2025-04-17 11:05:46 +08:00
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import re
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import json
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import os
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2025-04-22 15:02:00 +08:00
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import traceback # Import traceback for better error logging
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2025-04-26 12:08:40 +08:00
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from datetime import datetime
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2025-04-17 11:05:46 +08:00
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class TopicParser:
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"""选题解析器类,负责解析和处理选题"""
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@staticmethod
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2025-04-26 12:08:40 +08:00
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def parse_topics(result, run_id=None):
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2025-04-22 15:02:00 +08:00
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"""解析 AI 返回的 JSON 格式的选题列表"""
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2025-04-26 12:08:40 +08:00
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# 如果没有提供run_id,生成一个新的
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if run_id is None:
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run_id = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
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# 保存原始LLM响应
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save_dir = os.path.join("result", run_id)
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os.makedirs(save_dir, exist_ok=True)
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raw_response_path = os.path.join(save_dir, f"raw_llm_response_{run_id}.txt")
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try:
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with open(raw_response_path, "w", encoding="utf-8") as f:
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f.write(result)
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print(f"原始LLM响应已保存到:{raw_response_path}")
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except Exception as e:
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print(f"保存原始LLM响应失败:{e}")
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2025-04-22 15:12:46 +08:00
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# --- Debug: Print raw input ---
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print("--- Raw Input to parse_topics ---")
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print(repr(result)) # Use repr() to see special characters like \n
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print("--- End Raw Input ---")
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# --- End Debug ---
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2025-04-22 15:02:00 +08:00
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print("\n开始解析 JSON 格式的选题结果...")
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result_list = []
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try:
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# --- Try to remove <think> block first ---
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potential_json_part = result # Start with the original result
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if "</think>" in result:
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parts = result.split("</think>", 1) # Split only once
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if len(parts) > 1:
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print("检测到并移除了 '</think>' 标签前的部分。")
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potential_json_part = parts[1] # Take the part after </think>
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# --- End of <think> removal ---
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# 尝试直接将结果(或</think>之后的部分)解析为 JSON
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# 先移除可能的Markdown代码块标记 ```json ... ```
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cleaned_result = re.sub(r'^```json\s*|\s*```$', '', potential_json_part.strip(), flags=re.MULTILINE) # Apply to potential_json_part
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if not cleaned_result: # Handle case where everything was removed
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print("错误:移除 <think> 和/或 markdown 标记后内容为空。")
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return []
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2025-04-22 15:02:00 +08:00
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parsed_json = json.loads(cleaned_result)
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# 验证解析结果是否为列表
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if isinstance(parsed_json, list):
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print(f"成功解析 JSON,包含 {len(parsed_json)} 个潜在选题。")
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required_keys = {"index", "date", "logic", "object", "product", "product_logic", "style", "style_logic", "target_audience", "target_audience_logic"}
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for i, item in enumerate(parsed_json):
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# 验证每个元素是否为字典并包含所有必需的键
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if isinstance(item, dict) and required_keys.issubset(item.keys()):
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# 可以添加更细致的类型验证,例如检查 'index' 是否为数字字符串等
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# 确保所有值都是字符串,以防 AI 返回非字符串类型
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valid_item = {str(k): str(v) for k, v in item.items()}
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# 添加 'error' 字段以兼容旧接口(如果需要)
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valid_item['error'] = False
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result_list.append(valid_item)
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else:
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print(f"警告: 第 {i+1} 个元素不是有效选题对象或缺少键: {item}")
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else:
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print(f"错误: 解析结果不是一个 JSON 数组 (List)。实际类型: {type(parsed_json)}")
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except json.JSONDecodeError as e:
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print(f"错误: 解析 JSON 失败 - {e}")
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print("------ 无法解析的原始文本 (After potential <think> removal) ------")
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print(potential_json_part) # Print the part we tried to parse
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print("-------------------------------")
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# 在失败时返回空列表
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return []
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except Exception as e: # Catch other potential errors
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print(f"解析选题时发生意外错误: {e}")
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traceback.print_exc()
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return []
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print(f"最终成功解析选题数量:{len(result_list)}")
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# (可选)保留索引重新分配逻辑,处理 AI 可能生成的无效或重复索引
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if result_list:
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print("重新分配和验证选题索引...")
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used_indices = set()
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# 第一步:尝试解析已有的index,如果是有效数字则保留
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for item in result_list:
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raw_index = item.get('index', '')
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try:
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index_value = int(raw_index.strip())
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if index_value in used_indices:
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item['index'] = None # Mark for reassignment
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else:
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item['index'] = str(index_value) # Keep valid, unique index
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used_indices.add(index_value)
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except (ValueError, TypeError):
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item['index'] = None # Mark for reassignment
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# 第二步:为所有无效或重复的index分配新值
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next_available_index = 1
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for item in result_list:
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if item.get('index') is None:
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while next_available_index in used_indices:
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next_available_index += 1
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item['index'] = str(next_available_index)
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used_indices.add(next_available_index)
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next_available_index += 1
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print("选题索引已重新分配完毕。")
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return result_list
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@staticmethod
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def save_topics(result_list, output_dir, run_id, result=None): # result is optional now
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"""保存解析后的选题到JSON文件"""
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os.makedirs(output_dir, exist_ok=True)
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json_path = os.path.join(output_dir, f"tweet_topic_{run_id}.json") # Consistent naming with README?
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try:
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with open(json_path, "w", encoding="utf-8") as f:
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json.dump(result_list, f, ensure_ascii=False, indent=4)
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print(f"选题结果已保存到: {json_path}")
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return True, json_path
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except Exception as e:
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print(f"错误: 保存选题 JSON 文件失败 - {e}")
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traceback.print_exc()
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# Log raw result if saving fails and result was provided
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if result:
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error_log_file = os.path.join(output_dir, f"error_log_{run_id}.txt")
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try:
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with open(error_log_file, "w", encoding="utf-8") as f:
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f.write("无法解析或保存选题,原始内容如下:\n\n")
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f.write(result)
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print(f"原始 AI 输出已记录到: {error_log_file}")
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except Exception as log_e:
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print(f"错误: 记录原始输出失败 - {log_e}")
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return False, None
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2025-04-17 11:05:46 +08:00
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@staticmethod
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def load_topics_from_json(json_path):
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"""从JSON文件加载选题列表"""
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try:
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with open(json_path, "r", encoding="utf-8") as f:
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topics_list = json.load(f)
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# Basic validation
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if isinstance(topics_list, list):
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print(f"从 {json_path} 加载了 {len(topics_list)} 个选题。")
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return topics_list
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else:
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print(f"错误: {json_path} 中的内容不是一个有效的 JSON 数组。")
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return None
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except FileNotFoundError:
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print(f"错误: 找不到选题文件 {json_path}")
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return None
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except json.JSONDecodeError as e:
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print(f"错误: 解析选题文件 {json_path} 失败 - {e}")
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return None
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except Exception as e:
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print(f"加载选题文件时发生意外错误: {e}")
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traceback.print_exc()
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return None
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