# coding=utf-8 """ AI 翻译器模块 对推送内容进行多语言翻译 基于 LiteLLM 统一接口，支持 100+ AI 提供商 """ import json from dataclasses import dataclass, field from pathlib import Path from typing import Any, Dict, List, Optional from trendradar.ai.client import AIClient @dataclass class TranslationResult: """翻译结果""" translated_text: str = "" # 翻译后的文本 original_text: str = "" # 原始文本 success: bool = False # 是否成功 error: str = "" # 错误信息 @dataclass class BatchTranslationResult: """批量翻译结果""" results: List[TranslationResult] = field(default_factory=list) success_count: int = 0 fail_count: int = 0 total_count: int = 0 class AITranslator: """AI 翻译器""" def __init__(self, translation_config: Dict[str, Any], ai_config: Dict[str, Any]): """ 初始化 AI 翻译器 Args: translation_config: AI 翻译配置 (AI_TRANSLATION) ai_config: AI 模型配置（LiteLLM 格式） """ self.translation_config = translation_config self.ai_config = ai_config # 翻译配置 self.enabled = translation_config.get("ENABLED", False) self.target_language = translation_config.get("LANGUAGE", "English") # 创建 AI 客户端（基于 LiteLLM） self.client = AIClient(ai_config) # 加载提示词模板 self.system_prompt, self.user_prompt_template = self._load_prompt_template( translation_config.get("PROMPT_FILE", "ai_translation_prompt.txt") ) def _load_prompt_template(self, prompt_file: str) -> tuple: """加载提示词模板""" config_dir = Path(__file__).parent.parent.parent / "config" prompt_path = config_dir / prompt_file if not prompt_path.exists(): print(f"[翻译] 提示词文件不存在: {prompt_path}") return "", "" content = prompt_path.read_text(encoding="utf-8") # 解析 [system] 和 [user] 部分 system_prompt = "" user_prompt = "" if "[system]" in content and "[user]" in content: parts = content.split("[user]") system_part = parts[0] user_part = parts[1] if len(parts) > 1 else "" if "[system]" in system_part: system_prompt = system_part.split("[system]")[1].strip() user_prompt = user_part.strip() else: user_prompt = content return system_prompt, user_prompt def translate(self, text: str) -> TranslationResult: """ 翻译单条文本 Args: text: 要翻译的文本 Returns: TranslationResult: 翻译结果 """ result = TranslationResult(original_text=text) if not self.enabled: result.error = "翻译功能未启用" return result if not self.client.api_key: result.error = "未配置 AI API Key" return result if not text or not text.strip(): result.translated_text = text result.success = True return result try: # 构建提示词 user_prompt = self.user_prompt_template user_prompt = user_prompt.replace("{target_language}", self.target_language) user_prompt = user_prompt.replace("{content}", text) # 调用 AI API response = self._call_ai(user_prompt) result.translated_text = response.strip() result.success = True except Exception as e: error_type = type(e).__name__ error_msg = str(e) if len(error_msg) > 100: error_msg = error_msg[:100] + "..." result.error = f"翻译失败 ({error_type}): {error_msg}" return result def translate_batch(self, texts: List[str]) -> BatchTranslationResult: """ 批量翻译文本（单次 API 调用） Args: texts: 要翻译的文本列表 Returns: BatchTranslationResult: 批量翻译结果 """ batch_result = BatchTranslationResult(total_count=len(texts)) if not self.enabled: for text in texts: batch_result.results.append(TranslationResult( original_text=text, error="翻译功能未启用" )) batch_result.fail_count = len(texts) return batch_result if not self.client.api_key: for text in texts: batch_result.results.append(TranslationResult( original_text=text, error="未配置 AI API Key" )) batch_result.fail_count = len(texts) return batch_result if not texts: return batch_result # 过滤空文本 non_empty_indices = [] non_empty_texts = [] for i, text in enumerate(texts): if text and text.strip(): non_empty_indices.append(i) non_empty_texts.append(text) # 初始化结果列表 for text in texts: batch_result.results.append(TranslationResult(original_text=text)) # 空文本直接标记成功 for i, text in enumerate(texts): if not text or not text.strip(): batch_result.results[i].translated_text = text batch_result.results[i].success = True batch_result.success_count += 1 if not non_empty_texts: return batch_result try: # 构建批量翻译内容（使用编号格式） batch_content = self._format_batch_content(non_empty_texts) # 构建提示词 user_prompt = self.user_prompt_template user_prompt = user_prompt.replace("{target_language}", self.target_language) user_prompt = user_prompt.replace("{content}", batch_content) # 调用 AI API response = self._call_ai(user_prompt) # 解析批量翻译结果 translated_texts = self._parse_batch_response(response, len(non_empty_texts)) # 填充结果 for idx, translated in zip(non_empty_indices, translated_texts): batch_result.results[idx].translated_text = translated batch_result.results[idx].success = True batch_result.success_count += 1 except Exception as e: error_msg = f"批量翻译失败: {type(e).__name__}: {str(e)[:100]}" for idx in non_empty_indices: batch_result.results[idx].error = error_msg batch_result.fail_count = len(non_empty_indices) return batch_result def _format_batch_content(self, texts: List[str]) -> str: """格式化批量翻译内容""" lines = [] for i, text in enumerate(texts, 1): lines.append(f"[{i}] {text}") return "\n".join(lines) def _parse_batch_response(self, response: str, expected_count: int) -> List[str]: """ 解析批量翻译响应 Args: response: AI 响应文本 expected_count: 期望的翻译数量 Returns: List[str]: 翻译结果列表 """ results = [] lines = response.strip().split("\n") current_idx = None current_text = [] for line in lines: # 尝试匹配 [数字] 格式 stripped = line.strip() if stripped.startswith("[") and "]" in stripped: bracket_end = stripped.index("]") try: idx = int(stripped[1:bracket_end]) # 保存之前的内容 if current_idx is not None: results.append((current_idx, "\n".join(current_text).strip())) current_idx = idx current_text = [stripped[bracket_end + 1:].strip()] except ValueError: if current_idx is not None: current_text.append(line) else: if current_idx is not None: current_text.append(line) # 保存最后一条 if current_idx is not None: results.append((current_idx, "\n".join(current_text).strip())) # 按索引排序并提取文本 results.sort(key=lambda x: x[0]) translated = [text for _, text in results] # 如果解析结果数量不匹配，尝试简单按行分割 if len(translated) != expected_count: # 回退：按行分割（去除编号） translated = [] for line in lines: stripped = line.strip() if stripped.startswith("[") and "]" in stripped: bracket_end = stripped.index("]") translated.append(stripped[bracket_end + 1:].strip()) elif stripped: translated.append(stripped) # 确保返回正确数量 while len(translated) < expected_count: translated.append("") return translated[:expected_count] def _call_ai(self, user_prompt: str) -> str: """调用 AI API（使用 LiteLLM）""" messages = [] if self.system_prompt: messages.append({"role": "system", "content": self.system_prompt}) messages.append({"role": "user", "content": user_prompt}) return self.client.chat(messages)