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e813bd9486
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🤖 Generated with CodeArts Agent
148 lines
4.8 KiB
Python
148 lines
4.8 KiB
Python
# 硅基AI对接
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import requests
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from ..user_init.user_init import get_ai_info_setting
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_LANG_NAME = {
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"zh": "Chinese ",
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"zh_CN": " Chinese ",
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"zh_TW": "Chinese (traditional) ",
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"en": "English ",
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"ja": " Japanese ",
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"ko": "Korean ",
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"fr": "French ",
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"de": " German ",
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"es": "Spanish ",
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"ru": "Russian ",
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"it": " Italian ",
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"pt": "Portuguese",
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}
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def _lang_to_name(code: str) -> str:
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if not code:
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return "Chinese"
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return _LANG_NAME.get(code, code)
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# 硅基AI翻译接口
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async def translateObject(text: str, target_lang_code: str = "zh") -> str:
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ai_info_setting = get_ai_info_setting()
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api_key = ai_info_setting.get("api_key", "")
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base_url = ai_info_setting.get("base_url", "https://api.siliconflow.cn/v1").rstrip(
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"/"
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)
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model = ai_info_setting.get("model", "THUDM/glm-4-9b-chat")
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print(
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"💡[WeiLin-Comfyui-Tools] 硅基AI翻译接口-使用模型：",
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model,
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" 目标语种：",
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target_lang_code,
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" 正在翻译中...",
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)
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url = f"{base_url}/chat/completions"
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target_lang_name = _lang_to_name(target_lang_code)
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# 处理批量翻译：如果文本包含换行符，说明是多个翻译项
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if "\n" in text:
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prompt = f"将以下每一行AI绘画提示词翻译成{target_lang_name}，每行对应一个翻译结果，保持相同的行数和顺序：\n{text}"
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else:
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prompt = f"将以下AI绘画提示词翻译成{target_lang_name}，只输出翻译结果：{text}"
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payload = {
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"model": model,
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"messages": [{"role": "user", "content": prompt}],
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"temperature": 0,
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"stream": False,
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"max_tokens": 4096,
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"enable_thinking": False,
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"thinking_budget": 4096,
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"min_p": 0.05,
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"stop": None,
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"top_p": 0.7,
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"top_k": 50,
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"frequency_penalty": 0.5,
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"n": 1,
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"response_format": {"type": "text"},
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"tools": [],
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}
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# payload = {
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# "model": model,
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# "messages": [
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# {
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# "role": "system",
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# "content": f"ying You are a data translation processing expert, translate the text field of the JSON string data passed by the user into {_lang_to_name(target_lang_code)} (excluding numbers and other special characters, only translate the text) and fill in the corresponding translate field. You only need to return the corresponding JSON string data and do not modify any other data or parameters"
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# },
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# {
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# "content": objectData,
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# "role": "user"
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# }
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# ],
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# "stream": False,
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# "max_tokens": 4096,
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# "enable_thinking": False,
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# "thinking_budget": 4096,
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# "min_p": 0.05,
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# "stop": None,
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# "temperature": 0,
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# "top_p": 0.7,
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# "top_k": 50,
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# "frequency_penalty": 0.5,
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# "n": 1,
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# "response_format": {"type": "json_object"},
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# "tools": []
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# }
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headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
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response = requests.post(url, json=payload, headers=headers, timeout=(10, 60))
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dataResponse = response.json()
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if response.status_code != 200:
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raise RuntimeError(
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f"📌[WeiLin-Comfyui-Tools] 硅基AI接口错误: {response.status_code} {dataResponse}"
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)
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print(
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"💡[WeiLin-Comfyui-Tools] 硅基AI翻译接口-翻译结果：",
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dataResponse["choices"][0]["message"]["content"][:20],
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"...",
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)
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try:
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print(
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f"💡[WeiLin-Comfyui-Tools] 硅基AI翻译接口-翻译完成，以下是使用信息：\n - PromptToken：{dataResponse['usage']['total_tokens']}，\n - CompletionTokens：{dataResponse['usage']['completion_tokens']}，\n - TotalTokens：{dataResponse['usage']['total_tokens']}"
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)
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except KeyError as e:
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print(
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"💡[WeiLin-Comfyui-Tools] 硅基AI翻译接口-使用信息获取失败，可能是接口返回异常，错误信息：",
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str(e),
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)
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print(
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"💡[WeiLin-Comfyui-Tools] 硅基AI翻译接口：",
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dataResponse["choices"][0]["finish_reason"],
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)
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return dataResponse["choices"][0]["message"]["content"]
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# 硅基AI模型列表接口
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def getModelList() -> dict:
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ai_info_setting = get_ai_info_setting()
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api_key = ai_info_setting["api_key"]
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base_url = ai_info_setting["base_url"]
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url = f"{base_url}/models"
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headers = {"Authorization": f"Bearer {api_key}"}
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querystring = {"type": "text"}
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response = requests.get(url, headers=headers, params=querystring)
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if response.status_code != 200:
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raise RuntimeError(
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f"📌[WeiLin-Comfyui-Tools] 硅基AI接口错误: {response.status_code} {response.json()}"
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)
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return response.json()
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