analyze_response.py•6.26 kB
"""
市场分析接口的响应模型定义
"""
from typing import Optional, Dict, Any
from pydantic import BaseModel, Field
class MarketOpportunityScore(BaseModel):
"""市场机会评分"""
overall_score: float = Field(
...,
ge=0,
le=100,
description="综合评分 (0-100分)。"
"整合所有外部市场指标计算得出，分数越高表示市场机会越好"
)
market_size_score: float = Field(..., ge=0, le=100, description="市场规模得分")
growth_potential_score: float = Field(..., ge=0, le=100, description="增长潜力得分")
competition_intensity_score: float = Field(..., ge=0, le=100, description="竞争强度得分 (分数越高表示竞争越小)")
market_sentiment_score: float = Field(..., ge=0, le=100, description="市场情绪得分")
level: str = Field(
...,
description="机会等级: 'excellent' (优秀, 80+), 'good' (良好, 60-80), "
"'medium' (中等, 40-60), 'poor' (较差, <40)"
)
summary: str = Field(..., description="评分总结说明")
class OperationalCapabilityScore(BaseModel):
"""运营能力评分"""
overall_score: float = Field(
...,
ge=0,
le=100,
description="综合评分 (0-100分)。"
"整合所有内部运营指标计算得出，分数越高表示运营能力越强"
)
growth_momentum_score: float = Field(..., ge=0, le=100, description="增长势能得分")
user_quality_score: float = Field(..., ge=0, le=100, description="用户质量得分")
cost_efficiency_score: float = Field(..., ge=0, le=100, description="成本效率得分")
product_quality_score: float = Field(..., ge=0, le=100, description="产品质量得分")
infrastructure_score: float = Field(..., ge=0, le=100, description="基础设施得分")
level: str = Field(
...,
description="能力等级: 'strong' (强, 80+), 'good' (良好, 60-80), "
"'medium' (中等, 40-60), 'weak' (弱, <40)"
)
summary: str = Field(..., description="评分总结说明")
class RecommendationItem(BaseModel):
"""单条建议"""
priority: str = Field(..., description="优先级: 'high', 'medium', 'low'")
category: str = Field(..., description="建议类别: '市场策略', '运营优化', '产品改进' 等")
title: str = Field(..., description="建议标题")
description: str = Field(..., description="详细说明")
expected_impact: str = Field(..., description="预期影响")
class AnalyzeResponse(BaseModel):
"""
市场分析响应模型
返回详细的市场机会评估、运营能力评估和战略建议
"""
# 基本信息
product_name: Optional[str] = Field(None, description="产品名称")
analysis_timestamp: str = Field(..., description="分析时间戳 (ISO 8601格式)")
# 核心评分
market_opportunity: MarketOpportunityScore = Field(..., description="市场机会评分")
operational_capability: OperationalCapabilityScore = Field(..., description="运营能力评分")
# 综合评估
comprehensive_score: float = Field(
...,
ge=0,
le=100,
description="综合评分 (0-100分)。"
"市场机会和运营能力的加权平均，反映整体可行性"
)
feasibility_level: str = Field(
...,
description="可行性等级: 'highly_recommended' (强烈推荐), 'recommended' (推荐), "
"'conditional' (有条件可行), 'not_recommended' (不推荐)"
)
# 战略建议
recommendations: list[RecommendationItem] = Field(
...,
description="战略建议列表，按优先级排序"
)
# 风险提示
risk_warnings: list[str] = Field(
default_factory=list,
description="主要风险警示"
)
# 关键指标洞察
key_insights: Dict[str, Any] = Field(
default_factory=dict,
description="关键指标的深度洞察，包括异常值、趋势分析等"
)
class Config:
json_schema_extra = {
"example": {
"product_name": "便携式充电桩",
"analysis_timestamp": "2025-11-09T10:30:00Z",
"market_opportunity": {
"overall_score": 78.5,
"market_size_score": 85,
"growth_potential_score": 82,
"competition_intensity_score": 65,
"market_sentiment_score": 82,
"level": "good",
"summary": "市场规模充足，增长潜力大，但竞争较为激烈"
},
"operational_capability": {
"overall_score": 68.2,
"growth_momentum_score": 75,
"user_quality_score": 60,
"cost_efficiency_score": 55,
"product_quality_score": 73,
"infrastructure_score": 78,
"level": "good",
"summary": "运营基础较好，但在用户留存和成本控制方面有提升空间"
},
"comprehensive_score": 73.4,
"feasibility_level": "recommended",
"recommendations": [
{
"priority": "high",
"category": "运营优化",
"title": "提升用户留存率",
"description": "当前7日留存率35%低于行业平均水平，建议优化用户体验和增值服务",
"expected_impact": "预计可提升留存率至45%+，带来GMV增长15%"
}
],
"risk_warnings": [
"市场竞争激烈，需要明确差异化定位",
"获客成本较高，需要优化营销ROI"
],
"key_insights": {
"market_trend": "行业处于快速增长期，90天趋势呈上升态势",
"competitive_landscape": "中等集中度市场，仍有机会突围"
}
}
}