@@ -394,7 +394,7 @@ export class ProcessingManager {
394394 } ) )
395395 ]
396396
397- const { object : problemInfo , usage } = await generateObject ( {
397+ const { object : problemInfo } = await generateObject ( {
398398 model : llmProvider ,
399399 schema : problemInfoSchema ,
400400 messages : [
@@ -409,10 +409,10 @@ export class ProcessingManager {
409409 mode : 'json' , // Enforce JSON output mode if supported by the model/provider
410410 abortSignal
411411 } )
412- console . log ( {
413- problemInfo,
414- usage
415- } )
412+ // console.log({
413+ // problemInfo,
414+ // usage
415+ // })
416416
417417 if ( ! problemInfo || Object . keys ( problemInfo ) . length === 0 ) {
418418 throw new Error ( 'Failed to extract problem information or received empty data.' )
@@ -498,7 +498,7 @@ For complexity explanations, please be thorough. For example: "Time complexity:
498498
499499Your solution should be efficient, well-commented, and handle edge cases.
500500`
501- const { text : responseContent , usage } = await generateText ( {
501+ const { text : responseContent } = await generateText ( {
502502 model : solutionLLMProvider ,
503503 messages : [
504504 {
@@ -511,10 +511,10 @@ Your solution should be efficient, well-commented, and handle edge cases.
511511 maxTokens : solutionLLMProvider . provider == 'openai' ? 4000 : 6000 ,
512512 abortSignal
513513 } )
514- console . log ( {
515- responseContent,
516- usage
517- } )
514+ // console.log({
515+ // responseContent,
516+ // usage
517+ // })
518518
519519 if ( ! responseContent ) {
520520 throw new Error ( 'No content received from AI for solution generation.' )
@@ -654,7 +654,7 @@ Your solution should be efficient, well-commented, and handle edge cases.
654654 progress : 60
655655 } )
656656
657- const { text : debugContent , usage } = await generateText ( {
657+ const { text : debugContent } = await generateText ( {
658658 model : debuggingLLMProvider ,
659659 messages : [
660660 {
@@ -682,10 +682,10 @@ Your solution should be efficient, well-commented, and handle edge cases.
682682 maxTokens : debuggingLLMProvider . provider == 'openai' ? 4000 : 6000 ,
683683 abortSignal
684684 } )
685- console . log ( {
686- debugContent,
687- usage
688- } )
685+ // console.log({
686+ // debugContent,
687+ // usage
688+ // })
689689
690690 if ( ! debugContent ) {
691691 throw new Error ( 'No content received from AI for debug analysis.' )
@@ -795,7 +795,7 @@ Your solution should be efficient, well-commented, and handle edge cases.
795795 progress : 60
796796 } )
797797
798- const { text : answer , usage } = await generateText ( {
798+ const { text : answer } = await generateText ( {
799799 model : llmProvider ,
800800 messages : [
801801 {
@@ -823,10 +823,10 @@ Tell answers in details of about 200 words minimum.
823823 maxTokens : llmProvider . provider == 'openai' ? 4000 : 6000
824824 } )
825825
826- console . log ( {
827- answer,
828- usage
829- } )
826+ // console.log({
827+ // answer,
828+ // usage
829+ // })
830830
831831 if ( ! answer || answer . trim ( ) . length === 0 ) {
832832 throw new Error ( 'Failed to generate a response to the question.' )
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