Fix: Handle missing teacher answers — include all student answers instead

When 標準答案 is not uploaded, filter_student_wrong_answers now returns
ALL student answers + ALL questions (instead of empty arrays), with a
separate prompt template that asks the LLM to infer correctness.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

chatkit/backend/app/report_generator.py

@@ -51,10 +51,11 @@ def filter_student_wrong_answers(
     student: dict,
     questions_data: dict,
     teacher_answers_data: dict,
-) -> tuple[list[dict], list[dict], list[dict]]:
+) -> tuple[list[dict], list[dict], list[dict], bool]:
     """Compare a student's answers with teacher answers, return wrong items.
 
-    Returns (wrong_questions, wrong_student_answers, relevant_teacher_answers).
+    Returns (wrong_questions, wrong_student_answers, relevant_teacher_answers, has_teacher_answers).
+    When teacher answers are missing, returns ALL student answers & questions instead.
     """
     teacher_map: dict[int, dict] = {}
     for ta in teacher_answers_data.get("answers", []):
@@ -68,6 +69,12 @@ def filter_student_wrong_answers(
         if num is not None:
             question_map[int(num)] = q
 
+    # No teacher answers → return ALL student answers for LLM to analyze
+    if not teacher_map:
+        all_questions = questions_data.get("questions", [])
+        all_answers = student.get("answers", [])
+        return all_questions, all_answers, [], False
+
     wrong_questions: list[dict] = []
     wrong_answers: list[dict] = []
     relevant_teacher: list[dict] = []
@@ -91,7 +98,7 @@ def filter_student_wrong_answers(
             if q:
                 wrong_questions.append(q)
 
-    return wrong_questions, wrong_answers, relevant_teacher
+    return wrong_questions, wrong_answers, relevant_teacher, True
 
 
 STUDENT_REPORT_SYSTEM_PROMPT = """You are ClassLens, an AI teaching assistant that creates a focused, personalized exam analysis report for a single student.
@@ -173,10 +180,53 @@ STUDENT_REPORT_PROMPT = """請為以下學生生成個人化的錯題分析報
 請針對每一道錯題提供詳細分析，找出錯誤模式，並給出具體的學習建議。"""
 
 
+STUDENT_REPORT_PROMPT_NO_KEY = """請為以下學生生成個人化的考試分析報告。
+
+## 學生姓名：{student_name}
+
+## 考試總題數：{total_questions}
+
+## 考試題目：
+{wrong_questions}
+
+## 該學生的全部答案：
+{wrong_answers}
+
+⚠️ 注意：未提供標準答案，請根據題目內容與學生答案進行分析。
+請嘗試判斷答案的正確性，找出可能的錯誤，並給出具體的學習建議。"""
+
+
 def get_default_prompt() -> str:
     return STUDENT_REPORT_PROMPT
 
 
+def _fill_student_prompt(
+    student_name: str,
+    total_questions: int,
+    wrong_questions: list[dict],
+    wrong_answers: list[dict],
+    relevant_teacher: list[dict],
+    has_teacher_answers: bool,
+) -> str:
+    """Fill the appropriate prompt template for a student."""
+    if has_teacher_answers:
+        return STUDENT_REPORT_PROMPT.format(
+            student_name=student_name,
+            total_questions=total_questions,
+            wrong_count=len(wrong_answers),
+            wrong_questions=json.dumps({"questions": wrong_questions}, ensure_ascii=False, indent=2),
+            wrong_answers=json.dumps(wrong_answers, ensure_ascii=False, indent=2),
+            teacher_answers=json.dumps(relevant_teacher, ensure_ascii=False, indent=2),
+        )
+    else:
+        return STUDENT_REPORT_PROMPT_NO_KEY.format(
+            student_name=student_name,
+            total_questions=total_questions,
+            wrong_questions=json.dumps({"questions": wrong_questions}, ensure_ascii=False, indent=2),
+            wrong_answers=json.dumps(wrong_answers, ensure_ascii=False, indent=2),
+        )
+
+
 def build_student_prompt(
     student: dict,
     questions_data: dict,
@@ -184,21 +234,17 @@ def build_student_prompt(
 ) -> dict:
     """Build the filled prompt for a student (for preview).
 
-    Returns dict with filled_prompt, student_name, total_questions, wrong_count.
+    Returns dict with filled_prompt, student_name, total_questions, wrong_count, has_teacher_answers.
     """
     total_questions = len(questions_data.get("questions", []))
-    wrong_questions, wrong_answers, relevant_teacher = filter_student_wrong_answers(
+    wrong_questions, wrong_answers, relevant_teacher, has_teacher = filter_student_wrong_answers(
         student, questions_data, teacher_answers_data,
     )
     student_name = student.get("name", "Unknown")
 
-    filled = STUDENT_REPORT_PROMPT.format(
-        student_name=student_name,
-        total_questions=total_questions,
-        wrong_count=len(wrong_answers),
-        wrong_questions=json.dumps({"questions": wrong_questions}, ensure_ascii=False, indent=2),
-        wrong_answers=json.dumps(wrong_answers, ensure_ascii=False, indent=2),
-        teacher_answers=json.dumps(relevant_teacher, ensure_ascii=False, indent=2),
+    filled = _fill_student_prompt(
+        student_name, total_questions,
+        wrong_questions, wrong_answers, relevant_teacher, has_teacher,
     )
 
     return {
@@ -206,6 +252,7 @@ def build_student_prompt(
         "student_name": student_name,
         "total_questions": total_questions,
         "wrong_count": len(wrong_answers),
+        "has_teacher_answers": has_teacher,
     }
 
 
@@ -233,13 +280,13 @@ async def generate_student_report(
     client = AsyncOpenAI(api_key=settings.openai_api_key)
 
     total_questions = len(questions_data.get("questions", []))
-    wrong_questions, wrong_answers, relevant_teacher = filter_student_wrong_answers(
+    wrong_questions, wrong_answers, relevant_teacher, has_teacher = filter_student_wrong_answers(
         student, questions_data, teacher_answers_data,
     )
 
     student_name = student.get("name", "Unknown")
 
-    if not wrong_answers:
+    if has_teacher and not wrong_answers:
         # All correct — return a simple congratulations page
         return f"""<!DOCTYPE html>
 <html lang="zh-TW"><head><meta charset="UTF-8"><title>{student_name} - 分析報告</title>
@@ -248,13 +295,9 @@ async def generate_student_report(
 h1{{color:#4ecdc4;margin-bottom:1rem}}p{{color:#94a3b8;font-size:1.1rem}}</style></head>
 <body><div class="card"><h1>🎉 全部答對！</h1><p><strong>{student_name}</strong> 在本次考試中答對了全部 {total_questions} 題，表現優異！</p></div></body></html>"""
 
-    filled_prompt = STUDENT_REPORT_PROMPT.format(
-        student_name=student_name,
-        total_questions=total_questions,
-        wrong_count=len(wrong_answers),
-        wrong_questions=json.dumps({"questions": wrong_questions}, ensure_ascii=False, indent=2),
-        wrong_answers=json.dumps(wrong_answers, ensure_ascii=False, indent=2),
-        teacher_answers=json.dumps(relevant_teacher, ensure_ascii=False, indent=2),
+    filled_prompt = _fill_student_prompt(
+        student_name, total_questions,
+        wrong_questions, wrong_answers, relevant_teacher, has_teacher,
     )
 
     prompt_tokens = _estimate_tokens(STUDENT_REPORT_SYSTEM_PROMPT) + _estimate_tokens(filled_prompt)