75 lines
3.0 KiB
Python
75 lines
3.0 KiB
Python
from typing import Any, Dict
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import traceback
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class LLMClient:
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"""轻量LLM客户端。
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kind: local | service | ollama
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config: 保存与调用所需的最小配置信息
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"""
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def __init__(self, kind: str, config: Dict[str, Any]):
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self.kind = kind
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self.config = config or {}
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def translate(self, text: str, target_language: str, system_prompt: str = "") -> str:
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"""翻译文本到目标语言"""
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# Service类型：使用真实的API connector
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if self.kind == "service" and self.config.get("connector"):
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try:
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# 构建翻译指令的messages
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lang_map = {
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"英语": "English",
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"中文": "Chinese",
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"日语": "Japanese",
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"韩语": "Korean",
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"法语": "French",
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"德语": "German",
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"西班牙语": "Spanish",
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"意大利语": "Italian",
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"俄语": "Russian",
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"葡萄牙语": "Portuguese",
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}
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target_lang = lang_map.get(target_language, target_language)
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# 使用system_prompt（优先使用传入的，否则使用config中的）
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sys_prompt = system_prompt or self.config.get("system_prompt") or "You are a translation engine. Only output the translated text."
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messages = [
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{"role": "system", "content": sys_prompt},
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{"role": "user", "content": f"Translate the following text to {target_lang}. Keep the meaning and style.\n\n{text}"}
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]
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# 调用真实API
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return self.config["connector"].invoke(messages)
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except Exception as e:
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error_msg = f"LLM API调用失败: {str(e)}"
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print(error_msg)
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print(traceback.format_exc())
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return error_msg
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# Ollama类型：占位实现（可扩展为实际调用）
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elif self.kind == "ollama":
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# TODO: 实现Ollama API调用
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host = self.config.get("host", "localhost:11434")
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model = self.config.get("model", "unknown")
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return f"[Ollama {host}/{model}] -> {target_language}: {text}"
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# Local类型：占位实现（可扩展为实际模型加载）
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elif self.kind == "local":
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# TODO: 实现本地模型加载与推理
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path = self.config.get("path", "unknown")
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return f"[Local {path}] -> {target_language}: {text}"
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# 未知类型或无connector：返回占位结果
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else:
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provider = self.config.get("provider") or self.kind
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model = self.config.get("model") or self.config.get("path") or self.config.get("host") or "unknown"
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return f"[LLM {provider}/{model}] -> {target_language}: {text}"
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