Soulter
118 lines
3.9 KiB
Python
118 lines
3.9 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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from astrbot.core.message.message_event_result import MessageChain
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import astrbot.core.message.components as Comp
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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.strip()})"
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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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result_chain: MessageChain = None
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"""返回的消息链"""
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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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_completion_text: str = ""
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def __init__(
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self,
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role: str,
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completion_text: str = "",
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result_chain: MessageChain = None,
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tools_call_args: List[Dict[str, any]] = None,
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tools_call_name: List[str] = None,
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raw_completion: ChatCompletion = None,
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_new_record: Dict[str, any] = None,
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):
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"""初始化 LLMResponse
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Args:
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role (str): 角色, assistant, tool, err
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completion_text (str, optional): 返回的结果文本，已经过时，推荐使用 result_chain. Defaults to "".
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result_chain (MessageChain, optional): 返回的消息链. Defaults to None.
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tools_call_args (List[Dict[str, any]], optional): 工具调用参数. Defaults to None.
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tools_call_name (List[str], optional): 工具调用名称. Defaults to None.
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raw_completion (ChatCompletion, optional): 原始响应, OpenAI 格式. Defaults to None.
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"""
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self.role = role
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self.completion_text = completion_text
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self.result_chain = result_chain
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self.tools_call_args = tools_call_args
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self.tools_call_name = tools_call_name
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self.raw_completion = raw_completion
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self._new_record = _new_record
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@property
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def completion_text(self):
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if self.result_chain:
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return self.result_chain.get_plain_text()
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return self._completion_text
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@completion_text.setter
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def completion_text(self, value):
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if self.result_chain:
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self.result_chain.chain = [
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comp
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for comp in self.result_chain.chain
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if not isinstance(comp, Comp.Plain)
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] # 清空 Plain 组件
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self.result_chain.chain.insert(0, Comp.Plain(value))
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else:
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self._completion_text = value
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