Fix mentor modal i18n and improve AI feedback quality

app/api/analyze-code/route.ts

@@ -38,6 +38,20 @@ interface CodeAnalysis {
   detailedFeedback: string
 }
 
+const LOW_SIGNAL_KO_PATTERNS = [
+  "전반적으로",
+  "일반적으로",
+  "좋은 시도",
+  "조금 더 개선",
+]
+
+const LOW_SIGNAL_EN_PATTERNS = [
+  "overall",
+  "generally",
+  "good attempt",
+  "could be improved",
+]
+
 function clamp(value: number, min: number, max: number): number {
   if (!Number.isFinite(value)) {
     return min
@@ -96,6 +110,106 @@ function deriveEfficiencyLevel(efficiency: number): CodeAnalysis["efficiencyLeve
   return "Low"
 }
 
+function isLowSignalText(text: string, language: MentorLanguage): boolean {
+  const normalized = text.trim().toLowerCase()
+  if (!normalized) {
+    return true
+  }
+
+  const hasConcreteAction = /(replace|change|trace|check|use|reduce|split|추적|바꿔|확인|사용|줄이|분리)/i.test(
+    text
+  )
+  const hasTestReference = /(test|케이스|입력|expected|actual|pass|fail|통과|실패)/i.test(text)
+  const matchedPattern =
+    language === "ko"
+      ? LOW_SIGNAL_KO_PATTERNS.some((pattern) => normalized.includes(pattern))
+      : LOW_SIGNAL_EN_PATTERNS.some((pattern) => normalized.includes(pattern))
+
+  if (text.length < 24 && !hasConcreteAction) {
+    return true
+  }
+  if (matchedPattern && !hasConcreteAction) {
+    return true
+  }
+
+  return !hasConcreteAction && !hasTestReference
+}
+
+function buildDeterministicSuggestion(
+  language: MentorLanguage,
+  testResults: AnalyzeRequest["testResults"],
+  allTestsPassed: boolean,
+  code: string
+): string {
+  const firstFailed = testResults.find((result) => !result.passed)
+  const hasNestedLoop = /for\s*\(.*\)\s*{[\s\S]*for\s*\(/.test(code)
+
+  if (language === "ko") {
+    if (!allTestsPassed && firstFailed) {
+      return `실패 케이스(${firstFailed.input}) 기준으로 첫 오분기 지점 1곳만 수정해보세요.`
+    }
+    return hasNestedLoop
+      ? "중첩 순회를 Map/Set 조회로 바꿔 반복 스캔을 줄여보세요."
+      : "경계값 처리(빈 입력/최소 길이)를 early return으로 분리해보세요."
+  }
+
+  if (!allTestsPassed && firstFailed) {
+    return `Patch one wrong branch first using the failing case (${firstFailed.input}).`
+  }
+  return hasNestedLoop
+    ? "Replace nested scans with Map/Set lookups to reduce repeated passes."
+    : "Extract boundary checks (empty/min length) into early returns."
+}
+
+function buildDeterministicDetailedFeedback(
+  language: MentorLanguage,
+  testResults: AnalyzeRequest["testResults"],
+  allTestsPassed: boolean,
+  code: string
+): string {
+  const passed = testResults.filter((result) => result.passed).length
+  const total = testResults.length
+  const firstFailed = testResults.find((result) => !result.passed)
+  const hasNestedLoop = /for\s*\(.*\)\s*{[\s\S]*for\s*\(/.test(code)
+
+  if (language === "ko") {
+    if (!allTestsPassed && firstFailed) {
+      return `${passed}/${total} 통과 상태입니다. 실패 케이스 입력(${firstFailed.input})에서 조건문 분기 순서를 위에서 아래로 추적해 기대값(${firstFailed.expected})과 달라지는 첫 지점을 수정하세요.`
+    }
+    return hasNestedLoop
+      ? `${passed}/${total} 통과입니다. 정답은 맞으니 다음 단계는 중첩 루프를 줄여 시간복잡도를 개선하는 것입니다.`
+      : `${passed}/${total} 통과입니다. 현재 로직은 안정적이며, 다음 개선은 경계값 처리와 함수 책임 분리입니다.`
+  }
+
+  if (!allTestsPassed && firstFailed) {
+    return `${passed}/${total} tests pass. Start with the failing input (${firstFailed.input}), trace branch flow top-down, and fix the first divergence from expected output (${firstFailed.expected}).`
+  }
+  return hasNestedLoop
+    ? `${passed}/${total} tests pass. Correctness is stable; next step is reducing nested loops for better time complexity.`
+    : `${passed}/${total} tests pass. Logic is stable; next step is clearer boundary handling and smaller function responsibilities.`
+}
+
+function normalizeAnalysisFeedback(
+  analysis: CodeAnalysis,
+  language: MentorLanguage,
+  testResults: AnalyzeRequest["testResults"],
+  allTestsPassed: boolean,
+  code: string
+): CodeAnalysis {
+  const suggestion = isLowSignalText(analysis.suggestion, language)
+    ? buildDeterministicSuggestion(language, testResults, allTestsPassed, code)
+    : analysis.suggestion
+  const detailedFeedback = isLowSignalText(analysis.detailedFeedback, language)
+    ? buildDeterministicDetailedFeedback(language, testResults, allTestsPassed, code)
+    : analysis.detailedFeedback
+
+  return {
+    ...analysis,
+    suggestion,
+    detailedFeedback,
+  }
+}
+
 function parseAnalysisJson(
   content: string,
   testResults: AnalyzeRequest["testResults"]
@@ -187,7 +301,7 @@ Return ONLY the JSON object, no other text.`
     model: getLanguageModel("claude", model, apiKey),
     prompt,
     maxOutputTokens,
-    temperature: 0.7,
+    temperature: 0.35,
   })
   const content = result.text
 
@@ -256,7 +370,7 @@ Return ONLY the JSON object, no other text.`
     system: "You are a helpful coding mentor. Always respond with valid JSON only.",
     prompt,
     maxOutputTokens,
-    temperature: 0.7,
+    temperature: 0.35,
   })
   const content = result.text
 
@@ -324,7 +438,7 @@ Return ONLY the JSON object, no other text.`
     model: getLanguageModel("gemini", model, apiKey),
     prompt,
     maxOutputTokens,
-    temperature: 0.7,
+    temperature: 0.35,
   })
   const content = result.text
 
@@ -432,6 +546,14 @@ export async function POST(req: NextRequest) {
       )
     }
 
+    analysis = normalizeAnalysisFeedback(
+      analysis,
+      language,
+      testResults,
+      allTestsPassed,
+      code
+    )
+
     return NextResponse.json(analysis)
   } catch (error) {
     console.error("Error analyzing code:", error)

app/api/review-code/route.ts

@@ -38,10 +38,89 @@ const REVIEW_REPLY_FORMAT_RULES = `Reply format:
 - Avoid rhetorical questions and repetitive praise.
 - Keep it to one short acknowledgement + one concrete action point whenever possible.`
 
+const LOW_SIGNAL_KO_PATTERNS = [
+  "좋은 시도",
+  "좋은 접근",
+  "잘하고 있어",
+  "전반적으로",
+  "일반적으로",
+  "조금 더 개선",
+]
+
+const LOW_SIGNAL_EN_PATTERNS = [
+  "good attempt",
+  "good job",
+  "overall",
+  "generally",
+  "could be improved",
+  "looks fine",
+]
+
 function resolveResponseTokenLimit(maxOutputTokens: number): number {
   return Math.max(256, maxOutputTokens)
 }
 
+function isLowSignalReview(text: string, language: MentorLanguage): boolean {
+  const normalized = text.trim().toLowerCase()
+  if (!normalized) {
+    return true
+  }
+
+  const lineCount = text
+    .split("\n")
+    .map((line) => line.trim())
+    .filter(Boolean).length
+  const hasTestReference = /(test|케이스|입력|expected|actual|pass|fail|통과|실패)/i.test(text)
+  const hasConcreteAction = /(replace|change|trace|check|use|추적|바꿔|확인|사용|적용)/i.test(text)
+
+  const matchedPattern =
+    language === "ko"
+      ? LOW_SIGNAL_KO_PATTERNS.some((pattern) => normalized.includes(pattern))
+      : LOW_SIGNAL_EN_PATTERNS.some((pattern) => normalized.includes(pattern))
+
+  if (lineCount <= 1 && !hasTestReference) {
+    return true
+  }
+  if (matchedPattern && !hasConcreteAction) {
+    return true
+  }
+  return !hasTestReference && !hasConcreteAction
+}
+
+function buildDeterministicReviewFallback(
+  language: MentorLanguage,
+  testResults: TestResult[],
+  allTestsPassed: boolean,
+  code: string
+): string {
+  const firstFailed = testResults.find((result) => !result.passed)
+  const hasNestedLoop = /for\s*\(.*\)\s*{[\s\S]*for\s*\(/.test(code)
+
+  if (language === "ko") {
+    if (!allTestsPassed && firstFailed) {
+      return `지금은 ${testResults.filter((r) => r.passed).length}/${testResults.length} 통과야. 먼저 실패한 케이스 1개부터 고치자.
+입력: ${firstFailed.input}
+기대값: ${firstFailed.expected}, 실제값: ${firstFailed.actual}
+다음 액션: 이 케이스를 기준으로 조건문 분기 순서를 위에서 아래로 한 줄씩 추적하고, 기대값과 다른 첫 분기 지점만 수정해봐.`
+    }
+
+    return hasNestedLoop
+      ? "테스트는 통과했어. 다음으로 중첩 루프를 줄일 수 있는지부터 보자. Map/Set으로 조회를 O(1)로 바꾸면 반복 스캔을 줄일 가능성이 커."
+      : "테스트는 통과했어. 다음 액션은 함수 책임을 한 단계만 분리하는 거야. 경계값 처리(빈 입력/최소 길이)를 early return으로 먼저 두면 유지보수가 쉬워져."
+  }
+
+  if (!allTestsPassed && firstFailed) {
+    return `You are at ${testResults.filter((r) => r.passed).length}/${testResults.length}. Fix one failing case first.
+Input: ${firstFailed.input}
+Expected: ${firstFailed.expected}, Actual: ${firstFailed.actual}
+Next action: trace the branch order top-down for this case and patch only the first branch where behavior diverges from expected output.`
+  }
+
+  return hasNestedLoop
+    ? "Your tests pass. Next action: reduce nested scans first. Consider replacing repeated lookups with Map/Set for O(1) access."
+    : "Your tests pass. Next action: isolate one responsibility. Put boundary checks (empty/min length) as early returns to simplify maintenance."
+}
+
 function finalizeMentorResponse(
   text: string,
   language: MentorLanguage,
@@ -160,6 +239,8 @@ ${!r.passed ? `  Input: ${r.input}\n  Expected: ${r.expected}\n  Got: ${r.actual
   }
 - Suggest algorithm alternatives naturally when relevant.
 - Do not dump a full solution unless explicitly requested.
+- Reference at least one concrete test detail (input/expected/actual or pass count).
+- Include exactly one next action that the learner can execute immediately.
 - ${REVIEW_REPLY_FORMAT_RULES}
 
 Provide your supportive feedback now:
@@ -192,7 +273,7 @@ async function reviewWithClaude(
     model: getLanguageModel("claude", model, apiKey),
     prompt,
     maxOutputTokens: resolveResponseTokenLimit(maxOutputTokens),
-    temperature: 0.7,
+    temperature: 0.35,
   })
   return result.text
 }
@@ -223,7 +304,7 @@ async function reviewWithGPT(
       "You are a helpful coding mentor who provides constructive feedback and guides students to learn.",
     prompt,
     maxOutputTokens: resolveResponseTokenLimit(maxOutputTokens),
-    temperature: 0.7,
+    temperature: 0.35,
   })
   return result.text
 }
@@ -252,7 +333,7 @@ async function reviewWithGemini(
     model: getLanguageModel("gemini", model, apiKey),
     prompt,
     maxOutputTokens: resolveResponseTokenLimit(maxOutputTokens),
-    temperature: 0.7,
+    temperature: 0.35,
   })
   return result.text
 }
@@ -337,7 +418,10 @@ export async function POST(req: NextRequest) {
       }
 
       if (resolved) {
-        feedback = finalizeMentorResponse(resolved, language, allTestsPassed)
+        const refined = isLowSignalReview(resolved, language)
+          ? buildDeterministicReviewFallback(language, testResults, allTestsPassed, code)
+          : resolved
+        feedback = finalizeMentorResponse(refined, language, allTestsPassed)
       } else {
         feedback = finalizeMentorResponse(
           generateFallbackReviewFeedback(

app/problem/[id]/problem-page-client.tsx

@@ -508,15 +508,15 @@ export function ProblemPageClient({ problem }: ProblemPageClientProps) {
       <AlertDialog open={isMentorAlertOpen} onOpenChange={setIsMentorAlertOpen}>
         <AlertDialogContent overlayClassName="bg-black/45">
           <AlertDialogHeader>
-            <AlertDialogTitle>AI 멘토 설정 필요</AlertDialogTitle>
+            <AlertDialogTitle>{copy.problem.mentorSetupTitle}</AlertDialogTitle>
             <AlertDialogDescription>
-              모델을 등록해야만 정확한 피드백이 가능합니다.
+              {copy.problem.mentorSetupDescription}
             </AlertDialogDescription>
           </AlertDialogHeader>
           <AlertDialogFooter>
-            <AlertDialogCancel>취소</AlertDialogCancel>
+            <AlertDialogCancel>{copy.problem.mentorSetupCancel}</AlertDialogCancel>
             <AlertDialogAction onClick={() => router.push("/settings")}>
-              설정 페이지로 이동
+              {copy.problem.mentorSetupGoToSettings}
             </AlertDialogAction>
           </AlertDialogFooter>
         </AlertDialogContent>

lib/i18n.ts

@@ -55,6 +55,10 @@ export interface LocaleCopy {
     translationReady: string;
     fallbackEnglish: string;
     mentorSetupNotice: string;
+    mentorSetupTitle: string;
+    mentorSetupDescription: string;
+    mentorSetupCancel: string;
+    mentorSetupGoToSettings: string;
   };
   problemCard: {
     solved: string;
@@ -132,6 +136,11 @@ const localeCopy: Record<AppLanguage, LocaleCopy> = {
       fallbackEnglish: "English (fallback)",
       mentorSetupNotice:
         "If you do not add a model, it is difficult to expect accurate mentoring.",
+      mentorSetupTitle: "AI mentor setup required",
+      mentorSetupDescription:
+        "You need to set up a model and API key to receive accurate feedback.",
+      mentorSetupCancel: "Cancel",
+      mentorSetupGoToSettings: "Go to Settings",
     },
     problemCard: {
       solved: "Solved",
@@ -205,6 +214,11 @@ const localeCopy: Record<AppLanguage, LocaleCopy> = {
       translationReady: "영어 + 한국어",
       fallbackEnglish: "영어 기본값 (fallback)",
       mentorSetupNotice: "모델을 추가하지 않으면 정확한 멘토링을 기대하기는 어렵습니다.",
+      mentorSetupTitle: "AI 멘토 설정 필요",
+      mentorSetupDescription:
+        "정확한 피드백을 받으려면 모델과 API Key를 설정해야 합니다.",
+      mentorSetupCancel: "취소",
+      mentorSetupGoToSettings: "설정 페이지로 이동",
     },
     problemCard: {
       solved: "해결됨",