116 lines
3.5 KiB
Python
Executable File
116 lines
3.5 KiB
Python
Executable File
from __future__ import annotations
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import json
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from .models import Question
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def build_extraction_prompt(content: str) -> dict:
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"""Build a prompt for LLM to parse questions from a question file.
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Args:
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content: Raw text content containing questions.
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Returns:
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dict with 'system_prompt' and 'user_prompt' keys.
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"""
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system_prompt = (
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"你是一个专业的题目解析助手。从用户提供的题目文件中识别并解析所有题目。\n"
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"严格按照要求的 JSON 格式输出，不要输出任何其他内容。"
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)
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user_prompt = f"""请从以下题目文件内容中解析出所有题目。
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## 题目文件内容
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{content}
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## 解析要求
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1. 识别每道题的类型：
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- single_choice: 选择题（有 A/B/C/D 等选项）
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- true_false: 判断题（判断对错）
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- fill_blank: 填空题（有空格需要填写）
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- short_answer: 简答题（需要文字回答）
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2. 提取题目的所有信息
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3. 如果题目有答案和解析，也一并提取
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4. 为每道题分配唯一 ID
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## 输出格式
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输出纯 JSON 数组，每个元素格式如下：
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```json
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[
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{{
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"id": "q_001",
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"knowledge_point_ids": [],
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"level": 1,
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"type": "single_choice",
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"prompt": "题目内容",
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"options": ["A. 选项一", "B. 选项二", "C. 选项三", "D. 选项四"],
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"answer": "A",
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"explanation": "解析内容（如果有）"
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}}
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]
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```
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注意：
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- type 必须是 single_choice, true_false, fill_blank, short_answer 之一
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- 选择题的 answer 填选项字母（A/B/C/D）
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- 判断题的 answer 填 "True" 或 "False"
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- 填空题的 answer 填正确答案文本
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- 简答题的 answer 填参考答案（如果有）
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- 如果无法确定 knowledge_point_ids，留空数组
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- level 默认为 1，如果能从题目难度判断则相应调整
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请直接输出 JSON 数组，不要包含 markdown 代码块标记或其他文字。"""
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return {
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"system_prompt": system_prompt,
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"user_prompt": user_prompt,
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}
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def parse_questions_json(json_str: str) -> list[Question]:
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"""Parse LLM-returned JSON string into a list of Question objects.
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Args:
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json_str: JSON string containing a list of question dicts.
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Returns:
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List of Question objects.
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Raises:
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json.JSONDecodeError: If json_str is not valid JSON.
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ValueError: If the parsed data is not a list.
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"""
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# Try to extract JSON from possible markdown code blocks
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cleaned = json_str.strip()
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if cleaned.startswith("```"):
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# Remove markdown code block markers
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lines = cleaned.split("\n")
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# Remove first line (```json or ```)
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lines = lines[1:]
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# Remove last line (```)
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if lines and lines[-1].strip() == "```":
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lines = lines[:-1]
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cleaned = "\n".join(lines)
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data = json.loads(cleaned)
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if not isinstance(data, list):
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raise ValueError(f"Expected a JSON array, got {type(data).__name__}")
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questions: list[Question] = []
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for item in data:
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q = Question(
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id=item.get("id", "q_unknown"),
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knowledge_point_ids=item.get("knowledge_point_ids", []),
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level=item.get("level", 1),
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type=item.get("type", "single_choice"),
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prompt=item.get("prompt", ""),
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options=item.get("options", []),
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answer=item.get("answer"),
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explanation=item.get("explanation", ""),
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source_refs=item.get("source_refs", []),
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)
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questions.append(q)
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return questions
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