Soulter
68 lines
2.0 KiB
Python
68 lines
2.0 KiB
Python
import enum
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from dataclasses import dataclass, field
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from typing import List, Dict, Type
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from .func_tool_manager import FuncCall
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from openai.types.chat.chat_completion import ChatCompletion
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from astrbot.core.db.po import Conversation
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class ProviderType(enum.Enum):
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CHAT_COMPLETION = "chat_completion"
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SPEECH_TO_TEXT = "speech_to_text"
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TEXT_TO_SPEECH = "text_to_speech"
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@dataclass
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class ProviderMetaData:
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type: str
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"""提供商适配器名称，如 openai, ollama"""
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desc: str = ""
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"""提供商适配器描述."""
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provider_type: ProviderType = ProviderType.CHAT_COMPLETION
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cls_type: Type = None
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default_config_tmpl: dict = None
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"""平台的默认配置模板"""
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provider_display_name: str = None
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"""显示在 WebUI 配置页中的提供商名称，如空则是 type"""
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@dataclass
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class ProviderRequest:
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prompt: str
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"""提示词"""
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session_id: str = ""
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"""会话 ID"""
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image_urls: List[str] = None
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"""图片 URL 列表"""
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func_tool: FuncCall = None
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"""工具"""
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contexts: List = None
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"""上下文。格式与 openai 的上下文格式一致：
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参考 https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages
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"""
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system_prompt: str = ""
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"""系统提示词"""
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conversation: Conversation = None
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def __repr__(self):
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return f"ProviderRequest(prompt={self.prompt}, session_id={self.session_id}, image_urls={self.image_urls}, func_tool={self.func_tool}, contexts={self.contexts}, system_prompt={self.system_prompt})"
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def __str__(self):
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return self.__repr__()
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@dataclass
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class LLMResponse:
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role: str
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"""角色, assistant, tool, err"""
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completion_text: str = ""
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"""LLM 返回的文本"""
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tools_call_args: List[Dict[str, any]] = field(default_factory=list)
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"""工具调用参数"""
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tools_call_name: List[str] = field(default_factory=list)
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"""工具调用名称"""
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raw_completion: ChatCompletion = None
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_new_record: Dict[str, any] = None
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