116 lines
3.4 KiB
Python
116 lines
3.4 KiB
Python
# -*- coding: utf-8 -*-
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"""
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数据模型
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"""
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from datetime import datetime
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from enum import StrEnum
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from typing import Dict, List, Optional
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from pydantic import BaseModel, Field
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from pydantic_ai._uuid import uuid7
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from pydantic_ai.messages import ModelMessage, ModelMessagesTypeAdapter
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from sqlmodel import Field as SqlField, SQLModel
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# 消息历史数据表模型
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# 重新初始化：先手动删除 alembic 相关配置和文件夹，再使用 reflex db init 初始化数据库表
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class MessageHistory(SQLModel, table=True):
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id: str = SqlField(
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default_factory=lambda: str(uuid7()),
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primary_key=True,
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description="消息唯一标识",
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)
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conversation_id: str = SqlField(index=True, description="对话唯一标识")
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run_id: str = SqlField(index=True, description="运行唯一标识")
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new_message: str = SqlField(description="新增消息")
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@staticmethod
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def adapt(
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conversation_id: str, run_id: str, new_message: List[ModelMessage]
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) -> "MessageHistory":
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"""
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适配新增消息为消息历史记录
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:param conversation_id: 对话唯一标识
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:param run_id: 运行唯一标识
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:param new_message: 新增消息
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:return: 消息历史记录
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"""
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return MessageHistory(
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conversation_id=conversation_id,
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run_id=run_id,
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new_message=ModelMessagesTypeAdapter.dump_json(new_message).decode(
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"utf-8"
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), # 序列化为 JSON 字符串
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)
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class EventKind(StrEnum):
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"""事件类型"""
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PART_START = "part_start"
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PART_DELTA = "part_delta"
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PART_END = "part_end"
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FUNCTION_TOOL_CALL = "function_tool_call"
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FUNCTION_TOOL_RESULT = "function_tool_result"
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RUN_START = "run_start"
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RUN_END = "run_end"
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class PartKind(StrEnum):
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"""分片类型"""
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THINKING = "thinking"
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TOOL_SEARCH = "tool-search"
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CAPABILITY_LOAD = "capability-load"
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TOOL_CALL = "tool-call"
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TEXT = "text"
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TOOL_RETURN = "tool-return"
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RETRY_PROMPT = "retry-prompt"
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RUN_RETURN = "run-return"
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class Kind(StrEnum):
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"""分段种类"""
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THINKING = "thinking"
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TOOL_SEARCH = "tool-search"
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CAPABILITY_LOAD = "capability-load"
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TOOL_CALL = "tool-call"
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TEXT = "text"
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TOOL_RETURN = "tool-return"
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RETRY_PROMPT = "retry-prompt"
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RUN_RETURN = "run-return"
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class Reasoning(BaseModel):
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"""推理类"""
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kind: Kind = Field(..., description="推理类型")
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content: str = Field(default="", description="推理内容")
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class Run(BaseModel):
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"""运行类"""
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user_prompt: str = Field(..., description="用户提示词")
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reasonings: Dict[int, Reasoning] = Field(
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default_factory=dict, description="推理字典"
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)
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is_reasoning: bool = Field(
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default=False,
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description="正在推理状态，True 表示正在推理，False 表示非正在推理",
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)
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assistant_content: str = Field(default="", description="回复正文")
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is_streaming: bool = Field(
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default=False,
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description="流式输出状态，True 表示正在流式输出，False 表示非正在流式输出",
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)
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class Conversation(BaseModel):
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"""对话类"""
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description: str = Field(default="新对话", description="描述")
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runs: Dict[str, Run] = Field(default_factory=dict, description="运行字典")
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created_at: datetime = Field(default_factory=datetime.now, description="创建时间")
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