307 lines
12 KiB
Python
307 lines
12 KiB
Python
import requests
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import json
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import time
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import logging
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logger = logging.getLogger(__name__)
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class SiliconFlowClient:
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def __init__(self, api_key="sk-xqbujijjqqmlmlvkhvxeogqjtzslnhdtqxqgiyuhwpoqcjvf", model="Qwen/QwQ-32B"):
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"""
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初始化SiliconFlow客户端
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"""
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self.api_key = api_key
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self.model = model
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self.base_url = "https://api.siliconflow.cn/v1"
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self.messages = []
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self.system_message = None
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logger.info(f"初始化SiliconFlow客户端 - 模型: {model}")
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def set_model(self, model):
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"""设置使用的模型"""
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self.model = model
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logger.info(f"SiliconFlow切换模型: {model}")
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def set_system_message(self, message):
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"""设置系统消息"""
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self.system_message = message
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self.messages = []
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if message:
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self.messages.append({"role": "system", "content": message})
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logger.debug(f"SiliconFlow设置系统消息 - 长度: {len(message) if message else 0}")
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def add_message(self, role, content):
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"""添加消息到对话历史"""
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self.messages.append({"role": role, "content": content})
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def clear_history(self):
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"""清空对话历史"""
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self.messages = []
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if self.system_message:
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self.messages.append({"role": "system", "content": self.system_message})
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logger.debug("SiliconFlow清空对话历史")
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def chat(self, message):
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"""
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非流式对话
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"""
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try:
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# 添加用户消息
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self.add_message("user", message)
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payload = {
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"model": self.model,
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"messages": self.messages,
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"stream": False,
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"max_tokens": 2048,
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"temperature": 0.7,
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"top_p": 0.7,
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}
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json"
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}
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response = requests.post(
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f"{self.base_url}/chat/completions",
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json=payload,
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headers=headers,
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timeout=60
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)
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if response.status_code == 200:
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data = response.json()
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assistant_message = data['choices'][0]['message']['content']
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self.add_message("assistant", assistant_message)
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return assistant_message
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else:
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error_msg = f"SiliconFlow API错误: {response.status_code} - {response.text}"
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logger.error(error_msg)
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return f"API调用失败: {error_msg}"
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except Exception as e:
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error_msg = f"SiliconFlow对话出错: {str(e)}"
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logger.exception("SiliconFlow对话异常")
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return error_msg
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def chat_stream(self, message):
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"""
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流式对话
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"""
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try:
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# 添加用户消息
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self.add_message("user", message)
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payload = {
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"model": self.model,
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"messages": self.messages,
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"stream": True,
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"max_tokens": 2048,
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"temperature": 0.7,
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"top_p": 0.7,
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}
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json"
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}
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response = requests.post(
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f"{self.base_url}/chat/completions",
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json=payload,
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headers=headers,
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stream=True,
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timeout=120
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)
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if response.status_code != 200:
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error_msg = f"SiliconFlow API错误: {response.status_code} - {response.text}"
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logger.error(error_msg)
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yield f"API调用失败: {error_msg}"
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return
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assistant_message = ""
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for line in response.iter_lines():
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if line:
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line = line.decode('utf-8')
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if line.startswith('data: '):
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data_str = line[6:] # 移除 'data: ' 前缀
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if data_str.strip() == '[DONE]':
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break
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try:
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data = json.loads(data_str)
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if 'choices' in data and len(data['choices']) > 0:
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delta = data['choices'][0].get('delta', {})
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content = delta.get('content', '')
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if content:
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assistant_message += content
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yield content
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except json.JSONDecodeError:
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continue
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# 添加完整的助手回复到历史
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if assistant_message:
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self.add_message("assistant", assistant_message)
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except requests.exceptions.Timeout:
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error_msg = "SiliconFlow请求超时"
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logger.error(error_msg)
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yield error_msg
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except Exception as e:
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error_msg = f"SiliconFlow流式对话出错: {str(e)}"
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logger.exception("SiliconFlow流式对话异常")
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yield error_msg
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@classmethod
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def get_available_models(cls, api_key="sk-xqbujijjqqmlmlvkhvxeogqjtzslnhdtqxqgiyuhwpoqcjvf"):
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"""
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获取可用的模型列表
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"""
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import os
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# 尝试多种网络配置
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proxy_configs = [
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# 不使用代理
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{'proxies': None, 'verify': True},
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# 使用系统代理但禁用SSL验证
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{'proxies': None, 'verify': False},
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# 明确禁用代理
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{'proxies': {'http': None, 'https': None}, 'verify': True},
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{'proxies': {'http': None, 'https': None}, 'verify': False},
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]
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for i, config in enumerate(proxy_configs):
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try:
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logger.info(f"尝试网络配置 {i+1}/{len(proxy_configs)}")
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headers = {"Authorization": f"Bearer {api_key}"}
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# 创建会话以便更好地控制连接
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session = requests.Session()
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if config['proxies'] is not None:
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session.proxies.update(config['proxies'])
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response = session.get(
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"https://api.siliconflow.cn/v1/models",
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headers=headers,
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timeout=30,
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verify=config['verify']
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)
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if response.status_code == 200:
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data = response.json()
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all_models = data.get('data', [])
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logger.info(f"SiliconFlow API返回 {len(all_models)} 个模型")
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models = []
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excluded_keywords = ['embedding', 'stable-diffusion', 'bge-', 'rerank', 'whisper']
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for model in all_models:
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model_id = model.get('id', '')
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if not model_id:
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continue
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# 排除明显的非聊天模型
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if any(keyword in model_id.lower() for keyword in excluded_keywords):
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continue
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# 包含常见的聊天模型关键词或者包含chat、instruct等
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chat_keywords = ['chat', 'instruct', 'qwen', 'glm', 'internlm', 'baichuan', 'llama', 'mistral', 'claude', 'gpt', 'yi']
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if any(keyword in model_id.lower() for keyword in chat_keywords):
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models.append({
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'id': model_id,
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'name': model_id,
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'description': model.get('description', ''),
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})
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logger.info(f"获取SiliconFlow模型列表成功 - 总数: {len(all_models)}, 聊天模型: {len(models)}")
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# 如果过滤后的模型太少，返回所有模型（除了明确的排除项）
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if len(models) < 10:
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logger.warning("过滤后的聊天模型数量过少，返回所有非排除模型")
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models = []
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for model in all_models:
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model_id = model.get('id', '')
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if model_id and not any(keyword in model_id.lower() for keyword in excluded_keywords):
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models.append({
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'id': model_id,
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'name': model_id,
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'description': model.get('description', ''),
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})
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return models
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else:
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logger.warning(f"网络配置 {i+1} 失败: {response.status_code} - {response.text}")
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except Exception as e:
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logger.warning(f"网络配置 {i+1} 异常: {str(e)}")
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continue
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# 所有配置都失败了
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logger.error("所有网络配置都失败，无法获取模型列表")
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raise Exception("无法连接到SiliconFlow API服务器")
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@classmethod
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def _get_fallback_models(cls):
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"""
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当API调用失败时，返回预定义的常用模型列表
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"""
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logger.info("使用预定义的模型列表作为备选方案")
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return [
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{
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'id': 'Qwen/Qwen2.5-7B-Instruct',
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'name': 'Qwen2.5-7B-Instruct',
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'description': '通义千问2.5 7B指令模型'
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},
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{
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'id': 'Qwen/Qwen2.5-14B-Instruct',
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'name': 'Qwen2.5-14B-Instruct',
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'description': '通义千问2.5 14B指令模型'
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},
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{
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'id': 'Qwen/Qwen2.5-32B-Instruct',
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'name': 'Qwen2.5-32B-Instruct',
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'description': '通义千问2.5 32B指令模型'
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},
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{
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'id': 'Qwen/Qwen2.5-72B-Instruct',
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'name': 'Qwen2.5-72B-Instruct',
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'description': '通义千问2.5 72B指令模型'
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},
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{
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'id': 'Qwen/QwQ-32B-Preview',
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'name': 'QwQ-32B-Preview',
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'description': '通义千问推理模型预览版'
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},
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{
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'id': 'deepseek-ai/DeepSeek-V2.5',
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'name': 'DeepSeek-V2.5',
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'description': 'DeepSeek V2.5 模型'
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},
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{
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'id': 'meta-llama/Llama-3.1-8B-Instruct',
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'name': 'Llama-3.1-8B-Instruct',
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'description': 'Meta Llama 3.1 8B指令模型'
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},
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{
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'id': 'meta-llama/Llama-3.1-70B-Instruct',
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'name': 'Llama-3.1-70B-Instruct',
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'description': 'Meta Llama 3.1 70B指令模型'
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},
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{
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'id': 'THUDM/glm-4-9b-chat',
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'name': 'GLM-4-9B-Chat',
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'description': '智谱GLM-4 9B对话模型'
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},
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{
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'id': 'internlm/internlm2_5-7b-chat',
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'name': 'InternLM2.5-7B-Chat',
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'description': '书生浦语2.5 7B对话模型'
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}
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] |