Initial commit: PastPaper Master full stack

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-21 12:15:35 +07:00
commit 7a09167261
105 changed files with 24799 additions and 0 deletions
--- a/backend/regenerate_analysis.py
+++ b/backend/regenerate_analysis.py
@@ -0,0 +1,69 @@
+"""Re-generate AI trio (knowledge_reminder, ai_hint, solution) in English for existing questions."""
+
+import json
+import asyncio
+from app.services.supabase_client import get_supabase
+from app.services.llm_clients import get_qwen_client
+from app.services.paper_processor import ANALYSIS_PROMPT
+
+
+async def regenerate_for_paper(paper_id: str):
+    sb = get_supabase()
+    qwen = get_qwen_client()
+
+    questions = sb.table("paper_questions").select("*").eq("paper_id", paper_id).order("display_order").execute().data
+    print(f"Found {len(questions)} questions for paper {paper_id[:8]}")
+
+    for q in questions:
+        qnum = q["question_number"]
+        print(f"  Regenerating Q{qnum}...", end=" ", flush=True)
+
+        answer_section = ""
+        if q.get("raw_answer_text"):
+            answer_section = f"- Reference answer: {q['raw_answer_text']}"
+        elif q.get("correct_option"):
+            answer_section = f"- Correct option: {q['correct_option']}"
+        elif q.get("correct_answer"):
+            answer_section = f"- Correct answer: {q['correct_answer']}"
+
+        resp = qwen.chat.completions.create(
+            model="qwen-plus",
+            messages=[
+                {"role": "system", "content": ANALYSIS_PROMPT.format(
+                    question_number=qnum,
+                    question_type=q["question_type"],
+                    score=q.get("score", "unknown"),
+                    question_text=q["question_text"],
+                    topics=", ".join(q.get("topics", [])),
+                    answer_section=answer_section,
+                )},
+            ],
+            temperature=0.3,
+            response_format={"type": "json_object"},
+        )
+        analysis = json.loads(resp.choices[0].message.content)
+
+        sb.table("paper_questions").update({
+            "knowledge_reminder": analysis.get("knowledge_reminder", ""),
+            "ai_hint": analysis.get("ai_hint", ""),
+            "solution": analysis.get("solution", ""),
+        }).eq("id", q["id"]).execute()
+
+        print("done")
+
+    print(f"All questions regenerated for paper {paper_id[:8]}")
+
+
+async def main():
+    sb = get_supabase()
+    papers = sb.table("papers").select("id,course_code,year,term").eq("status", "ready").order("created_at", desc=True).execute().data
+
+    for p in papers:
+        print(f"\n=== {p['course_code']} {p['year']} {p['term']} ===")
+        await regenerate_for_paper(p["id"])
+
+    print("\nAll done!")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())