154 lines
6.6 KiB
Python
154 lines
6.6 KiB
Python
from datetime import datetime
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from pydantic import BaseModel, ConfigDict, Field
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from pydantic.alias_generators import to_camel
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from typing import Optional, List
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from module_admin.annotation.pydantic_annotation import as_query
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class RagflowListQueryModel(BaseModel):
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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page: int = Field(default=1, description='当前页码')
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page_size: int = Field(default=10, description='每页数量')
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orderby: Optional[str] = Field(default='create_time', description='排序字段')
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desc: Optional[str] = Field(default='true', description='排序方式')
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name: Optional[str] = Field(default=None, description='名称')
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# dataset_id: Optional[str] = Field(default=None, description='数据集ID')
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# chat_id: Optional[str] = Field(default=None, description='聊天ID')
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@as_query
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class ListDocumentsQueryModel(BaseModel):
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"""
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查询文档列表参数模型
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"""
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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page: int = Field(default=1, description='当前页码')
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page_size: int = Field(default=10, description='每页数量')
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orderby: Optional[str] = Field(default='create_time', description='排序字段')
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desc: Optional[str] = Field(default='true', description='排序方式')
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keywords: Optional[str] = Field(default=None, description='关键字')
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document_id: Optional[str] = Field(default=None, description='文档ID')
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document_name: Optional[str] = Field(default=None, description='文档名称')
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class UpdateFileModel(BaseModel):
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"""
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更新文件模型
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"""
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# name 要带文件后缀名
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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name: Optional[str] = Field(default=None, description='文件名称')
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meta_fields: Optional[dict] = Field(default=None, description='文件元数据')
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# naive, manual qa table paper book laws presentation picture one email
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chunk_method: Optional[str] = Field(default=None, description='分块方法')
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# 不同的分块方法有不同的参数.
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parser_config: Optional[dict] = Field(default=None, description='解析器配置')
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# status: Optional[str] = Field(default=None, description='状态')
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class DocumentIdsModel(BaseModel):
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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documnet_ids: list[str] = Field(default=None, description='文件ID列表')
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class DeleteFileModel(BaseModel):
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ids: List[str] = Field(description='文档ID列表')
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class CreateDatasetModel(BaseModel):
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"""
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创建数据集参数模型
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"""
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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name:str = Field(description='数据集名称')
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avatar: Optional[str] = Field(default=None, description='数据集头像, base64编码')
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description: Optional[str] = Field(default=None, description='数据集描述')
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embedding_model: Optional[str] = Field(default=None, description='数据集的embedding模型')
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permission: Optional[str] = Field(default = "me", description='数据集权限')
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chunk_method: Optional[str] = Field(default = "naive", description='数据集分块方法')
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parser_config: Optional[dict] = Field(default = None, description='数据集解析配置')
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class LLM(BaseModel):
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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model_name: Optional[str] = Field(default=None, description='模型名称')
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temperature: Optional[float] = Field(default=0.1, description='模型温度')
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top_p: Optional[float] = Field(default=0.3, description='模型top_p')
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presence_penalty: Optional[float] = Field(default=0.2, description='模型presence_penalty')
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frequency_penalty: Optional[float] = Field(default=0.7, description='模型frequency_penalty')
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class Prompt(BaseModel):
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"""
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聊天助手提示词参数
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"""
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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similarity_threshold: Optional[float] = Field(default=0.2, description='相似度阈值')
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keywords_similarity_weight: Optional[float] = Field(default=0.7, description='关键词相似度权重')
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top_n: Optional[int] = Field(default=8, description='返回结果数量')
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variables: Optional[List[dict]] = Field(default=[{"key": "knowledge", "optional": "true"}], description='变量列表')
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# 默认余弦相似度
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rerank_model: Optional[str] = Field(default=None, description='rerank模型')
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empty_response: Optional[str] = Field(default=None, description='空结果回复')
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opener: Optional[str] = Field(default=None, description='开启者')
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show_quote: Optional[bool] = Field(default=True, description='是否显示引用')
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prompt: Optional[str] = Field(default=None, description='提示语')
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class UpdateChatAssistantModel(BaseModel):
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""" 修改聊天助手参数
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"""
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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chat_id: str = Field(default = None, description='聊天助手ID')
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name: Optional[str] = Field(default = None, description='聊天助手名称')
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# base64编码的图像
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avatar: Optional[str] = Field(default = None, description='聊天助手头像')
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# 启用了哪些数据集?
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dataset_ids: Optional[List[str]] = Field(default = None, description='数据集ID列表')
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# 模型配置参数
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llm: Optional[LLM] = Field(default = None, description='LLM模型')
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prompt: Optional[Prompt] = Field(default = None, description='LLM模型')
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class CreateSessionWithChatModel(BaseModel):
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"""
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创建会话及会话内容模型
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"""
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model_config = ConfigDict(alias_generator=to_camel, from_attributes=True)
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chat_id: str = Field(default = None, description='会话ID')
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name: str = Field(default = None, description='会话名称')
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user_id: Optional[str] = Field(default = None, description='用户ID')
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class ConverseWithChatAssistantModel(BaseModel):
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"""
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会话聊天模型
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"""
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# 移除alias_generator，使用原始的snake_case参数名
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model_config = ConfigDict(from_attributes=True)
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chat_id: str = Field(default = None, description='会话ID')
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question: str = Field(default = None, description='问题')
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stream: Optional[bool] = Field(default = True, description='是否流式返回')
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session_id: Optional[str] = Field(default = None, description='会话ID')
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user_id: Optional[str] = Field(default = None, description='用户ID')
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