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a020ea5c87
* ✨ feat(llm): 实现LLM服务模块，支持多提供商统一接口和高级功能 * 🎨 Ruff * ✨ Config配置类支持BaseModel存储 * 🎨 代码格式化 * 🎨 代码格式化 * 🎨 格式化代码 * ✨ feat(llm): 添加 AI 对话历史管理 * ✨ feat(llmConfig): 引入 LLM 配置模型及管理功能 * 🎨 Ruff --------- Co-authored-by: fccckaug <xxxmio123123@gmail.com> Co-authored-by: HibiKier <45528451+HibiKier@users.noreply.github.com> Co-authored-by: HibiKier <775757368@qq.com> Co-authored-by: fccckaug <xxxmcsmiomio3@gmail.com> Co-authored-by: webjoin111 <455457521@qq.com>
58 lines
1.4 KiB
Python
58 lines
1.4 KiB
Python
"""
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OpenAI API 适配器
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支持 OpenAI、DeepSeek 和其他 OpenAI 兼容的 API 服务。
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"""
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from typing import TYPE_CHECKING
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from .base import OpenAICompatAdapter, RequestData
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if TYPE_CHECKING:
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from ..service import LLMModel
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class OpenAIAdapter(OpenAICompatAdapter):
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"""OpenAI兼容API适配器"""
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@property
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def api_type(self) -> str:
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return "openai"
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@property
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def supported_api_types(self) -> list[str]:
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return ["openai", "deepseek", "general_openai_compat"]
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def get_chat_endpoint(self) -> str:
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"""返回聊天完成端点"""
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return "/v1/chat/completions"
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def get_embedding_endpoint(self) -> str:
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"""返回嵌入端点"""
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return "/v1/embeddings"
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def prepare_simple_request(
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self,
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model: "LLMModel",
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api_key: str,
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prompt: str,
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history: list[dict[str, str]] | None = None,
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) -> RequestData:
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"""准备简单文本生成请求 - OpenAI优化实现"""
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url = self.get_api_url(model, self.get_chat_endpoint())
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headers = self.get_base_headers(api_key)
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messages = []
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if history:
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messages.extend(history)
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messages.append({"role": "user", "content": prompt})
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body = {
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"model": model.model_name,
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"messages": messages,
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}
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body = self.apply_config_override(model, body)
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return RequestData(url=url, headers=headers, body=body)
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