160 lines
6.3 KiB
Python
160 lines
6.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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内容整合API模型
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"""
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from typing import List, Optional, Dict, Any, Union
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from pydantic import BaseModel, Field, validator
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class ContentIntegrationRequest(BaseModel):
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"""内容整合请求模型"""
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document_paths: Optional[List[str]] = Field(default=None, description="文档文件路径列表（可选，纯搜索模式时可为空）")
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keywords: List[str] = Field(..., description="搜索关键词列表", min_length=1)
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cookies: str = Field(..., description="小红书Cookie字符串")
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# 小红书搜索配置
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sort_type: int = Field(default=2, ge=0, le=4, description="排序方式: 0综合排序, 1最新, 2最多点赞, 3最多评论, 4最多收藏")
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note_type: int = Field(default=2, ge=0, le=2, description="笔记类型: 0不限, 1视频笔记, 2普通笔记")
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note_time: int = Field(default=0, ge=0, le=3, description="笔记时间: 0不限, 1一天内, 2一周内, 3半年内")
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note_range: int = Field(default=0, ge=0, le=3, description="笔记范围: 0不限, 1已看过, 2未看过, 3已关注")
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pos_distance: int = Field(default=0, ge=0, le=2, description="位置距离: 0不限, 1同城, 2附近")
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query_num: int = Field(default=10, ge=1, le=50, description="每个关键词搜索的笔记数量")
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# 输出配置
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output_path: str = Field(default="data/output", description="输出目录路径")
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@validator('document_paths')
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def validate_document_paths(cls, v):
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if v is not None and not v:
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raise ValueError("如果提供文档路径，列表不能为空")
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return v
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@validator('keywords')
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def validate_keywords(cls, v):
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if not v:
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raise ValueError("关键词列表不能为空")
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# 去除空字符串和重复关键词
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cleaned = list(set(k.strip() for k in v if k.strip()))
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if not cleaned:
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raise ValueError("关键词列表不能全为空")
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return cleaned
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@validator('cookies')
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def validate_cookies(cls, v):
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if not v or not v.strip():
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raise ValueError("Cookie不能为空")
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return v.strip()
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class Config:
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schema_extra = {
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"example": {
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"document_paths": [
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"uploads/travel_guide.pdf",
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"uploads/attraction_info.docx"
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],
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"keywords": ["北京旅游", "故宫攻略", "长城一日游"],
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"cookies": "a1=your_cookie_value; web_session=your_session_value",
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"sort_type": 2,
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"note_type": 2,
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"note_time": 0,
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"note_range": 0,
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"pos_distance": 0,
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"query_num": 10,
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"output_path": "data/output"
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}
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}
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class DocumentInfo(BaseModel):
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"""文档信息模型"""
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file_path: str = Field(..., description="文件路径")
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file_type: str = Field(..., description="文件类型")
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content_length: int = Field(..., description="内容长度")
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class XHSInfo(BaseModel):
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"""小红书信息模型"""
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total_notes: int = Field(..., description="笔记总数")
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authors: List[str] = Field(..., description="作者列表")
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total_interactions: int = Field(..., description="总互动数")
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class SearchConfig(BaseModel):
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"""搜索配置模型"""
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sort_type: int = Field(..., description="排序方式")
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note_type: int = Field(..., description="笔记类型")
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note_time: int = Field(..., description="笔记时间")
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note_range: int = Field(..., description="笔记范围")
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pos_distance: int = Field(..., description="位置距离")
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query_num: int = Field(..., description="每个关键词搜索的笔记数量")
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class InputSummary(BaseModel):
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"""输入摘要模型"""
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document_count: int = Field(..., description="文档数量")
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xhs_notes_count: int = Field(..., description="小红书笔记数量")
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keywords: List[str] = Field(..., description="关键词列表")
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class DocumentInfoDetail(BaseModel):
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"""详细文档信息模型"""
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documents: List[DocumentInfo] = Field(..., description="文档列表")
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integrated_text_length: int = Field(..., description="整合文本长度")
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class ContentIntegrationResponse(BaseModel):
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"""内容整合响应模型"""
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success: bool = Field(..., description="是否成功")
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timestamp: str = Field(..., description="时间戳")
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processing_time: str = Field(..., description="处理时间")
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# 成功时的字段
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input_summary: Optional[InputSummary] = Field(None, description="输入摘要")
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document_info: Optional[DocumentInfoDetail] = Field(None, description="文档信息")
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xhs_info: Optional[XHSInfo] = Field(None, description="小红书信息")
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integrated_content: Optional[str] = Field(None, description="整合后的内容")
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search_config: Optional[SearchConfig] = Field(None, description="搜索配置")
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# 失败时的字段
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error_message: Optional[str] = Field(None, description="错误信息")
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class Config:
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schema_extra = {
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"example": {
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"success": True,
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"timestamp": "20250715_143022",
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"processing_time": "45.32秒",
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"input_summary": {
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"document_count": 2,
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"xhs_notes_count": 25,
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"keywords": ["北京旅游", "故宫攻略"]
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},
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"document_info": {
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"documents": [
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{
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"file_path": "uploads/travel_guide.pdf",
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"file_type": "pdf",
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"content_length": 5420
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}
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],
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"integrated_text_length": 8650
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},
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"xhs_info": {
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"total_notes": 25,
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"authors": ["旅游达人小王", "北京导游张三"],
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"total_interactions": 15420
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},
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"integrated_content": "# 北京旅游全攻略...",
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"search_config": {
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"sort_type": 2,
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"note_type": 2,
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"note_time": 0,
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"note_range": 0,
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"pos_distance": 0,
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"query_num": 10
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}
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}
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} |