 25%, high: 50%, max: 95%), but minimum 1024 tokens. Auto does not request thinking.">
                                                 Allocates a portion of the response length for thinking (min: 1024 tokens, low: 10%, medium: 25%, high: 50%, max: 95%), but minimum 1024 tokens. Auto does not request thinking.
                                             </div>
 -                                            <div class="toggle-description justifyLeft marginBot5" data-source="makersuite,vertexai" data-i18n="Allocates a portion of the response length for thinking (Flash 2.5/Pro 2.5) (min: 0/128 tokens, low: 10%, medium: 25%, high: 50%, max: 24576/32768 tokens). Auto lets the model decide.">
 +                                            <div class="toggle-description justifyLeft marginBot5" data-source="makersuite,vertexai">
 +                                                <span data-i18n="Sets a dynamic reasoning depth level for thinking (Flash 3/Pro 3). High and low are supported by both, minimal and medium are Flash 3 only. Auto lets the model decide.">
 +                                                    Sets a dynamic reasoning depth level for thinking (Flash 3/Pro 3). High and low are supported by both, minimal and medium are Flash 3 only. Auto lets the model decide.
 +                                                </span>
 +                                                <br>
 +                                                <span data-i18n="Allocates a portion of the response length for thinking (Flash 2.5/Pro 2.5) (min: 0/128 tokens, low: 10%, medium: 25%, high: 50%, max: 24576/32768 tokens). Auto lets the model decide.">
                                                     Allocates a portion of the response length for thinking (Flash 2.5/Pro 2.5) (min: 0/128 tokens, low: 10%, medium: 25%, high: 50%, max: 24576/32768 tokens). Auto lets the model decide.
 +                                                </span>
                                             </div>
                                         </div>
                                     </div>

src/endpoints/backends/chat-completions.js+5 -1 Viewed

             const thinkingConfig = { includeThoughts: includeReasoning };
             const thinkingBudget = calculateGoogleBudgetTokens(generationConfig.maxOutputTokens, reasoningEffort, model);
             if (typeof thinkingBudget === 'number' && Number.isInteger(thinkingBudget)) {
                 thinkingConfig.thinkingBudget = thinkingBudget;
+            }
 +            if (typeof thinkingBudget === 'string' && thinkingBudget.length > 0) {
 +                thinkingConfig.thinkingLevel = thinkingBudget;
 +            }
++
             // Vertex doesn't allow mixing disabled thinking with includeThoughts
             if (useVertexAi && thinkingBudget === 0 && thinkingConfig.includeThoughts) {
                 console.info('Thinking budget is 0, but includeThoughts is true. Thoughts will not be included in the response.');

src/prompt-converters.js+50 -4 Viewed

  * @param {number} maxTokens Maximum tokens
  * @param {string} reasoningEffort Reasoning effort
  * @param {string} model Model name
  * @returns {number?|string|null} Budget tokens
  */
 export function calculateGoogleBudgetTokens(maxTokens, reasoningEffort, model) {
     function getFlashBudget() {

         return budgetTokens;
+    }
 -    if (model.includes('flash-lite')) {
 +    function getGemini3FlashBudget() {
 +        switch (reasoningEffort) {
 +            case REASONING_EFFORT.auto:
 +                return null;
 +            case REASONING_EFFORT.min:
 +                return 'minimal';
 +            case REASONING_EFFORT.low:
 +                return 'low';
 +            case REASONING_EFFORT.medium:
 +                return 'medium';
 +            case REASONING_EFFORT.high:
 +                return 'high';
 +            case REASONING_EFFORT.max:
 +                return 'high';
 +        }
++
 +        return null;
 +    }
++
 +    function getGemini3ProBudget() {
 +        switch (reasoningEffort) {
 +            case REASONING_EFFORT.auto:
 +                return null;
 +            case REASONING_EFFORT.min:
 +                return 'low';
 +            case REASONING_EFFORT.low:
 +                return 'low';
 +            case REASONING_EFFORT.medium:
 +                return 'low';
 +            case REASONING_EFFORT.high:
 +                return 'high';
 +            case REASONING_EFFORT.max:
 +                return 'high';
 +        }
++
 +        return null;
 +    }
++
 +    if (/gemini-3-pro/.test(model)) {
 +        return getGemini3ProBudget();
 +    }
++
 +    if (/gemini-3-flash/.test(model) ) {
 +        return getGemini3FlashBudget();
 +    }
++
 +    if (/flash-lite/.test(model)) {
         return getFlashLiteBudget();
+    }
     if (model/flash/.includestest('flash'model)) {
         return getFlashBudget();
+    }
     if (model/pro/.includestest('pro'model)) {
         return getProBudget();
+    }