682 lines
25 KiB
Python
682 lines
25 KiB
Python
import os
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import yaml
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import openpyxl
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import requests
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import logging
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from datetime import datetime
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from openpyxl import Workbook
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from openpyxl.styles import Font
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# API配置
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API_KEY = "app-m7XGgbTe3BVHmA1TAYg9Ec4v" # Dify API Key
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WORKFLOW_ID = os.getenv("DIFY_WORKFLOW_ID", "your-workflow-id-here") # 工作流ID
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API_BASE_URL = "http://192.168.100.143/v1" # API基础地址
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FILE_UPLOAD_URL = f"{API_BASE_URL}/files/upload" # 文件上传地址
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EXCEL_PATH = "ai作业/AI考试作业.xlsx"
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ASSIGNMENT_DIR = "ai作业/作业"
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OUTPUT_DIR = "results"
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OUTPUT_FILE = os.path.join(OUTPUT_DIR, "批改结果.xlsx")
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# 日志配置
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LOG_DIR = os.path.join(OUTPUT_DIR, "logs")
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os.makedirs(LOG_DIR, exist_ok=True)
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LOG_FILE = os.path.join(LOG_DIR, f"grading_log_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log")
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler(LOG_FILE),
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logging.StreamHandler()
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]
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)
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logger = logging.getLogger(__name__)
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# 确保输出目录存在
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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def read_excel_submissions():
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"""读取Excel中的作业提交记录"""
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wb = openpyxl.load_workbook(EXCEL_PATH)
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ws = wb.active
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submissions = []
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# 获取标题行确定列索引
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headers = [cell.value for cell in ws[1]]
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name_col = headers.index('填写人')
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workflow_col = headers.index('工作流程描述')
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solution_col = headers.index('Dify工作流解决方案设计')
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for row in ws.iter_rows(min_row=2, values_only=True):
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if len(row) > max(name_col, workflow_col, solution_col): # 确保有足够列
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submissions.append({
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'name': row[name_col],
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'work_description': row[workflow_col],
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'solution': row[solution_col]
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})
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return submissions
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def check_yml_files(submissions):
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"""检查Excel中的提交记录是否有对应的YML文件"""
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missing_files = []
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for sub in submissions:
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yml_path = find_assignment_yml(sub['name'])
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if not yml_path:
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missing_files.append(sub['name'])
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if missing_files:
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print("\n以下提交记录缺少对应的YML文件:")
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for name in missing_files:
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print(f"- {name}")
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def find_assignment_yml(name):
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"""根据姓名查找对应的YML作业文件"""
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for filename in os.listdir(ASSIGNMENT_DIR):
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if filename.endswith('.yml'): # 仅支持.yml格式
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# 从文件名中提取姓名部分(第二个下划线分隔的部分)
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parts = filename.split('_')
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if len(parts) >= 2:
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# 处理可能存在的@符号
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student_name = parts[1].split('@')[0]
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if name == student_name:
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return os.path.join(ASSIGNMENT_DIR, filename)
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return None
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def parse_yml_file(yml_path):
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"""解析YML文件内容"""
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with open(yml_path, 'r', encoding='utf-8') as f:
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return yaml.safe_load(f)
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def call_dify_api(yml_path, assignment_data):
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"""调用Dify API进行作业批改，上传YML文件"""
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# 先上传文件
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upload_headers = {
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"Authorization": f"Bearer {API_KEY}"
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}
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upload_data = {
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"user": "ai-grading-system",
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"type": "yml" # 自定义文件类型
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}
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try:
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# 上传文件
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with open(yml_path, 'rb') as f:
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files = {'file': (os.path.basename(yml_path), f, 'text/plain')}
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upload_response = requests.post(
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FILE_UPLOAD_URL,
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headers=upload_headers,
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files=files,
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data=upload_data
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)
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upload_response.raise_for_status()
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file_id = upload_response.json().get('id')
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if not file_id:
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print("文件上传失败: 未获取到文件ID")
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return None
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# 执行工作流
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run_url = f"{API_BASE_URL}/workflows/run"
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run_headers = {
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"Authorization": f"Bearer {API_KEY}",
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"Content-Type": "application/json"
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}
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run_data = {
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"inputs": {
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"yml_file": {
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"transfer_method": "local_file",
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"upload_file_id": file_id,
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"type": "custom"
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},
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"work_description": assignment_data.get('work_description', ''),
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"solution": assignment_data.get('solution', '')
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},
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"response_mode": "blocking",
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"user": "ai-grading-system"
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}
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response = requests.post(run_url, headers=run_headers, json=run_data)
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response.raise_for_status()
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return response.json()
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except requests.exceptions.RequestException as e:
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print(f"API调用失败: {e}")
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return None
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def save_result(result, wb=None, is_regrade=False):
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"""保存单个批改结果到Excel
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Args:
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result: 批改结果字典
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wb: 工作簿对象(可选)
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is_regrade: 是否为复批(默认False)
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"""
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try:
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# 根据是否为复批确定输出文件路径
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output_file = os.path.join(OUTPUT_DIR, "复批结果.xlsx") if is_regrade else OUTPUT_FILE
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# 如果工作簿不存在则创建
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if wb is None:
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wb = Workbook()
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ws = wb.active
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ws.title = "复批结果" if is_regrade else "批改结果"
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# 添加表头
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headers = ["姓名", "评分", "评分详情"]
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ws.append(headers)
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# 设置表头样式
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for cell in ws[1]:
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cell.font = Font(bold=True)
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else:
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ws = wb.active
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# 格式化详情
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details = result.get('details', {})
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if isinstance(details, dict):
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formatted_details = []
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# 添加总分
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formatted_details.append(f"总分: {details.get('total_score', 0)}分")
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# 添加各部分评分
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for section, data in details.get('sections', {}).items():
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formatted_details.append(f"\n{section} ({data.get('score', 0)}分)")
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# 添加优点
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if details.get('advantages'):
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formatted_details.append("\n优点:")
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formatted_details.extend([f"- {adv}" for adv in details['advantages']])
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# 添加不足
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if details.get('disadvantages'):
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formatted_details.append("\n不足之处:")
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formatted_details.extend([f"- {dis}" for dis in details['disadvantages']])
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# 添加建议
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if details.get('suggestions'):
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formatted_details.append("\n改进建议:")
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formatted_details.extend([f"- {sug}" for sug in details['suggestions']])
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details_text = "\n".join(formatted_details)
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else:
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details_text = str(details)
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# 添加数据行
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try:
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# 确保details是字符串格式
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if isinstance(details_text, dict):
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details_text = str(details_text)
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ws.append([
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result['name'],
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result.get('score', 'N/A'),
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details_text
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])
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except Exception as e:
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print(f"添加数据行失败: {e}")
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# 尝试简化格式保存
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ws.append([
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result['name'],
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result.get('score', 'N/A'),
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str(result.get('details', ''))[:32767] # Excel单元格最大长度限制
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])
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# 自动调整列宽
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for column in ws.columns:
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max_length = 0
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column = [cell for cell in column]
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for cell in column:
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try:
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if len(str(cell.value)) > max_length:
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max_length = len(cell.value)
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except:
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pass
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adjusted_width = (max_length + 2) * 1.2
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ws.column_dimensions[column[0].column_letter].width = adjusted_width
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# 保存到文件
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temp_file = output_file + ".tmp"
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wb.save(temp_file)
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if os.path.exists(output_file):
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os.remove(output_file)
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os.rename(temp_file, output_file)
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return wb
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except Exception as e:
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print(f"保存结果失败: {e}")
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raise
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def log_api_result(name, response, score=None):
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"""记录API请求结果到日志文件"""
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try:
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status = "成功" if response and isinstance(response, dict) else "失败"
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data = response.get('data', {}) if response else {}
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outputs = data.get('outputs', {}) if data else {}
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logger.info(
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f"学生: {name} - API请求{status}\n"
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f"评分: {score}\n"
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f"API响应摘要: {str(outputs.get('text', '无响应文本'))[:200]}...\n"
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f"完整响应: {str(response)[:500]}..."
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)
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except Exception as e:
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logger.error(f"记录API结果失败: {e}")
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def parse_api_response(response):
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"""解析API返回的评分结果"""
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import re # 添加正则表达式支持
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# 直接从response.data中获取评分数据
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if not response or not isinstance(response, dict):
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return None, "无效的API响应"
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data = response.get('data', {})
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outputs = data.get('outputs', {})
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text = outputs.get('text', '')
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if not text:
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return None, "无评分结果"
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# 初始化结果字典
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result = {
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'total_score': 0,
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'sections': {},
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'advantages': [],
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'disadvantages': [],
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'suggestions': []
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}
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try:
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# 提取总分 - 改进匹配逻辑
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total_score_match = re.search(r'### 总分[：:]\s*(\d+)分', text)
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if total_score_match:
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try:
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result['total_score'] = int(total_score_match.group(1))
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except (ValueError, AttributeError):
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result['total_score'] = 0
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# 提取各部分评分
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sections = [
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('工作流描述', r'#### 1\. 工作流描述是否能够覆盖自己提出的问题.*?\*\*评分[：:]\s*(\d+)分'),
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('YML文件', r'#### 2\. YML文件是否符合Dify工作流的设计标准且能实现自己提出的工作流功能.*?\*\*评分[：:]\s*(\d+)分'),
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('实用性', r'#### 3\. 工作流的实用性、可重复性和可推广性.*?\*\*评分[：:]\s*(\d+)分')
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]
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for name, pattern in sections:
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section_match = re.search(pattern, text, re.DOTALL)
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if section_match:
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section_text = section_match.group(0)
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try:
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score = int(section_match.group(1))
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result['sections'][name] = {
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'score': score,
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'analysis': '\n'.join(section_text.split('\n')[2:]).strip()
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}
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except (ValueError, AttributeError, IndexError):
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result['sections'][name] = {
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'score': 0,
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'analysis': '\n'.join(section_text.split('\n')[2:]).strip()
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}
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# 提取优点
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adv_start = text.find("### 优点")
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if adv_start != -1:
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adv_end = text.find("### 不足之处", adv_start)
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advantages = text[adv_start+5:adv_end].strip().split('\n')[1:]
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result['advantages'] = [a.strip()[3:] for a in advantages if a.strip()]
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# 提取不足
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dis_start = text.find("### 不足之处")
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if dis_start != -1:
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dis_end = text.find("### 改进建议", dis_start)
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disadvantages = text[dis_start+7:dis_end].strip().split('\n')[1:]
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result['disadvantages'] = [d.strip()[3:] for d in disadvantages if d.strip()]
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# 提取改进建议
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sug_start = text.find("### 改进建议")
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if sug_start != -1:
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sug_end = text.find("\n\n", sug_start)
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suggestions = text[sug_start+7:sug_end].strip().split('\n')[1:]
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result['suggestions'] = [s.strip()[3:] for s in suggestions if s.strip()]
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return result['total_score'], result
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except Exception as e:
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print(f"解析评分结果出错: {e}")
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return None, f"解析评分结果出错: {e}"
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def get_graded_students():
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"""获取已批改的学生名单"""
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if not os.path.exists(OUTPUT_FILE):
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return set()
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try:
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wb = openpyxl.load_workbook(OUTPUT_FILE)
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ws = wb.active
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graded_students = set()
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for row in ws.iter_rows(min_row=2, values_only=True):
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if row and row[0]: # 第一列为姓名
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graded_students.add(row[0])
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return graded_students
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except Exception as e:
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print(f"读取已批改名单失败: {e}")
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return set()
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def regrade_zero_scores():
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"""复批0分作业"""
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print("\n开始复批0分作业...")
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# 检查原始结果文件是否存在
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if not os.path.exists(OUTPUT_FILE):
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print("❌ 未找到原始批改结果文件，无法进行复批")
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return
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try:
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# 读取原始结果
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original_wb = openpyxl.load_workbook(OUTPUT_FILE)
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original_ws = original_wb.active
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# 初始化复批工作簿
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regrade_wb = None
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# 查找0分记录
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zero_count = 0
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for row in original_ws.iter_rows(min_row=2, values_only=True):
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name, score, details = row[0], row[1], row[2]
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if score == 0:
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zero_count += 1
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print(f"\n发现0分记录: {name}")
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# 查找YML文件
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yml_path = find_assignment_yml(name)
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if not yml_path:
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print(f"⚠️ 未找到 {name} 的作业文件，保持0分")
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result = {
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'name': name,
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'score': 0,
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'details': details
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}
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regrade_wb = save_result(result, regrade_wb, is_regrade=True)
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continue
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# 解析YML文件
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try:
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print(f"解析YML文件: {os.path.basename(yml_path)}")
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yml_content = parse_yml_file(yml_path)
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except Exception as e:
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print(f"❌ 解析YML文件失败: {e}")
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result = {
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'name': name,
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'score': 0,
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'details': f'YML文件解析失败: {str(e)}'
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}
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regrade_wb = save_result(result, regrade_wb, is_regrade=True)
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continue
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# 准备API调用数据
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assignment_data = {
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'name': name,
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**yml_content
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}
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# 调用API进行复批
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print("调用Dify API进行复批...")
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api_response = call_dify_api(yml_path, assignment_data)
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if not api_response:
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logger.error(f"{name} - 复批API调用失败")
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print(f"❌ {name} 复批失败")
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result = {
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'name': name,
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'score': 0,
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'details': '复批API调用失败'
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}
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regrade_wb = save_result(result, regrade_wb, is_regrade=True)
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continue
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# 解析API响应
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try:
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score, new_details = parse_api_response(api_response)
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print(f"✅ {name} 复批完成 - 新得分: {score}")
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logger.info(f"{name} - 复批完成，新得分: {score}")
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log_api_result(name, api_response, score)
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# 使用save_result保存复批结果
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result = {
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'name': name,
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'score': score,
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'details': new_details
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}
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regrade_wb = save_result(result, regrade_wb, is_regrade=True)
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except Exception as e:
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print(f"❌ 解析API响应失败: {e}")
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result = {
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'name': name,
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'score': 0,
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'details': f'复批结果解析失败: {str(e)}'
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}
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regrade_wb = save_result(result, regrade_wb, is_regrade=True)
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# 保存复批结果
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if zero_count > 0:
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print(f"\n✅ 共复批{zero_count}份0分作业")
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else:
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print("\n没有发现0分记录需要复批")
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except Exception as e:
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print(f"\n❌ 复批流程出现错误: {e}")
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raise
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def regrade_100_scores():
|
||
"""复批0分作业"""
|
||
print("\n开始复批100分作业...")
|
||
|
||
# 检查原始结果文件是否存在
|
||
if not os.path.exists(OUTPUT_FILE):
|
||
print("❌ 未找到原始批改结果文件，无法进行复批")
|
||
return
|
||
|
||
try:
|
||
# 读取原始结果
|
||
original_wb = openpyxl.load_workbook(OUTPUT_FILE)
|
||
original_ws = original_wb.active
|
||
|
||
# 初始化复批工作簿
|
||
regrade_wb = None
|
||
|
||
# 查找100分记录
|
||
zero_count = 0
|
||
for row in original_ws.iter_rows(min_row=2, values_only=True):
|
||
name, score, details = row[0], row[1], row[2]
|
||
|
||
if score == 100:
|
||
zero_count += 1
|
||
print(f"\n发现100分记录: {name}")
|
||
|
||
# 查找YML文件
|
||
yml_path = find_assignment_yml(name)
|
||
if not yml_path:
|
||
print(f"⚠️ 未找到 {name} 的作业文件，保持0分")
|
||
result = {
|
||
'name': name,
|
||
'score': 0,
|
||
'details': details
|
||
}
|
||
regrade_wb = save_result(result, regrade_wb, is_regrade=True)
|
||
continue
|
||
|
||
# 解析YML文件
|
||
try:
|
||
print(f"解析YML文件: {os.path.basename(yml_path)}")
|
||
yml_content = parse_yml_file(yml_path)
|
||
except Exception as e:
|
||
print(f"❌ 解析YML文件失败: {e}")
|
||
result = {
|
||
'name': name,
|
||
'score': 0,
|
||
'details': f'YML文件解析失败: {str(e)}'
|
||
}
|
||
regrade_wb = save_result(result, regrade_wb, is_regrade=True)
|
||
continue
|
||
|
||
# 准备API调用数据
|
||
assignment_data = {
|
||
'name': name,
|
||
**yml_content
|
||
}
|
||
|
||
# 调用API进行复批
|
||
print("调用Dify API进行复批...")
|
||
api_response = call_dify_api(yml_path, assignment_data)
|
||
if not api_response:
|
||
logger.error(f"{name} - 复批API调用失败")
|
||
print(f"❌ {name} 复批失败")
|
||
result = {
|
||
'name': name,
|
||
'score': 0,
|
||
'details': '复批API调用失败'
|
||
}
|
||
regrade_wb = save_result(result, regrade_wb, is_regrade=True)
|
||
continue
|
||
|
||
# 解析API响应
|
||
try:
|
||
score, new_details = parse_api_response(api_response)
|
||
print(f"✅ {name} 复批完成 - 新得分: {score}")
|
||
logger.info(f"{name} - 复批完成，新得分: {score}")
|
||
log_api_result(name, api_response, score)
|
||
|
||
# 使用save_result保存复批结果
|
||
result = {
|
||
'name': name,
|
||
'score': score,
|
||
'details': new_details
|
||
}
|
||
regrade_wb = save_result(result, regrade_wb, is_regrade=True)
|
||
except Exception as e:
|
||
print(f"❌ 解析API响应失败: {e}")
|
||
result = {
|
||
'name': name,
|
||
'score': 0,
|
||
'details': f'复批结果解析失败: {str(e)}'
|
||
}
|
||
regrade_wb = save_result(result, regrade_wb, is_regrade=True)
|
||
|
||
# 保存复批结果
|
||
if zero_count > 0:
|
||
print(f"\n✅ 共复批{zero_count}份100分作业")
|
||
else:
|
||
print("\n没有发现100分记录需要复批")
|
||
|
||
except Exception as e:
|
||
print(f"\n❌ 复批流程出现错误: {e}")
|
||
raise
|
||
|
||
def main():
|
||
"""主函数，执行作业批改流程"""
|
||
print("\n请选择批改模式:")
|
||
print("1. 全部批改(包括未批改和0分复批)")
|
||
print("2. 仅复批0分作业")
|
||
print("3. 仅复批100分作业")
|
||
|
||
while True:
|
||
choice = input("请输入选择(1/2/3): ").strip()
|
||
if choice in ('1', '2', '3'):
|
||
break
|
||
print("无效输入，请重新选择")
|
||
|
||
if choice == '2':
|
||
# 仅执行复批
|
||
regrade_zero_scores()
|
||
return
|
||
|
||
if choice == '3':
|
||
# 仅执行复批
|
||
regrade_100_scores()
|
||
return
|
||
|
||
print("\n开始批改作业...")
|
||
|
||
try:
|
||
# 读取Excel中的作业提交
|
||
print("读取Excel提交记录...")
|
||
submissions = read_excel_submissions()
|
||
|
||
# 获取已批改学生名单
|
||
graded_students = get_graded_students()
|
||
print(f"共找到{len(submissions)}份提交记录")
|
||
|
||
# 检查YML文件是否存在(不再阻止批改流程)
|
||
check_yml_files(submissions)
|
||
|
||
total_count = len(submissions)
|
||
processed_count = 0
|
||
wb = None # 初始化工作簿对象
|
||
|
||
for sub in submissions:
|
||
processed_count += 1
|
||
print(f"\n[{processed_count}/{total_count}] 正在处理: {sub['name']}")
|
||
|
||
# 检查是否已批改过
|
||
if sub['name'] in graded_students:
|
||
print(f"⏩ {sub['name']} 已批改过，跳过")
|
||
continue
|
||
|
||
# 准备结果字典
|
||
result = {
|
||
'name': sub['name'],
|
||
'score': 0,
|
||
'details': ''
|
||
}
|
||
|
||
# 查找对应的YML文件
|
||
yml_path = find_assignment_yml(sub['name'])
|
||
if not yml_path:
|
||
print(f"⚠️ 未找到 {sub['name']} 的作业文件，自动评为0分")
|
||
result['details'] = '未提交YML作业文件'
|
||
wb = save_result(result, wb)
|
||
continue
|
||
|
||
# 解析YML文件
|
||
try:
|
||
print(f"解析YML文件: {os.path.basename(yml_path)}")
|
||
yml_content = parse_yml_file(yml_path)
|
||
except Exception as e:
|
||
print(f"❌ 解析YML文件失败: {e}")
|
||
result['details'] = f'YML文件解析失败: {str(e)}'
|
||
wb = save_result(result, wb)
|
||
continue
|
||
|
||
# 准备API调用数据
|
||
assignment_data = {
|
||
**sub,
|
||
**yml_content
|
||
}
|
||
|
||
# 调用API进行批改(上传YML文件)
|
||
print("调用Dify API进行批改...")
|
||
api_response = call_dify_api(yml_path, assignment_data)
|
||
if not api_response:
|
||
logger.error(f"{sub['name']} - API调用失败")
|
||
print(f"❌ {sub['name']} 批改失败")
|
||
result['details'] = 'API调用失败'
|
||
wb = save_result(result, wb)
|
||
continue
|
||
|
||
# 解析API响应
|
||
try:
|
||
score, details = parse_api_response(api_response)
|
||
result['score'] = score
|
||
result['details'] = details
|
||
logger.info(f"{sub['name']} - 批改完成，得分: {score}")
|
||
print(f"✅ {sub['name']} 批改完成 - 得分: {score}")
|
||
log_api_result(sub['name'], api_response, score)
|
||
wb = save_result(result, wb)
|
||
except Exception as e:
|
||
print(f"❌ 解析API响应失败: {e}")
|
||
result['details'] = f'结果解析失败: {str(e)}'
|
||
wb = save_result(result, wb)
|
||
|
||
print(f"\n✅ 所有{total_count}份作业批改完成")
|
||
print(f"批改结果已实时保存到: {OUTPUT_FILE}")
|
||
|
||
except Exception as e:
|
||
print(f"\n❌ 批改流程出现严重错误: {e}")
|
||
raise
|
||
|
||
if __name__ == "__main__":
|
||
main()
|