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