501 lines
18 KiB
Python
501 lines
18 KiB
Python
"""
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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 = {
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# 场景1：霸凌/同伴冲突
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"bullying": json.dumps({
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"detected": True,
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"category": "bullying",
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"severity": "medium",
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"summary": "孩子描述被同学欺负、被嘲笑，感到伤心和无助",
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"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"
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}),
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# 场景2：抑郁情绪
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"depression": json.dumps({
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"detected": True,
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"category": "depression",
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"severity": "high",
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"summary": "孩子表达对生活失去兴趣、经常哭泣、觉得自己没有价值",
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"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"
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}),
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# 场景3：焦虑/恐惧
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"anxiety": json.dumps({
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"detected": True,
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"category": "anxiety",
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"severity": "low",
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"summary": "孩子表达对即将到来的考试感到紧张，有些担心",
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"suggestion": "可以通过游戏和放松训练帮助孩子缓解焦虑情绪"
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}),
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# 场景4：正常对话（无问题）
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"normal": json.dumps({
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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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# 场景5：家庭矛盾
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"family_conflict": json.dumps({
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"detected": True,
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"category": "family_conflict",
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"severity": "high",
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"summary": "孩子描述父母经常争吵、提到害怕父母离婚",
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"suggestion": "建议家长注意家庭氛围对孩子的影响，考虑家庭咨询"
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}),
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# 场景6：自卑/自我否定
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"self_esteem": json.dumps({
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"detected": True,
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"category": "self_esteem",
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"severity": "medium",
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"summary": "孩子反复说自己很笨、什么都不如别人、不值得被喜欢",
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"suggestion": "建议多给予孩子正面鼓励和肯定，避免过度批评"
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}),
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# 场景7：社交孤立
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"social_isolation": json.dumps({
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"detected": True,
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"category": "social_isolation",
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"severity": "medium",
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"summary": "孩子表达在学校没有朋友、午餐时间独自一人、感到孤独",
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"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"
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}),
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}
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# ============================================================================
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# 测试用例：虚构儿童对话上下文
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# ============================================================================
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TEST_CASES = [
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# ---- 霸凌/同伴冲突 ----
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{
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"case_id": "bullying_01",
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"scenario": "同伴冲突",
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"context": (
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"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，"
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"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"
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"孩子：每次下课我都躲起来，因为我怕再被他欺负。\n"
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),
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"expected_detected": True,
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"expected_category": "bullying",
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"expected_severity_min": "medium", # minimum: at least medium
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},
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# ---- 抑郁情绪 ----
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{
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"case_id": "depression_01",
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"scenario": "抑郁情绪",
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"context": (
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"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"
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"孩子：我觉得我是一个很糟糕的人，没有人喜欢我。\n"
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"孩子：有时候我想，要是我不在了就好了。\n"
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),
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"expected_detected": True,
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"expected_category": "depression",
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"expected_severity_min": "high",
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},
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# ---- 焦虑/恐惧 ----
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{
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"case_id": "anxiety_01",
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"scenario": "分离焦虑",
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"context": (
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"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"
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"孩子：我担心在幼儿园里会做噩梦，害怕一个人睡觉。\n"
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),
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"expected_detected": True,
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"expected_category": "anxiety",
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"expected_severity_min": "low",
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},
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# ---- 正常对话 ----
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{
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"case_id": "normal_01",
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"scenario": "正常对话",
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"context": (
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"孩子：今天我画了一幅画，是一只大恐龙！\n"
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"孩子：晚上吃的是我最喜欢的红烧肉，好开心呀！\n"
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"孩子：明天我想和好朋友一起去公园玩。\n"
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),
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"expected_detected": False,
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"expected_category": "none",
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"expected_severity_min": "none",
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},
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# ---- 家庭矛盾 ----
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{
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"case_id": "family_conflict_01",
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"scenario": "家庭矛盾",
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"context": (
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"孩子：昨天晚上爸爸妈妈又吵架了，吵得很凶，妈妈哭了。\n"
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"孩子：我很害怕，怕他们会离婚。\n"
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"孩子：我觉得是我的错，是因为我表现不好他们才吵架的。\n"
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),
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"expected_detected": True,
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"expected_category": "family_conflict",
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"expected_severity_min": "high",
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},
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# ---- 自卑/自我否定 ----
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{
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"case_id": "self_esteem_01",
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"scenario": "自卑/自我否定",
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"context": (
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"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"
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"孩子：班上的同学都不喜欢我，没有人想和我坐同桌。\n"
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"孩子：我什么都学不会，我好笨啊。\n"
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),
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"expected_detected": True,
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"expected_category": "self_esteem",
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"expected_severity_min": "medium",
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},
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# ---- 社交孤立 ----
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{
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"case_id": "social_isolation_01",
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"scenario": "社交孤立",
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"context": (
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"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"
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"孩子：同学们都有自己的朋友，只有我是一个人。\n"
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"孩子：我不想去学校了，那里好孤单。\n"
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),
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"expected_detected": True,
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"expected_category": "social_isolation",
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"expected_severity_min": "medium",
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},
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]
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# ============================================================================
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# Fixtures
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# ============================================================================
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@pytest.fixture
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def api_key():
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"""测试用 API key（不会被真实调用）"""
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return "test-minimax-api-key-12345"
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@pytest.fixture
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def screener(api_key):
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"""创建筛查器实例"""
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return PsychoScreener(api_key=api_key)
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# ============================================================================
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# 测试：真实调用 MiniMax API（需要有效的 API key）
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# ============================================================================
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@pytest.mark.integration
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class TestPsychoScreenerIntegration:
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"""集成测试：真实调用 MiniMax API（需设置 MINIMAX_API_KEY）"""
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@pytest.fixture(autouse=True)
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def check_api_key(self):
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api_key = os.environ.get("MINIMAX_API_KEY", "")
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if not api_key:
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pytest.skip("MINIMAX_API_KEY not set, skipping integration test")
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def test_screen_bullying(self):
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api_key = os.environ.get("MINIMAX_API_KEY")
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screener = PsychoScreener(api_key=api_key)
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context = TEST_CASES[0]["context"]
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result = screener.screen(context)
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print(f"\n[integration] bullying result: {result.model_dump_json(indent=2)}")
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assert result.detected is True
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assert result.category == "bullying"
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def test_screen_normal(self):
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api_key = os.environ.get("MINIMAX_API_KEY")
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screener = PsychoScreener(api_key=api_key)
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context = TEST_CASES[3]["context"]
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result = screener.screen(context)
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print(f"\n[integration] normal result: {result.model_dump_json(indent=2)}")
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assert result.detected is False
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# ============================================================================
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# 测试：Mock 测试（不真实调用 API）
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# ============================================================================
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@pytest.mark.unit
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class TestPsychoScreenerUnit:
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"""单元测试：使用 Mock API 响应"""
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def _mock_api_call(self, case_id: str) -> MagicMock:
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"""根据 case_id 返回对应的 mock 响应"""
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# 从 case_id 提取场景 key
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scenario_map = {
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"bullying": "bullying",
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"depression": "depression",
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"anxiety": "anxiety",
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"normal": "normal",
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"family_conflict": "family_conflict",
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"self_esteem": "self_esteem",
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"social_isolation": "social_isolation",
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}
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for key, scenario in scenario_map.items():
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if key in case_id:
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mock_resp = MagicMock()
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mock_resp.raise_for_status = MagicMock()
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mock_resp.json.return_value = {
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"choices": [{"message": {"content": MOCK_RESPONSES[scenario]}}]
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}
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return mock_resp
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# 默认返回 normal
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mock_resp = MagicMock()
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mock_resp.raise_for_status = MagicMock()
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mock_resp.json.return_value = {
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"choices": [{"message": {"content": MOCK_RESPONSES["normal"]}}]
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}
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return mock_resp
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@pytest.mark.parametrize("test_case", TEST_CASES, ids=lambda tc: tc["case_id"])
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def test_screen_cases(self, api_key, test_case, requests_mock):
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"""参数化测试所有场景"""
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case_id = test_case["case_id"]
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# Mock HTTP POST
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requests_mock.post(
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"https://api.minimaxi.com/v1/text/chatcompletion_v2",
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json=self._mock_api_call(case_id).json(),
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)
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screener = PsychoScreener(api_key=api_key)
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result = screener.screen(test_case["context"])
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# 打印测试结果（方便调试）
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print(f"\n[test] {case_id} ({test_case['scenario']})")
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print(f" detected={result.detected}, category={result.category}, severity={result.severity}")
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print(f" summary={result.summary}")
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# 验证检测结果
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assert result.detected == test_case["expected_detected"], \
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f"[{case_id}] 检测结果不符：expected {test_case['expected_detected']}, got {result.detected}"
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if test_case["expected_detected"]:
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assert result.category == test_case["expected_category"], \
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f"[{case_id}] 类别不符：expected {test_case['expected_category']}, got {result.category}"
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# 验证严重程度（使用顺序比较）
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severity_order = ["none", "low", "medium", "high"]
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min_idx = severity_order.index(test_case["expected_severity_min"])
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result_idx = severity_order.index(result.severity)
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assert result_idx >= min_idx, \
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f"[{case_id}] 严重程度不足：expected >= {test_case['expected_severity_min']}, got {result.severity}"
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def test_build_response_prefix_detected(self, api_key):
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"""测试：检测到问题时生成前缀"""
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screener = PsychoScreener(api_key=api_key)
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result = ScreeningResult(
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detected=True,
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category="bullying",
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severity="medium",
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summary="孩子描述被同学欺负",
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suggestion="建议与家长沟通",
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raw_response="",
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)
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prefix = screener.build_response_prefix(result)
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print(f"\nprefix: {prefix}")
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assert "已发现特定心理问题" in prefix
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assert "bullying" in prefix
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assert "medium" in prefix
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def test_build_response_prefix_not_detected(self, api_key):
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"""测试：未检测到问题时返回空前缀"""
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screener = PsychoScreener(api_key=api_key)
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result = ScreeningResult(
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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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raw_response="",
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)
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prefix = screener.build_response_prefix(result)
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assert prefix == ""
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def test_json_parse_error_handling(self, api_key, requests_mock):
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"""测试：模型返回非 JSON 时优雅处理"""
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requests_mock.post(
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"https://api.minimaxi.com/v1/text/chatcompletion_v2",
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text="This is not JSON response",
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)
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screener = PsychoScreener(api_key=api_key)
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result = screener.screen("some context")
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# 应该优雅降级，不抛出异常
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assert result.detected is False
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assert "API调用失败" in result.summary
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# ============================================================================
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# 测试：数据结构验证
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# ============================================================================
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@pytest.mark.unit
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class TestScreeningResultModel:
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"""测试 ScreeningResult 数据模型"""
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def test_screening_result_valid(self):
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"""测试有效数据"""
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result = ScreeningResult(
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detected=True,
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category="bullying",
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severity="high",
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summary="test",
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suggestion="test",
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raw_response="test",
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)
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assert result.detected is True
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assert result.category == "bullying"
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def test_screening_result_defaults(self):
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"""测试默认值"""
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result = ScreeningResult(detected=False)
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assert result.detected is False
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assert result.category == "none"
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assert result.severity == "none"
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assert result.summary == ""
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# ============================================================================
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# 测试：集成小智AI流程
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# ============================================================================
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@pytest.mark.integration
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class TestXiaozhiIntegration:
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"""
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测试：与小智AI的集成流程
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假设 xiaozhi-esp32-server 返回的对话上下文经过本筛查器，
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验证端到端的处理流程
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"""
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def test_full_flow_with_bullying(self):
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"""
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模拟完整流程：
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1. 孩子说了一段可能被霸凌的话
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2. 筛查器识别出问题
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3. 原有回复被加上前缀
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"""
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# 模拟 xiaozhi 返回的原始回复
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original_response = "不要难过的小朋友，每个人都值得被友好对待哦。"
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# 这里需要真实 API key
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api_key = os.environ.get("MINIMAX_API_KEY", "")
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if not api_key:
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pytest.skip("MINIMAX_API_KEY not set")
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screener = PsychoScreener(api_key=api_key)
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context = (
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"孩子：今天小朋友又欺负我了，把我推倒在地上，还骂我。\n"
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"孩子：我觉得好委屈，为什么他们要这样对我？"
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)
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# 步骤1：筛查
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screening_result = screener.screen(context)
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print(f"\n[flow] screening result: {screening_result.model_dump_json(indent=2)}")
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# 步骤2：构建前缀
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prefix = screener.build_response_prefix(screening_result)
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# 步骤3：覆盖原有回复
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if prefix:
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final_response = f"{prefix}\n\n{original_response}"
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else:
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final_response = original_response
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print(f"\n[flow] final response:\n{final_response}")
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# 验证前缀存在
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if screening_result.detected:
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assert "已发现特定心理问题" in final_response
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else:
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assert "已发现特定心理问题" not in final_response
|
||
|
||
|
||
import os # for integration tests
|
||
|
||
|
||
def test_screen_from_messages_empty():
|
||
from psycho_screener.screener import screen_from_messages
|
||
result = screen_from_messages([])
|
||
assert result["has_concern"] is False
|
||
assert result["severity"] == "none"
|
||
|
||
|
||
def test_screen_from_messages_bullying():
|
||
from psycho_screener.screener import screen_from_messages
|
||
messages = [
|
||
{"role": "user", "content": "今天小朋友欺负我了"},
|
||
{"role": "assistant", "content": "发生了什么？"},
|
||
{"role": "user", "content": "他们打我，我好害怕"},
|
||
]
|
||
result = screen_from_messages(messages)
|
||
assert result["has_concern"] is True
|
||
assert "bully" in result["concern_types"]
|
||
|
||
|
||
def test_screen_from_messages_meta_filter():
|
||
from psycho_screener.screener import screen_from_messages
|
||
messages = [
|
||
{"role": "user", "content": "今天被打了"},
|
||
{"role": "assistant", "content": "嗯嗯"},
|
||
{"role": "user", "content": "[满意]"},
|
||
]
|
||
result = screen_from_messages(messages)
|
||
# [满意] 应被过滤，只剩 "今天被打了"
|
||
assert result["has_concern"] is True
|
||
|
||
|
||
def test_screen_from_messages_mixed_roles():
|
||
from psycho_screener.screener import screen_from_messages
|
||
messages = [
|
||
{"role": "system", "content": "你是小智"},
|
||
{"role": "assistant", "content": "好的主人"},
|
||
{"role": "user", "content": "我不想上学了"},
|
||
{"role": "assistant", "content": "为什么呢？"},
|
||
{"role": "user", "content": "同学都笑我"},
|
||
]
|
||
result = screen_from_messages(messages)
|
||
assert result["has_concern"] is True
|