282 lines
9.4 KiB
Python
282 lines
9.4 KiB
Python
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#!/usr/bin/env python3
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"""
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创建完整的成绩元数据文件
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从 grade.json 或 llm_grade.json 生成 metadata.json
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包含所有详细信息：未通过的测试、各题详情等
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"""
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import json
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import os
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import sys
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import re
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from datetime import datetime
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def extract_student_id():
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"""从环境变量或仓库名中提取学生 ID"""
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# 优先从环境变量获取
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student_id = os.getenv("STUDENT_ID")
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if student_id:
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return student_id
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# 从仓库名提取（格式：hw1-stu_sit001）
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repo = os.getenv("REPO", "")
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if repo:
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# 匹配 hw1-stu_xxxxx 格式
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match = re.search(r'hw\d+-stu[_-]?([^/]+)', repo)
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if match:
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return match.group(1)
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return None
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def extract_assignment_id():
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"""从环境变量或仓库名中提取作业 ID"""
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# 优先从环境变量获取
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assignment_id = os.getenv("ASSIGNMENT_ID")
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if assignment_id:
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return assignment_id
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# 从仓库名提取（格式：hw1-stu_sit001 或 hw1-template）
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repo = os.getenv("REPO", "")
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if repo:
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# 尝试匹配 hwX-stu_ 或 hwX-template
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match = re.search(r'(hw\d+)-(?:stu|template)', repo)
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if match:
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return match.group(1)
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# 如果只是 hwX 格式
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match = re.search(r'(hw\d+)$', repo)
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if match:
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return match.group(1)
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return "hw1" # 默认回退
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def create_grade_metadata(grade_file='grade.json'):
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"""从 grade.json 创建元数据，包含所有详细信息"""
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try:
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with open(grade_file, 'r') as f:
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grade_data = json.load(f)
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assignment_id = extract_assignment_id()
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student_id = extract_student_id()
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language = os.getenv("LANGUAGE", "python")
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# 提取所有相关信息
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final_score = grade_data.get("final_score", grade_data.get("score", 0))
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base_score = grade_data.get("base_score", final_score)
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penalty = grade_data.get("penalty", 0)
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passed = grade_data.get("passed", 0)
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total = grade_data.get("total", 0)
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fails = grade_data.get("fails", [])
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max_score = grade_data.get("max_score", 100)
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test_framework = grade_data.get("test_framework", "pytest")
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coverage = grade_data.get("coverage")
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raw_score = grade_data.get("raw_score")
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# 动态生成 type 字段
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type_map = {
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"python": "programming_python",
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"java": "programming_java",
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"r": "programming_r"
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}
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component_type = type_map.get(language, f"programming_{language}")
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component = {
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"type": component_type,
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"language": language,
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"score": round(final_score, 2),
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"max_score": max_score,
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"details": {
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"passed": passed,
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"total": total,
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"base_score": round(base_score, 2),
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"penalty": round(penalty, 2),
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"coverage": round(coverage, 2) if coverage else None,
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"raw_score": round(raw_score, 2) if raw_score else None,
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"failed_tests": fails,
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"test_framework": test_framework
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}
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}
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metadata = {
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"version": "1.0",
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"assignment": assignment_id,
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"student_id": student_id,
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"components": [component],
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"total_score": round(final_score, 2),
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"total_max_score": max_score,
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"timestamp": datetime.now().isoformat(),
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"generator": "gitea-autograde"
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}
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return metadata
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except Exception as e:
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print(f"Error creating grade metadata: {e}", file=sys.stderr)
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return {}
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def create_llm_metadata(llm_grade_file='artifacts/llm_grade.json'):
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"""从 llm_grade.json 创建元数据，包含所有详细信息"""
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try:
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with open(llm_grade_file, 'r') as f:
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llm_data = json.load(f)
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assignment_id = extract_assignment_id()
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student_id = extract_student_id()
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# 提取聚合后的信息
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total_score = llm_data.get("total_score", llm_data.get("total", 0))
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max_score = llm_data.get("max_score", 30)
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need_review = llm_data.get("need_review", False)
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questions_data = llm_data.get("details", llm_data.get("questions", []))
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# 构建各题详情
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question_details = []
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for i, q_data in enumerate(questions_data, 1):
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q_score = q_data.get("total", q_data.get("score", 0))
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q_max = q_data.get("max_score", 10)
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q_confidence = q_data.get("confidence", 1.0)
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q_flags = q_data.get("flags", [])
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q_need_review = "need_review" in q_flags or q_data.get("need_review", False)
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q_criteria = q_data.get("criteria", [])
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# 规范化 criteria 格式
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formatted_criteria = []
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for crit in q_criteria:
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formatted_criteria.append({
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"id": crit.get("id", ""),
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"score": round(float(crit.get("score", 0)), 2),
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"reason": crit.get("reason", "")
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})
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question_detail = {
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"question_id": f"SA{i}",
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"question_name": q_data.get("question", f"SA{i}"),
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"score": round(float(q_score), 2),
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"max_score": q_max,
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"confidence": round(float(q_confidence), 2),
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"need_review": q_need_review,
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"flags": q_flags,
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"criteria": formatted_criteria
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}
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question_details.append(question_detail)
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component = {
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"type": "llm_essay",
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"score": round(float(total_score), 2),
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"max_score": max_score,
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"details": {
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"questions": len(question_details),
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"need_review": need_review,
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"question_details": question_details
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}
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}
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metadata = {
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"version": "1.0",
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"assignment": assignment_id,
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"student_id": student_id,
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"components": [component],
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"total_score": round(float(total_score), 2),
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"total_max_score": max_score,
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"timestamp": datetime.now().isoformat(),
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"generator": "gitea-autograde"
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}
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return metadata
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except Exception as e:
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print(f"Error creating LLM metadata: {e}", file=sys.stderr)
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return {}
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def create_objective_metadata(objective_file='objective_grade.json'):
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"""从 objective_grade.json 创建元数据"""
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try:
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with open(objective_file, 'r', encoding='utf-8') as f:
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objective_data = json.load(f)
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assignment_id = extract_assignment_id()
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student_id = extract_student_id()
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total_score = objective_data.get("score", 0)
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max_score = objective_data.get("max_score", 0)
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components = objective_data.get("components", [])
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formatted_components = []
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for comp in components:
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comp_type = comp.get("type", "objective")
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formatted_components.append({
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"type": f"objective_{comp_type}",
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"score": comp.get("score", 0),
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"max_score": comp.get("max_score", 0),
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"details": comp.get("details", {})
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})
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if not formatted_components:
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formatted_components.append({
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"type": "objective_total",
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"score": total_score,
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"max_score": max_score,
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"details": {}
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})
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metadata = {
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"version": "1.0",
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"assignment": assignment_id,
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"student_id": student_id,
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"components": formatted_components,
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"total_score": total_score,
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"total_max_score": max_score,
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"timestamp": datetime.now().isoformat(),
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"generator": "gitea-autograde"
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}
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return metadata
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except Exception as e:
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print(f"Error creating objective metadata: {e}", file=sys.stderr)
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return {}
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def main():
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"""主函数"""
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# 检查命令行参数或环境变量
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grade_type = os.getenv("GRADE_TYPE", "programming").lower()
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grade_file_override = os.getenv("GRADE_FILE")
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if grade_type == "llm":
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# LLM 成绩
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llm_file = grade_file_override or "artifacts/llm_grade.json"
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if os.path.exists(llm_file):
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metadata = create_llm_metadata(llm_file)
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elif os.path.exists("llm_grade.json"):
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metadata = create_llm_metadata("llm_grade.json")
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else:
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print(f"Error: {llm_file} not found", file=sys.stderr)
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metadata = {}
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elif grade_type == "objective":
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objective_file = grade_file_override or "objective_grade.json"
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if os.path.exists(objective_file):
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metadata = create_objective_metadata(objective_file)
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else:
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print(f"Error: {objective_file} not found", file=sys.stderr)
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metadata = {}
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else:
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# 编程成绩
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grade_file = grade_file_override or "grade.json"
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if os.path.exists(grade_file):
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metadata = create_grade_metadata(grade_file)
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else:
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print(f"Error: {grade_file} not found", file=sys.stderr)
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metadata = {}
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# 输出到 stdout
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print(json.dumps(metadata, ensure_ascii=False, indent=2))
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if __name__ == "__main__":
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main()
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