feat: 儿童心理陪伴筛查插件初始版本
- 核心 PsychoScreener 模块，支持 MiniMax API 调用 - 8 种心理问题类别检测（霸凌、抑郁、焦虑、家庭矛盾等） - ScreeningResult 数据模型，含类别/严重程度/建议 - 单元测试 12 个（含参数化测试，覆盖 7 个虚构场景） - build_response_prefix() 支持检测后注入前缀标记 - pyproject.toml + .gitignore 完整项目脚手架main
Sileya
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# 儿童心理陪伴玩偶 - 环境变量配置
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# 复制此文件为 .env 并填入实际值
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# MiniMax API Key（必填）
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# 获取地址：https://platform.minimaxi.com/
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MINIMAX_API_KEY=your-api-key-here
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# MiniMax 模型（可选，默认 MiniMax-M2.5）
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MINIMAX_MODEL=MiniMax-M2.5
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# MiniMax API 地址（可选，默认使用官方接口）
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MINIMAX_BASE_URL=https://api.minimaxi.com/v1/text/chatcompletion_v2
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# 日志级别
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LOG_LEVEL=INFO
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@ -0,0 +1,25 @@
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# Python
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__pycache__/
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*.py[cod]
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*.so
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.venv/
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venv/
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.env
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# Test
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.pytest_cache/
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.coverage
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htmlcov/
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# IDE
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.idea/
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.vscode/
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*.swp
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# Build
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*.egg-info/
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dist/
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build/
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# OS
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.DS_Store
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# 儿童心理陪伴玩偶
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基于小智AI生态的儿童心理筛查插件，通过分析儿童与玩偶的对话内容，
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识别潜在的心理问题（如霸凌、抑郁情绪、焦虑、家庭矛盾等），
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为家长提供早期预警。
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## 项目结构
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```
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child-psycho-companion/
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├── src/
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│ └── psycho_screener/ # 核心筛查模块
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│ ├── __init__.py
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│ └── screener.py # 筛查器实现
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├── tests/
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│ ├── __init__.py
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│ ├── conftest.py
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│ └── test_screener.py # 单元测试
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├── .env.example # 环境变量模板
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├── pyproject.toml
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└── README.md
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```
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## 快速开始
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### 1. 安装
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```bash
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cd child-psycho-companion
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pip install -e .
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```
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### 2. 配置 API Key
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```bash
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export MINIMAX_API_KEY=your-api-key-here
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```
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### 3. 使用示例
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```python
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from psycho_screener import PsychoScreener
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screener = PsychoScreener(api_key="your-api-key")
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# 对儿童对话进行筛查
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context = """
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孩子：今天在学校，小明又打我了，我好害怕。
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孩子：他说如果我告诉老师就会打我。
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"""
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result = screener.screen(context)
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if result.detected:
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print(f"检测到问题：{result.summary}")
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prefix = screener.build_response_prefix(result)
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print(f"响应前缀：{prefix}")
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```
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### 4. 运行测试
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```bash
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# 安装测试依赖
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pip install -e ".[dev]"
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# 运行单元测试（Mock 模式，不调用真实 API）
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pytest tests/test_screener.py -v -m unit
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# 运行集成测试（需要真实 API key）
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export MINIMAX_API_KEY=your-key
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pytest tests/test_screener.py -v -m integration
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```
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## 核心流程
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```
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儿童语音 → 小智AI (STT) → 对话上下文
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↓
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心理筛查器 (MiniMax API)
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↓
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ScreeningResult {detected, category, severity}
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↓
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┌───────────┴───────────┐
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detected=True detected=False
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↓ ↓
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注入前缀标记 原样返回
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"已发现特定心理问题：..."
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```
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## 检测类别
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| 类别 | 描述 | 严重程度 |
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|------|------|---------|
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| bullying | 霸凌/同伴冲突 | low-high |
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| depression | 抑郁情绪 | medium-high |
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| anxiety | 焦虑/恐惧 | low-medium |
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| family_conflict | 家庭矛盾 | medium-high |
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| self_esteem | 自卑/自我否定 | low-medium |
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| trauma | 创伤事件 | medium-high |
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| social_isolation | 社交孤立 | medium-high |
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| other | 其他心理需求 | - |
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## 下一步
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- [ ] 接入 xinnan-tech/xiaozhi-esp32-server MCP 接入点
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- [ ] 构建案例库系统
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- [ ] 开发咨询师终端
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- [ ] 家长端报告界面
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[project]
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name = "child-psycho-companion"
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version = "0.1.0"
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description = "儿童心理陪伴玩偶 - 对话心理筛查插件"
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requires-python = ">=3.10"
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dependencies = [
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"requests>=2.31.0",
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"pydantic>=2.0",
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]
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[project.optional-dependencies]
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dev = [
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"pytest>=8.0",
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"pytest-asyncio>=0.23",
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"pytest-mock>=3.14",
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"requests-mock>=1.12",
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]
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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markers = [
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"unit: Unit tests with mocked API calls",
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"integration: Integration tests requiring real API calls",
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]
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[build-system]
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requires = ["setuptools>=61.0"]
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build-backend = "setuptools.build_meta"
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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"""
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儿童心理陪伴 - 核心筛查模块
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功能：对儿童对话上下文进行心理问题筛查，检测潜在心理需求或问题
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目标年龄段：3-8岁
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"""
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from .screener import PsychoScreener, ScreeningResult
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__all__ = ["PsychoScreener", "ScreeningResult"]
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"""
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儿童心理陪伴 - 筛查器
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基于 MiniMax API，对儿童对话进行心理问题筛查
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"""
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from __future__ import annotations
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import os
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import json
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import requests
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from typing import Literal
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from pydantic import BaseModel, Field
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# ============================================================================
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# 数据模型
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# ============================================================================
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class ConcernCategory(str):
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"""心理问题类别"""
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NONE = "none"
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BULLYING = "bullying" # 校园霸凌/同伴冲突
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DEPRESSION = "depression" # 抑郁情绪
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ANXIETY = "anxiety" # 焦虑/恐惧
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FAMILY_CONFLICT = "family_conflict" # 家庭矛盾
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SELF_ESTEEM = "self_esteem" # 自卑/自我否定
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TRAUMA = "trauma" # 创伤事件
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SOCIAL_ISOLATION = "social_isolation" # 社交孤立
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OTHER = "other" # 其他
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class ScreeningResult(BaseModel):
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"""筛查结果"""
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detected: bool = Field(description="是否检测到心理问题")
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category: str = Field(default=ConcernCategory.NONE, description="问题类别")
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severity: Literal["none", "low", "medium", "high"] = Field(
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default="none", description="严重程度"
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)
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summary: str = Field(default="", description="简要描述检测到的问题")
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suggestion: str = Field(default="", description="建议行动")
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raw_response: str = Field(default="", description="模型原始响应（调试用）")
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# ============================================================================
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# 筛查系统提示词
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# ============================================================================
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SYSTEM_PROMPT = """你是一个专业的儿童心理咨询师助手，专注于分析3-8岁儿童的对话内容，识别潜在的心理需求或问题。
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## 你的任务
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分析给定的儿童对话上下文，判断是否存在以下心理问题类别：
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1. **bullying** - 霸凌/同伴冲突：孩子表达被欺负、被嘲笑、被孤立、被人威胁等
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2. **depression** - 抑郁情绪：孩子表达悲伤、绝望、无助、对事物失去兴趣、提到"不想活了"等
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3. **anxiety** - 焦虑/恐惧：孩子表达担心、害怕、做噩梦、回避某些情境等
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4. **family_conflict** - 家庭矛盾：孩子表达父母争吵、离婚担心、被忽视、被严厉惩罚等
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5. **self_esteem** - 自卑/自我否定：孩子表达"我不行"、"没人喜欢我"、"我太笨了"等
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6. **trauma** - 创伤事件：孩子描述意外事故、暴力事件、亲人离世等创伤性经历
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7. **social_isolation** - 社交孤立：孩子表达没有朋友、被排斥、孤独感等
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8. **other** - 其他值得关注的心理需求
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## 输出格式
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请严格按以下JSON格式返回（不要添加任何额外内容）：
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{
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"detected": true/false,
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"category": "具体类别",
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"severity": "none/low/medium/high",
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"summary": "一句话描述检测到的问题",
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"suggestion": "建议的应对方式（简短，1-2句话）"
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}
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## 判断标准
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- **low**: 轻微迹象，需要关注但无需立即介入
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- **medium**: 中度迹象，建议与家长沟通
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- **high**: 严重迹象，需要专业干预
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如果对话内容完全正常，没有任何心理问题迹象，返回：
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{
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"detected": false,
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"category": "none",
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"severity": "none",
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"summary": "未检测到心理问题",
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"suggestion": ""
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}
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注意：
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- 只关注确实存在问题的迹象，不要过度解读
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- 儿童的语言表达可能不精确，需要结合上下文判断
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- 正常的情绪表达（偶尔哭、发脾气）不构成问题"""
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# ============================================================================
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# 筛查器
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# ============================================================================
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class PsychoScreener:
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"""
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儿童心理问题筛查器
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使用方法：
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screener = PsychoScreener(api_key="your-api-key")
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result = screener.screen("今天小明打我了，我很伤心")
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if result.detected:
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print(f"检测到问题：{result.summary}")
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"""
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def __init__(
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self,
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api_key: str | None = None,
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model: str = "MiniMax-M2.5",
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base_url: str = "https://api.minimaxi.com/v1/text/chatcompletion_v2",
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):
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self.api_key = api_key or os.environ.get("MINIMAX_API_KEY", "")
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self.model = model
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self.base_url = base_url
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if not self.api_key:
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raise ValueError(
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"MiniMax API key is required. "
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"Set MINIMAX_API_KEY env var or pass api_key parameter."
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)
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def _call_minimax(self, messages: list[dict]) -> str:
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"""调用 MiniMax API"""
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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}
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payload = {
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"model": self.model,
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"messages": messages,
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}
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response = requests.post(
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self.base_url,
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headers=headers,
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json=payload,
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timeout=30,
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)
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response.raise_for_status()
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data = response.json()
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# 兼容不同返回格式
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if "choices" in data:
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return data["choices"][0]["message"]["content"]
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elif "output" in data:
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return data["output"]
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return str(data)
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def screen(self, context: str) -> ScreeningResult:
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"""
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对给定的对话上下文进行心理问题筛查
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Args:
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context: 儿童的对话上下文（可以是多轮对话的汇总文本）
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Returns:
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ScreeningResult: 包含检测结果的数据模型
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"""
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messages = [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": f"请分析以下儿童对话内容：\n\n{context}"},
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]
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try:
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raw_response = self._call_minimax(messages)
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except Exception as e:
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return ScreeningResult(
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detected=False,
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category=ConcernCategory.OTHER,
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severity="none",
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summary=f"API调用失败: {str(e)}",
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suggestion="",
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raw_response=str(e),
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)
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# 尝试解析 JSON
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try:
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# 提取 JSON（可能模型返回带有 markdown 代码块）
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content = raw_response.strip()
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if content.startswith("```"):
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lines = content.split("\n")
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content = "\n".join(lines[1:-1]) # 去掉 ```json 和 ```
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parsed = json.loads(content)
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return ScreeningResult(
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detected=parsed.get("detected", False),
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category=parsed.get("category", ConcernCategory.NONE),
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severity=parsed.get("severity", "none"),
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summary=parsed.get("summary", ""),
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suggestion=parsed.get("suggestion", ""),
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raw_response=raw_response,
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)
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except json.JSONDecodeError:
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# 无法解析 JSON，返回原始内容
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return ScreeningResult(
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detected=False,
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category=ConcernCategory.OTHER,
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severity="none",
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summary="无法解析模型响应",
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suggestion="",
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raw_response=raw_response,
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)
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def build_response_prefix(self, result: ScreeningResult) -> str:
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"""
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根据筛查结果构建响应前缀
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Args:
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result: 筛查结果
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Returns:
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str: 如果检测到问题，返回前缀字符串；否则返回空字符串
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"""
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if not result.detected:
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return ""
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return f"【已发现特定心理问题】类别：{result.category}，严重程度：{result.severity}，描述：{result.summary}"
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# Test configuration for pytest
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@ -0,0 +1,456 @@
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"""
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单元测试 - 儿童心理筛查器
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测试场景：使用虚构的儿童对话上下文，验证筛查函数能否正确识别并标注心理问题
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运行方式：
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pytest tests/test_screener.py -v
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"""
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import pytest
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import json
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from unittest.mock import patch, MagicMock
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from psycho_screener.screener import (
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PsychoScreener,
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ScreeningResult,
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ConcernCategory,
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)
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# ============================================================================
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# Mock API 响应（用于测试）
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# ============================================================================
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MOCK_RESPONSES = {
|
||||
# 场景1：霸凌/同伴冲突
|
||||
"bullying": json.dumps({
|
||||
"detected": True,
|
||||
"category": "bullying",
|
||||
"severity": "medium",
|
||||
"summary": "孩子描述被同学欺负、被嘲笑，感到伤心和无助",
|
||||
"suggestion": "建议家长与孩子耐心沟通，了解具体情况，并与学校老师联系"
|
||||
}),
|
||||
|
||||
# 场景2：抑郁情绪
|
||||
"depression": json.dumps({
|
||||
"detected": True,
|
||||
"category": "depression",
|
||||
"severity": "high",
|
||||
"summary": "孩子表达对生活失去兴趣、经常哭泣、觉得自己没有价值",
|
||||
"suggestion": "高度建议寻求专业儿童心理咨询师帮助，密切关注孩子的安全"
|
||||
}),
|
||||
|
||||
# 场景3：焦虑/恐惧
|
||||
"anxiety": json.dumps({
|
||||
"detected": True,
|
||||
"category": "anxiety",
|
||||
"severity": "low",
|
||||
"summary": "孩子表达对即将到来的考试感到紧张，有些担心",
|
||||
"suggestion": "可以通过游戏和放松训练帮助孩子缓解焦虑情绪"
|
||||
}),
|
||||
|
||||
# 场景4：正常对话（无问题）
|
||||
"normal": json.dumps({
|
||||
"detected": False,
|
||||
"category": "none",
|
||||
"severity": "none",
|
||||
"summary": "未检测到心理问题",
|
||||
"suggestion": ""
|
||||
}),
|
||||
|
||||
# 场景5：家庭矛盾
|
||||
"family_conflict": json.dumps({
|
||||
"detected": True,
|
||||
"category": "family_conflict",
|
||||
"severity": "high",
|
||||
"summary": "孩子描述父母经常争吵、提到害怕父母离婚",
|
||||
"suggestion": "建议家长注意家庭氛围对孩子的影响，考虑家庭咨询"
|
||||
}),
|
||||
|
||||
# 场景6：自卑/自我否定
|
||||
"self_esteem": json.dumps({
|
||||
"detected": True,
|
||||
"category": "self_esteem",
|
||||
"severity": "medium",
|
||||
"summary": "孩子反复说自己很笨、什么都不如别人、不值得被喜欢",
|
||||
"suggestion": "建议多给予孩子正面鼓励和肯定，避免过度批评"
|
||||
}),
|
||||
|
||||
# 场景7：社交孤立
|
||||
"social_isolation": json.dumps({
|
||||
"detected": True,
|
||||
"category": "social_isolation",
|
||||
"severity": "medium",
|
||||
"summary": "孩子表达在学校没有朋友、午餐时间独自一人、感到孤独",
|
||||
"suggestion": "建议帮助孩子学习社交技巧，与学校合作创造更多交友机会"
|
||||
}),
|
||||
}
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# 测试用例：虚构儿童对话上下文
|
||||
# ============================================================================
|
||||
|
||||
TEST_CASES = [
|
||||
# ---- 霸凌/同伴冲突 ----
|
||||
{
|
||||
"case_id": "bullying_01",
|
||||
"scenario": "同伴冲突",
|
||||
"context": (
|
||||
"孩子：今天在学校，小明又打我了，他抢了我的玩具还不让我告诉老师，"
|
||||
"他说如果我告诉老师就会打我。我很害怕，我现在不想去学校了。\n"
|
||||
"孩子：每次下课我都躲起来，因为我怕再被他欺负。\n"
|
||||
),
|
||||
"expected_detected": True,
|
||||
"expected_category": "bullying",
|
||||
"expected_severity_min": "medium", # minimum: at least medium
|
||||
},
|
||||
|
||||
# ---- 抑郁情绪 ----
|
||||
{
|
||||
"case_id": "depression_01",
|
||||
"scenario": "抑郁情绪",
|
||||
"context": (
|
||||
"孩子：最近我总是觉得很累，什么都不想做，连我最喜欢的动画片都不想看了。\n"
|
||||
"孩子：我觉得我是一个很糟糕的人，没有人喜欢我。\n"
|
||||
"孩子：有时候我想，要是我不在了就好了。\n"
|
||||
),
|
||||
"expected_detected": True,
|
||||
"expected_category": "depression",
|
||||
"expected_severity_min": "high",
|
||||
},
|
||||
|
||||
# ---- 焦虑/恐惧 ----
|
||||
{
|
||||
"case_id": "anxiety_01",
|
||||
"scenario": "分离焦虑",
|
||||
"context": (
|
||||
"孩子：明天妈妈要送我上幼儿园，我好害怕，我不想和妈妈分开。\n"
|
||||
"孩子：我担心在幼儿园里会做噩梦，害怕一个人睡觉。\n"
|
||||
),
|
||||
"expected_detected": True,
|
||||
"expected_category": "anxiety",
|
||||
"expected_severity_min": "low",
|
||||
},
|
||||
|
||||
# ---- 正常对话 ----
|
||||
{
|
||||
"case_id": "normal_01",
|
||||
"scenario": "正常对话",
|
||||
"context": (
|
||||
"孩子：今天我画了一幅画，是一只大恐龙！\n"
|
||||
"孩子：晚上吃的是我最喜欢的红烧肉，好开心呀！\n"
|
||||
"孩子：明天我想和好朋友一起去公园玩。\n"
|
||||
),
|
||||
"expected_detected": False,
|
||||
"expected_category": "none",
|
||||
"expected_severity_min": "none",
|
||||
},
|
||||
|
||||
# ---- 家庭矛盾 ----
|
||||
{
|
||||
"case_id": "family_conflict_01",
|
||||
"scenario": "家庭矛盾",
|
||||
"context": (
|
||||
"孩子：昨天晚上爸爸妈妈又吵架了，吵得很凶，妈妈哭了。\n"
|
||||
"孩子：我很害怕，怕他们会离婚。\n"
|
||||
"孩子：我觉得是我的错，是因为我表现不好他们才吵架的。\n"
|
||||
),
|
||||
"expected_detected": True,
|
||||
"expected_category": "family_conflict",
|
||||
"expected_severity_min": "high",
|
||||
},
|
||||
|
||||
# ---- 自卑/自我否定 ----
|
||||
{
|
||||
"case_id": "self_esteem_01",
|
||||
"scenario": "自卑/自我否定",
|
||||
"context": (
|
||||
"孩子：今天老师表扬了小红但是没有表扬我，我就是个笨蛋，什么都做不好。\n"
|
||||
"孩子：班上的同学都不喜欢我，没有人想和我坐同桌。\n"
|
||||
"孩子：我什么都学不会，我好笨啊。\n"
|
||||
),
|
||||
"expected_detected": True,
|
||||
"expected_category": "self_esteem",
|
||||
"expected_severity_min": "medium",
|
||||
},
|
||||
|
||||
# ---- 社交孤立 ----
|
||||
{
|
||||
"case_id": "social_isolation_01",
|
||||
"scenario": "社交孤立",
|
||||
"context": (
|
||||
"孩子：今天课间的时候我一个人蹲在角落，没有人来和我玩。\n"
|
||||
"孩子：同学们都有自己的朋友，只有我是一个人。\n"
|
||||
"孩子：我不想去学校了，那里好孤单。\n"
|
||||
),
|
||||
"expected_detected": True,
|
||||
"expected_category": "social_isolation",
|
||||
"expected_severity_min": "medium",
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Fixtures
|
||||
# ============================================================================
|
||||
|
||||
@pytest.fixture
|
||||
def api_key():
|
||||
"""测试用 API key（不会被真实调用）"""
|
||||
return "test-minimax-api-key-12345"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def screener(api_key):
|
||||
"""创建筛查器实例"""
|
||||
return PsychoScreener(api_key=api_key)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# 测试：真实调用 MiniMax API（需要有效的 API key）
|
||||
# ============================================================================
|
||||
|
||||
@pytest.mark.integration
|
||||
class TestPsychoScreenerIntegration:
|
||||
"""集成测试：真实调用 MiniMax API（需设置 MINIMAX_API_KEY）"""
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def check_api_key(self):
|
||||
api_key = os.environ.get("MINIMAX_API_KEY", "")
|
||||
if not api_key:
|
||||
pytest.skip("MINIMAX_API_KEY not set, skipping integration test")
|
||||
|
||||
def test_screen_bullying(self):
|
||||
api_key = os.environ.get("MINIMAX_API_KEY")
|
||||
screener = PsychoScreener(api_key=api_key)
|
||||
|
||||
context = TEST_CASES[0]["context"]
|
||||
result = screener.screen(context)
|
||||
|
||||
print(f"\n[integration] bullying result: {result.model_dump_json(indent=2)}")
|
||||
assert result.detected is True
|
||||
assert result.category == "bullying"
|
||||
|
||||
def test_screen_normal(self):
|
||||
api_key = os.environ.get("MINIMAX_API_KEY")
|
||||
screener = PsychoScreener(api_key=api_key)
|
||||
|
||||
context = TEST_CASES[3]["context"]
|
||||
result = screener.screen(context)
|
||||
|
||||
print(f"\n[integration] normal result: {result.model_dump_json(indent=2)}")
|
||||
assert result.detected is False
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# 测试：Mock 测试（不真实调用 API）
|
||||
# ============================================================================
|
||||
|
||||
@pytest.mark.unit
|
||||
class TestPsychoScreenerUnit:
|
||||
"""单元测试：使用 Mock API 响应"""
|
||||
|
||||
def _mock_api_call(self, case_id: str) -> MagicMock:
|
||||
"""根据 case_id 返回对应的 mock 响应"""
|
||||
# 从 case_id 提取场景 key
|
||||
scenario_map = {
|
||||
"bullying": "bullying",
|
||||
"depression": "depression",
|
||||
"anxiety": "anxiety",
|
||||
"normal": "normal",
|
||||
"family_conflict": "family_conflict",
|
||||
"self_esteem": "self_esteem",
|
||||
"social_isolation": "social_isolation",
|
||||
}
|
||||
|
||||
for key, scenario in scenario_map.items():
|
||||
if key in case_id:
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.raise_for_status = MagicMock()
|
||||
mock_resp.json.return_value = {
|
||||
"choices": [{"message": {"content": MOCK_RESPONSES[scenario]}}]
|
||||
}
|
||||
return mock_resp
|
||||
|
||||
# 默认返回 normal
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.raise_for_status = MagicMock()
|
||||
mock_resp.json.return_value = {
|
||||
"choices": [{"message": {"content": MOCK_RESPONSES["normal"]}}]
|
||||
}
|
||||
return mock_resp
|
||||
|
||||
@pytest.mark.parametrize("test_case", TEST_CASES, ids=lambda tc: tc["case_id"])
|
||||
def test_screen_cases(self, api_key, test_case, requests_mock):
|
||||
"""参数化测试所有场景"""
|
||||
case_id = test_case["case_id"]
|
||||
|
||||
# Mock HTTP POST
|
||||
requests_mock.post(
|
||||
"https://api.minimaxi.com/v1/text/chatcompletion_v2",
|
||||
json=self._mock_api_call(case_id).json(),
|
||||
)
|
||||
|
||||
screener = PsychoScreener(api_key=api_key)
|
||||
result = screener.screen(test_case["context"])
|
||||
|
||||
# 打印测试结果（方便调试）
|
||||
print(f"\n[test] {case_id} ({test_case['scenario']})")
|
||||
print(f" detected={result.detected}, category={result.category}, severity={result.severity}")
|
||||
print(f" summary={result.summary}")
|
||||
|
||||
# 验证检测结果
|
||||
assert result.detected == test_case["expected_detected"], \
|
||||
f"[{case_id}] 检测结果不符：expected {test_case['expected_detected']}, got {result.detected}"
|
||||
|
||||
if test_case["expected_detected"]:
|
||||
assert result.category == test_case["expected_category"], \
|
||||
f"[{case_id}] 类别不符：expected {test_case['expected_category']}, got {result.category}"
|
||||
|
||||
# 验证严重程度（使用顺序比较）
|
||||
severity_order = ["none", "low", "medium", "high"]
|
||||
min_idx = severity_order.index(test_case["expected_severity_min"])
|
||||
result_idx = severity_order.index(result.severity)
|
||||
assert result_idx >= min_idx, \
|
||||
f"[{case_id}] 严重程度不足：expected >= {test_case['expected_severity_min']}, got {result.severity}"
|
||||
|
||||
def test_build_response_prefix_detected(self, api_key):
|
||||
"""测试：检测到问题时生成前缀"""
|
||||
screener = PsychoScreener(api_key=api_key)
|
||||
|
||||
result = ScreeningResult(
|
||||
detected=True,
|
||||
category="bullying",
|
||||
severity="medium",
|
||||
summary="孩子描述被同学欺负",
|
||||
suggestion="建议与家长沟通",
|
||||
raw_response="",
|
||||
)
|
||||
|
||||
prefix = screener.build_response_prefix(result)
|
||||
print(f"\nprefix: {prefix}")
|
||||
|
||||
assert "已发现特定心理问题" in prefix
|
||||
assert "bullying" in prefix
|
||||
assert "medium" in prefix
|
||||
|
||||
def test_build_response_prefix_not_detected(self, api_key):
|
||||
"""测试：未检测到问题时返回空前缀"""
|
||||
screener = PsychoScreener(api_key=api_key)
|
||||
|
||||
result = ScreeningResult(
|
||||
detected=False,
|
||||
category="none",
|
||||
severity="none",
|
||||
summary="未检测到心理问题",
|
||||
suggestion="",
|
||||
raw_response="",
|
||||
)
|
||||
|
||||
prefix = screener.build_response_prefix(result)
|
||||
assert prefix == ""
|
||||
|
||||
def test_json_parse_error_handling(self, api_key, requests_mock):
|
||||
"""测试：模型返回非 JSON 时优雅处理"""
|
||||
requests_mock.post(
|
||||
"https://api.minimaxi.com/v1/text/chatcompletion_v2",
|
||||
text="This is not JSON response",
|
||||
)
|
||||
|
||||
screener = PsychoScreener(api_key=api_key)
|
||||
result = screener.screen("some context")
|
||||
|
||||
# 应该优雅降级，不抛出异常
|
||||
assert result.detected is False
|
||||
assert "API调用失败" in result.summary
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# 测试：数据结构验证
|
||||
# ============================================================================
|
||||
|
||||
@pytest.mark.unit
|
||||
class TestScreeningResultModel:
|
||||
"""测试 ScreeningResult 数据模型"""
|
||||
|
||||
def test_screening_result_valid(self):
|
||||
"""测试有效数据"""
|
||||
result = ScreeningResult(
|
||||
detected=True,
|
||||
category="bullying",
|
||||
severity="high",
|
||||
summary="test",
|
||||
suggestion="test",
|
||||
raw_response="test",
|
||||
)
|
||||
assert result.detected is True
|
||||
assert result.category == "bullying"
|
||||
|
||||
def test_screening_result_defaults(self):
|
||||
"""测试默认值"""
|
||||
result = ScreeningResult(detected=False)
|
||||
assert result.detected is False
|
||||
assert result.category == "none"
|
||||
assert result.severity == "none"
|
||||
assert result.summary == ""
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# 测试：集成小智AI流程
|
||||
# ============================================================================
|
||||
|
||||
@pytest.mark.integration
|
||||
class TestXiaozhiIntegration:
|
||||
"""
|
||||
测试：与小智AI的集成流程
|
||||
|
||||
假设 xiaozhi-esp32-server 返回的对话上下文经过本筛查器，
|
||||
验证端到端的处理流程
|
||||
"""
|
||||
|
||||
def test_full_flow_with_bullying(self):
|
||||
"""
|
||||
模拟完整流程：
|
||||
1. 孩子说了一段可能被霸凌的话
|
||||
2. 筛查器识别出问题
|
||||
3. 原有回复被加上前缀
|
||||
"""
|
||||
# 模拟 xiaozhi 返回的原始回复
|
||||
original_response = "不要难过的小朋友，每个人都值得被友好对待哦。"
|
||||
|
||||
# 这里需要真实 API key
|
||||
api_key = os.environ.get("MINIMAX_API_KEY", "")
|
||||
if not api_key:
|
||||
pytest.skip("MINIMAX_API_KEY not set")
|
||||
|
||||
screener = PsychoScreener(api_key=api_key)
|
||||
|
||||
context = (
|
||||
"孩子：今天小朋友又欺负我了，把我推倒在地上，还骂我。\n"
|
||||
"孩子：我觉得好委屈，为什么他们要这样对我？"
|
||||
)
|
||||
|
||||
# 步骤1：筛查
|
||||
screening_result = screener.screen(context)
|
||||
print(f"\n[flow] screening result: {screening_result.model_dump_json(indent=2)}")
|
||||
|
||||
# 步骤2：构建前缀
|
||||
prefix = screener.build_response_prefix(screening_result)
|
||||
|
||||
# 步骤3：覆盖原有回复
|
||||
if prefix:
|
||||
final_response = f"{prefix}\n\n{original_response}"
|
||||
else:
|
||||
final_response = original_response
|
||||
|
||||
print(f"\n[flow] final response:\n{final_response}")
|
||||
|
||||
# 验证前缀存在
|
||||
if screening_result.detected:
|
||||
assert "已发现特定心理问题" in final_response
|
||||
else:
|
||||
assert "已发现特定心理问题" not in final_response
|
||||
|
||||
|
||||
import os # for integration tests
|
||||
Loading…
Reference in New Issue