Initial commit

skills/quiz-mastery/scripts/import_quiz.py

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+#!/usr/bin/env python3
+"""从题目文件导入题目。
+
+用法：python3 import_quiz.py <file_path> <document_id> <user_id>
+
+输出：JSON 格式的 prompt（system_prompt + user_prompt），由 agent 发给 LLM 解析题目。
+LLM 返回题目 JSON 后，agent 应调用 service.import_questions() 导入。
+"""
+from pathlib import Path
+import json
+import sys
+
+sys.path.append(str(Path(__file__).resolve().parents[1] / "src"))
+
+from quiz_mastery.file_parser import parse_file
+from quiz_mastery.quiz_extractor import build_extraction_prompt
+
+
+def main() -> None:
+    if len(sys.argv) < 4:
+        print("Usage: import_quiz.py <file_path> <document_id> <user_id>")
+        print("  file_path:   Path to question file (.md, .txt, .text)")
+        print("  document_id: Identifier for this document")
+        print("  user_id:     User identifier")
+        sys.exit(1)
+
+    file_path = sys.argv[1]
+    document_id = sys.argv[2]
+    user_id = sys.argv[3]
+
+    content = parse_file(file_path)
+    prompts = build_extraction_prompt(content)
+
+    output = {
+        "action": "import_questions",
+        "document_id": document_id,
+        "user_id": user_id,
+        "file_path": file_path,
+        "prompts": prompts,
+        "instructions": (
+            "Send the system_prompt and user_prompt to an LLM. "
+            "The LLM should return a JSON array of questions. "
+            "Then call service.import_questions(document_id, user_id, questions) to import."
+        ),
+    }
+
+    print(json.dumps(output, ensure_ascii=False, indent=2))
+
+
+if __name__ == "__main__":
+    main()