187 lines
6.4 KiB
Python
187 lines
6.4 KiB
Python
"""
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LLM 模型管理服务
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提供获取不同 LLM 提供商可用模型列表的功能
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"""
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from typing import List, Dict, Any, Optional
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import requests
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class LLMModelService:
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"""LLM 模型管理服务"""
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@staticmethod
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def get_openai_models(api_key: str, base_url: Optional[str] = None) -> List[str]:
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"""
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获取 OpenAI 兼容 API 的模型列表
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Args:
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api_key: API Key
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base_url: API 基础 URL，默认为 OpenAI 官方 API
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Returns:
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模型名称列表
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"""
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try:
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# 默认使用 OpenAI 官方 API
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if not base_url:
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base_url = "https://api.openai.com/v1"
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# 规范化 base_url：确保有协议前缀
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base_url = base_url.strip()
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if not base_url.startswith(('http://', 'https://')):
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base_url = 'https://' + base_url
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# 移除末尾的斜杠和常见 endpoint 路径
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base_url = base_url.rstrip('/')
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# 移除可能已经存在的 endpoint 路径
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for endpoint in ['/chat/completions', '/completions', '/embeddings', '/models']:
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if base_url.endswith(endpoint):
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base_url = base_url[:-len(endpoint)]
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break
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# 调用 models API
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try:
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response = requests.get(
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f"{base_url}/models",
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headers={
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json"
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},
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timeout=10
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)
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except requests.exceptions.InvalidSchema as e:
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raise Exception(f"URL 格式错误: {base_url}/models - 请确保 URL 以 http:// 或 https:// 开头")
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except requests.exceptions.ConnectionError as e:
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raise Exception(f"无法连接到 API: {base_url}/models - 请检查网络连接和 API 地址")
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except requests.exceptions.Timeout as e:
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raise Exception(f"请求超时: {base_url}/models - 请检查网络连接")
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if response.status_code != 200:
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raise Exception(f"HTTP {response.status_code}: {response.text}")
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data = response.json()
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models = [model['id'] for model in data.get('data', [])]
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# 返回所有模型，不做过滤
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return models
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except Exception as e:
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raise Exception(f"获取 OpenAI 模型列表失败: {str(e)}")
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@staticmethod
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def get_anthropic_models(api_key: str) -> List[str]:
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"""
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获取 Anthropic Claude 模型列表
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Args:
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api_key: API Key
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Returns:
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模型名称列表
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"""
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try:
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# Anthropic 没有公开的模型列表 API，返回已知模型
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return [
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"claude-3-5-sonnet-20241022",
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"claude-3-5-haiku-20241022",
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"claude-3-opus-20240229",
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"claude-3-sonnet-20240229",
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"claude-3-haiku-20240307",
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"claude-2.1",
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"claude-2.0",
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"claude-instant-1.2"
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]
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except Exception as e:
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raise Exception(f"获取 Anthropic 模型列表失败: {str(e)}")
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@staticmethod
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def get_ollama_models(base_url: str = "http://localhost:11434") -> List[str]:
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"""
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获取 Ollama 本地模型列表
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Args:
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base_url: Ollama API 地址
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Returns:
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模型名称列表
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"""
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try:
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response = requests.get(
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f"{base_url}/api/tags",
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timeout=10
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)
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if response.status_code != 200:
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raise Exception(f"HTTP {response.status_code}: {response.text}")
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data = response.json()
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models = [model['name'] for model in data.get('models', [])]
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return models
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except Exception as e:
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raise Exception(f"获取 Ollama 模型列表失败: {str(e)}")
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@staticmethod
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def detect_provider(api_url: str) -> str:
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"""
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根据 API URL 检测提供商类型
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Args:
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api_url: API 地址
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Returns:
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提供商类型: 'openai', 'anthropic', 'ollama', 'unknown'
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"""
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api_url_lower = api_url.lower()
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if 'openai' in api_url_lower or 'api.openai.com' in api_url_lower:
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return 'openai'
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elif 'anthropic' in api_url_lower or 'api.anthropic.com' in api_url_lower:
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return 'anthropic'
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elif 'ollama' in api_url_lower or 'localhost:11434' in api_url_lower or '127.0.0.1:11434' in api_url_lower:
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return 'ollama'
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elif 'bigmodel' in api_url_lower or 'glm' in api_url_lower:
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# 智谱AI GLM - 兼容 OpenAI API
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return 'openai'
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elif 'siliconflow' in api_url_lower or 'silicon.cloud' in api_url_lower:
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# SiliconFlow 等兼容 OpenAI API 的服务
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return 'openai'
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elif 'deepseek' in api_url_lower:
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# DeepSeek 等兼容 OpenAI API 的服务
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return 'openai'
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else:
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# 默认尝试 OpenAI 兼容 API
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return 'openai'
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@staticmethod
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def get_models_by_provider(
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provider: str,
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api_key: str,
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api_url: Optional[str] = None
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) -> List[str]:
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"""
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根据提供商类型获取模型列表
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Args:
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provider: 提供商类型 ('openai', 'anthropic', 'ollama')
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api_key: API Key
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api_url: API 地址（可选）
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Returns:
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模型名称列表
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"""
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if provider == 'openai':
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return LLMModelService.get_openai_models(api_key, api_url)
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elif provider == 'anthropic':
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return LLMModelService.get_anthropic_models(api_key)
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elif provider == 'ollama':
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base_url = api_url or "http://localhost:11434"
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# 移除 /v1 后缀（如果有）
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base_url = base_url.replace('/v1', '').replace('/v1/', '')
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return LLMModelService.get_ollama_models(base_url)
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else:
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raise Exception(f"不支持的提供商: {provider}")
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