487 lines
18 KiB
Python
487 lines
18 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Configuration Models
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配置数据模型 - 定义所有算法组件的配置结构
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"""
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from typing import Dict, List, Any, Optional, Union
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from pydantic import BaseModel, Field, validator
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from pathlib import Path
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import os
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class BaseConfig(BaseModel):
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"""基础配置类"""
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class Config:
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extra = "allow" # 允许额外字段
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validate_assignment = True
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class TaskModelConfig(BaseModel):
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"""任务级别的模型配置"""
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temperature: Optional[float] = Field(None, ge=0.0, le=2.0)
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top_p: Optional[float] = Field(None, ge=0.0, le=1.0)
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presence_penalty: Optional[float] = Field(None, ge=-2.0, le=2.0)
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frequency_penalty: Optional[float] = Field(None, ge=-2.0, le=2.0)
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max_tokens: Optional[int] = Field(None, gt=0)
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enable_stream: Optional[bool] = None
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def merge_with_default(self, default_config: "AIModelConfig") -> Dict[str, Any]:
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"""与默认配置合并，任务配置优先"""
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result = {
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"temperature": self.temperature if self.temperature is not None else default_config.temperature,
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"top_p": self.top_p if self.top_p is not None else default_config.top_p,
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"presence_penalty": self.presence_penalty if self.presence_penalty is not None else default_config.presence_penalty,
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"frequency_penalty": self.frequency_penalty if self.frequency_penalty is not None else default_config.frequency_penalty,
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"max_tokens": self.max_tokens if self.max_tokens is not None else default_config.max_tokens,
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"enable_stream": self.enable_stream if self.enable_stream is not None else default_config.enable_stream,
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}
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return {k: v for k, v in result.items() if v is not None}
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class AIModelConfig(BaseConfig):
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"""AI模型配置 - 改进版，支持任务级别参数"""
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# 基础配置
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model: str = "qwq-plus"
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api_url: str = ""
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api_key: str = ""
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timeout: int = Field(60, gt=0)
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max_retries: int = Field(3, ge=0)
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# 默认模型参数
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temperature: float = Field(0.7, ge=0.0, le=2.0)
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top_p: float = Field(0.5, ge=0.0, le=1.0)
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presence_penalty: float = Field(1.2, ge=-2.0, le=2.0)
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frequency_penalty: float = Field(0.0, ge=-2.0, le=2.0)
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max_tokens: Optional[int] = Field(None, gt=0)
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# 流式输出配置
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enable_stream: bool = True
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stream_chunk_size: int = 1024
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# 任务级别的模型参数配置
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task_configs: Dict[str, TaskModelConfig] = Field(default_factory=dict)
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def get_task_config(self, task_name: str) -> Dict[str, Any]:
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"""
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获取特定任务的模型配置
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Args:
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task_name: 任务名称 (topic_generation, content_generation, content_judging, poster_generation)
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Returns:
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该任务的模型参数字典
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"""
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if task_name in self.task_configs:
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return self.task_configs[task_name].merge_with_default(self)
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else:
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# 返回默认配置
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return {
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"temperature": self.temperature,
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"top_p": self.top_p,
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"presence_penalty": self.presence_penalty,
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"frequency_penalty": self.frequency_penalty,
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"max_tokens": self.max_tokens,
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"enable_stream": self.enable_stream,
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}
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def set_task_config(self, task_name: str, **params) -> None:
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"""
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设置特定任务的模型参数
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Args:
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task_name: 任务名称
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**params: 模型参数
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"""
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self.task_configs[task_name] = TaskModelConfig(**params)
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class PromptConfig(BaseConfig):
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"""提示词配置 - 解决硬编码的提示词路径问题"""
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# 内容生成提示词
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topic_generation: Dict[str, str] = Field(default_factory=dict)
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content_generation: Dict[str, str] = Field(default_factory=dict)
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content_judging: Dict[str, str] = Field(default_factory=dict)
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poster_generation: Dict[str, str] = Field(default_factory=dict)
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# 提示词模板路径 (支持自定义)
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template_directory: Optional[str] = None
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@validator("*", pre=True)
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def validate_prompts(cls, v):
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"""验证提示词配置"""
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if isinstance(v, dict):
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# 确保包含system和user两个键
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if "system" not in v or "user" not in v:
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return {
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"system": v.get("system", ""),
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"user": v.get("user", "")
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}
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return v
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class ContentGenerationConfig(BaseConfig):
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"""内容生成配置"""
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# 主题生成配置
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topic_count: int = Field(5, ge=1, le=20)
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topic_date_range: Optional[str] = None
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topic_style: str = "default"
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# 内容生成配置
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content_length: str = Field("medium", regex="^(short|medium|long)$")
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content_style: str = "default"
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enable_auto_judge: bool = True
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# 审核配置
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judge_enabled: bool = True
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judge_threshold: float = Field(0.7, ge=0.0, le=1.0)
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# 参考资料配置
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refer_sampling_rate: float = Field(0.5, ge=0.0, le=1.0)
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enable_refer_content: bool = True
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class PosterGenerationConfig(BaseConfig):
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"""海报生成配置 - 解决硬编码的模板和资源问题"""
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# 尺寸配置
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default_size: List[int] = Field(default_factory=lambda: [900, 1200])
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supported_sizes: List[List[int]] = Field(
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default_factory=lambda: [[900, 1200], [1080, 1080], [750, 1334]]
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)
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# 模板配置
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default_template: str = "vibrant"
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available_templates: List[str] = Field(
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default_factory=lambda: ["vibrant", "business", "collage"]
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)
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template_selection_mode: str = Field("manual", regex="^(manual|random|auto)$")
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# 字体配置 - 解决硬编码字体路径
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font_configs: Dict[str, Dict[str, Any]] = Field(default_factory=dict)
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default_font_family: str = "default"
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# 颜色主题配置 - 从硬编码中提取
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color_themes: Dict[str, Dict[str, List[List[int]]]] = Field(default_factory=dict)
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default_color_theme: str = "ocean_deep"
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# 效果配置
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glass_effect: Dict[str, Any] = Field(default_factory=dict)
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text_effects: Dict[str, Any] = Field(default_factory=dict)
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# 输出配置
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output_format: str = Field("PNG", regex="^(PNG|JPEG|WEBP)$")
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output_quality: int = Field(95, ge=1, le=100)
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generate_thumbnail: bool = True
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thumbnail_size: List[int] = Field(default_factory=lambda: [300, 400])
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class DocumentProcessingConfig(BaseConfig):
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"""文档处理配置"""
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# 支持的文件类型
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supported_extensions: List[str] = Field(
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default_factory=lambda: [".txt", ".md", ".pdf", ".docx", ".doc", ".xlsx", ".xls"]
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)
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# 提取配置
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max_file_size: int = Field(50 * 1024 * 1024) # 50MB
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encoding: str = "utf-8"
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extract_images: bool = True
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extract_tables: bool = True
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# 处理配置
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enable_content_cleaning: bool = True
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remove_extra_whitespace: bool = True
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normalize_text: bool = True
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# 爬虫相关配置
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enable_web_scraping: bool = True
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scraping_config: Dict[str, Any] = Field(default_factory=dict)
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class OutputConfig(BaseConfig):
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"""输出配置 - 解决硬编码的文件名和路径问题"""
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# 基础路径配置
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base_output_directory: str = "result"
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enable_timestamped_folders: bool = True
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folder_name_pattern: str = "run_{timestamp}"
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# 文件命名配置
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file_naming: Dict[str, str] = Field(default_factory=lambda: {
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"topics": "topics.json",
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"content": "article.json",
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"poster": "poster.png",
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"raw_response": "{stage}_raw_response.txt",
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"system_prompt": "{stage}_system_prompt.txt",
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"user_prompt": "{stage}_user_prompt.txt"
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})
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# 保存格式配置
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save_raw_responses: bool = True
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save_prompts: bool = True
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save_metadata: bool = True
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# 压缩和备份
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enable_compression: bool = False
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backup_count: int = 5
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class ResourceConfig(BaseConfig):
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"""资源配置 - 管理外部资源路径，包括static文件"""
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# 资源基础路径
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resource_base_directory: Optional[str] = None
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# 字体资源
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font_directory: Optional[str] = None
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font_files: Dict[str, str] = Field(default_factory=dict)
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# 提示词模板目录
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prompt_template_directory: Optional[str] = None
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# 图片资源
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image_assets_directory: Optional[str] = None
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default_background_images: List[str] = Field(default_factory=list)
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# 静态文件配置 - 解决爬虫模块依赖
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static_files_directory: Optional[str] = None
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required_js_files: Dict[str, str] = Field(default_factory=lambda: {
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"xhs_xs_xsc_56": "xhs_xs_xsc_56.js",
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"xhs_xray": "xhs_xray.js",
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"xhs_creator_xs": "xhs_creator_xs.js",
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"xhs_xray_pack1": "xhs_xray_pack1.js",
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"xhs_xray_pack2": "xhs_xray_pack2.js"
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})
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def get_js_file_path(self, js_name: str) -> Optional[str]:
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"""
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解析JavaScript文件路径
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Args:
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js_name: JS文件标识符
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Returns:
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完整的文件路径，如果找不到返回None
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"""
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if js_name not in self.required_js_files:
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return None
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filename = self.required_js_files[js_name]
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if self.static_files_directory:
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js_path = Path(self.resolve_path(self.static_files_directory)) / filename
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if js_path.exists():
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return str(js_path)
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# 搜索可能的路径
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search_paths = [
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Path("static") / filename,
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Path("../static") / filename,
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Path("../../static") / filename,
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Path(f"../{self.static_files_directory or 'static'}") / filename if self.static_files_directory else None
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]
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for path in search_paths:
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if path and path.exists():
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return str(path.resolve())
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return None
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def resolve_path(self, relative_path: str) -> str:
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"""
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解析相对路径为绝对路径
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Args:
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relative_path: 相对路径
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Returns:
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解析后的路径
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"""
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if not relative_path:
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return ""
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path = Path(relative_path)
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# 如果已经是绝对路径，直接返回
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if path.is_absolute():
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return str(path)
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# 如果有resource_base_directory，基于它解析
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if self.resource_base_directory:
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base_path = Path(self.resource_base_directory)
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resolved = base_path / path
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return str(resolved)
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# 否则基于当前目录解析
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return str(path.resolve())
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def find_resource_directory(self, resource_type: str) -> Optional[Path]:
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"""
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查找资源目录
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Args:
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resource_type: 资源类型 (fonts, prompts, images, static)
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Returns:
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找到的目录路径，如果找不到返回None
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"""
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# 根据资源类型确定目录名
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dir_mapping = {
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"fonts": self.font_directory,
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"prompts": self.prompt_template_directory,
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"images": self.image_assets_directory,
|
|||
|
|
"static": self.static_files_directory
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
relative_dir = dir_mapping.get(resource_type)
|
|||
|
|
if not relative_dir:
|
|||
|
|
return None
|
|||
|
|
|
|||
|
|
# 构建搜索路径列表
|
|||
|
|
search_paths = []
|
|||
|
|
|
|||
|
|
# 如果有基础目录，优先搜索
|
|||
|
|
if self.resource_base_directory:
|
|||
|
|
base_path = Path(self.resource_base_directory)
|
|||
|
|
search_paths.append(base_path / relative_dir)
|
|||
|
|
|
|||
|
|
# 添加相对路径搜索
|
|||
|
|
search_paths.extend([
|
|||
|
|
Path(relative_dir),
|
|||
|
|
Path("..") / relative_dir,
|
|||
|
|
Path("../..") / relative_dir,
|
|||
|
|
Path("../../..") / relative_dir
|
|||
|
|
])
|
|||
|
|
|
|||
|
|
# 特殊搜索：针对外部项目的resource目录
|
|||
|
|
if resource_type == "prompts":
|
|||
|
|
search_paths.extend([
|
|||
|
|
Path("resource/prompt"),
|
|||
|
|
Path("../resource/prompt"),
|
|||
|
|
Path("../../resource/prompt"),
|
|||
|
|
Path("../../../resource/prompt")
|
|||
|
|
])
|
|||
|
|
elif resource_type == "static":
|
|||
|
|
search_paths.extend([
|
|||
|
|
Path("static"),
|
|||
|
|
Path("../static"),
|
|||
|
|
Path("../../static"),
|
|||
|
|
Path("../../../static")
|
|||
|
|
])
|
|||
|
|
|
|||
|
|
# 搜索存在的目录
|
|||
|
|
for path in search_paths:
|
|||
|
|
if path.exists() and path.is_dir():
|
|||
|
|
return path.resolve()
|
|||
|
|
|
|||
|
|
return None
|
|||
|
|
|
|||
|
|
def validate_js_files(self) -> Dict[str, bool]:
|
|||
|
|
"""
|
|||
|
|
验证所有必需的JS文件是否存在
|
|||
|
|
|
|||
|
|
Returns:
|
|||
|
|
文件名->是否存在的字典
|
|||
|
|
"""
|
|||
|
|
result = {}
|
|||
|
|
for js_name in self.required_js_files:
|
|||
|
|
result[js_name] = self.get_js_file_path(js_name) is not None
|
|||
|
|
return result
|
|||
|
|
|
|||
|
|
|
|||
|
|
class WebCrawlingConfig(BaseModel):
|
|||
|
|
"""网页爬虫配置"""
|
|||
|
|
|
|||
|
|
# 请求配置
|
|||
|
|
request_interval: float = Field(default=1.0, ge=0.1, description="请求间隔（秒）")
|
|||
|
|
max_requests: int = Field(default=100, ge=0, description="最大请求数，0表示无限制")
|
|||
|
|
request_timeout: float = Field(default=30.0, ge=1.0, description="请求超时时间")
|
|||
|
|
|
|||
|
|
# 浏览器配置
|
|||
|
|
user_agent: str = Field(
|
|||
|
|
default="Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
|
|||
|
|
description="用户代理字符串"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# 代理配置
|
|||
|
|
enable_proxy: bool = Field(default=False, description="是否启用代理")
|
|||
|
|
proxy_config: Optional[Dict[str, str]] = Field(default=None, description="代理配置")
|
|||
|
|
|
|||
|
|
# 错误处理
|
|||
|
|
max_retries: int = Field(default=3, ge=0, description="最大重试次数")
|
|||
|
|
retry_delay: float = Field(default=2.0, ge=0.1, description="重试延迟")
|
|||
|
|
|
|||
|
|
# 内容过滤
|
|||
|
|
min_content_length: int = Field(default=50, ge=0, description="最小内容长度")
|
|||
|
|
max_content_length: int = Field(default=10000, ge=100, description="最大内容长度")
|
|||
|
|
|
|||
|
|
# 小红书特定配置
|
|||
|
|
xhs_search_config: Dict[str, Any] = Field(
|
|||
|
|
default_factory=lambda: {
|
|||
|
|
"default_sort_type": 0, # 默认排序类型
|
|||
|
|
"default_note_type": 0, # 默认笔记类型
|
|||
|
|
"enable_image_download": True,
|
|||
|
|
"enable_video_download": False,
|
|||
|
|
"search_result_limit": 50
|
|||
|
|
},
|
|||
|
|
description="小红书搜索配置"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
|
|||
|
|
class KeywordAnalysisConfig(BaseModel):
|
|||
|
|
"""关键词分析配置"""
|
|||
|
|
|
|||
|
|
# 基础配置
|
|||
|
|
max_keywords: int = Field(default=20, ge=1, le=100, description="最大关键词数量")
|
|||
|
|
min_keyword_length: int = Field(default=2, ge=1, description="最小关键词长度")
|
|||
|
|
max_keyword_length: int = Field(default=10, ge=2, description="最大关键词长度")
|
|||
|
|
|
|||
|
|
# AI分析配置
|
|||
|
|
enable_ai_analysis: bool = Field(default=True, description="是否启用AI分析")
|
|||
|
|
ai_analysis_threshold: int = Field(default=100, ge=0, description="启用AI分析的最小内容长度")
|
|||
|
|
|
|||
|
|
# 评分配置
|
|||
|
|
frequency_weight: float = Field(default=0.4, ge=0.0, le=1.0, description="频率权重")
|
|||
|
|
position_weight: float = Field(default=0.3, ge=0.0, le=1.0, description="位置权重")
|
|||
|
|
type_weight: float = Field(default=0.3, ge=0.0, le=1.0, description="类型权重")
|
|||
|
|
|
|||
|
|
# 分类配置
|
|||
|
|
enable_categorization: bool = Field(default=True, description="是否启用关键词分类")
|
|||
|
|
category_threshold: int = Field(default=2, ge=1, description="分类阈值")
|
|||
|
|
|
|||
|
|
# 搜索建议配置
|
|||
|
|
max_suggestions: int = Field(default=20, ge=1, description="最大搜索建议数量")
|
|||
|
|
enable_combination_suggestions: bool = Field(default=True, description="是否启用组合建议")
|
|||
|
|
|
|||
|
|
|
|||
|
|
class ContentAnalysisConfig(BaseModel):
|
|||
|
|
"""内容分析配置"""
|
|||
|
|
|
|||
|
|
# 质量评分配置
|
|||
|
|
content_length_weight: float = Field(default=0.25, ge=0.0, le=1.0, description="内容长度权重")
|
|||
|
|
title_quality_weight: float = Field(default=0.20, ge=0.0, le=1.0, description="标题质量权重")
|
|||
|
|
media_richness_weight: float = Field(default=0.20, ge=0.0, le=1.0, description="媒体丰富度权重")
|
|||
|
|
structure_weight: float = Field(default=0.20, ge=0.0, le=1.0, description="结构权重")
|
|||
|
|
tag_completeness_weight: float = Field(default=0.15, ge=0.0, le=1.0, description="标签完整性权重")
|
|||
|
|
|
|||
|
|
# 互动评分配置
|
|||
|
|
likes_weight: float = Field(default=0.40, ge=0.0, le=1.0, description="点赞权重")
|
|||
|
|
comments_weight: float = Field(default=0.35, ge=0.0, le=1.0, description="评论权重")
|
|||
|
|
shares_weight: float = Field(default=0.25, ge=0.0, le=1.0, description="分享权重")
|
|||
|
|
|
|||
|
|
# 分析配置
|
|||
|
|
enable_sentiment_analysis: bool = Field(default=True, description="是否启用情感分析")
|
|||
|
|
enable_theme_extraction: bool = Field(default=True, description="是否启用主题提取")
|
|||
|
|
enable_readability_analysis: bool = Field(default=True, description="是否启用可读性分析")
|
|||
|
|
|
|||
|
|
# 主题提取配置
|
|||
|
|
max_themes: int = Field(default=10, ge=1, description="最大主题数量")
|
|||
|
|
theme_frequency_threshold: int = Field(default=2, ge=1, description="主题频率阈值")
|