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* 跳过使用Open ai 接口时，DeepSeek-R1 模型的深度思考内容 (#54) * 跳过 DeepSeek-R1 模型的深度思考内容 * 跳过 DeepSeek-R1 模型的深度思考内容 * 新增LM Studio本地大模型API接口 * 优化代码，遇到Bad Case安全处理 * update:优化 --------- Co-authored-by: Sinyo <38577585+SinyoWong@users.noreply.github.com> Co-authored-by: hrz <1710360675@qq.com>
50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
from config.logger import setup_logging
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import openai
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from core.providers.llm.base import LLMProviderBase
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TAG = __name__
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logger = setup_logging()
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class LLMProvider(LLMProviderBase):
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def __init__(self, config):
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self.model_name = config.get("model_name")
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self.api_key = config.get("api_key")
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if 'base_url' in config:
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self.base_url = config.get("base_url")
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else:
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self.base_url = config.get("url")
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if "你" in self.api_key:
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logger.bind(tag=TAG).error("你还没配置LLM的密钥，请在配置文件中配置密钥，否则无法正常工作")
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self.client = openai.OpenAI(api_key=self.api_key, base_url=self.base_url)
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def response(self, session_id, dialogue):
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try:
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responses = self.client.chat.completions.create(
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model=self.model_name,
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messages=dialogue,
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stream=True
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)
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is_active = True
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for chunk in responses:
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try:
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# 检查是否存在有效的choice且content不为空
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delta = chunk.choices[0].delta if getattr(chunk, 'choices', None) else None
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content = delta.content if hasattr(delta, 'content') else ''
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except IndexError:
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content = ''
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if content:
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# 处理标签跨多个chunk的情况
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if '<think>' in content:
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is_active = False
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content = content.split('<think>')[0]
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if '</think>' in content:
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is_active = True
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content = content.split('</think>')[-1]
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if is_active:
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yield content
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except Exception as e:
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logger.bind(tag=TAG).error(f"Error in response generation: {e}")
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