tests/test_core.py - ui - Chaizee/ZenithCode_Incident-LLM-analytics

tests/test_core.py
65 строк2 KB
Chaizee
feat: add llm-analyzer realisation
08 июн 2026, 18:44
08 июн 2026, 18:440796e1d
import pandas as pd

from config import IncidentLLMResponse
from src.analytics import build_analytics
from src.llm import parse_response


def test_pydantic_parse():
    raw = '{"is_problem": true, "severity": 4, "core_issue": "нет воды"}'
    m = parse_response(raw)
    assert m.is_problem is True
    assert m.severity == 4


def test_pydantic_clamp():
    m = IncidentLLMResponse.model_validate({"is_problem": True, "severity": 99, "core_issue": "x"})
    assert m.severity == 5


def test_coalesce_text():
    from src.data import _coalesce_incident_text

    df = pd.DataFrame(
        {
            "text_ak": ["", "x"],
            "text_ai": ["реальная жалоба на дорогу", ""],
            "text_aj": ["", ""],
            "text_g": ["", ""],
        }
    )
    out = _coalesce_incident_text(df)
    assert out["incident_text"].iloc[0] == "реальная жалоба на дорогу"


def test_analytics_empty_problems():
    df = pd.DataFrame(
        {
            "municipality": ["А"],
            "settlement": ["с1"],
            "incident_text": ["t1"],
            "is_problem": [False],
            "severity": [1],
            "core_issue": ["—"],
        }
    )
    r = build_analytics(df)
    assert r["problems_count"] == 0
    assert list(r["chart"].columns) == ["municipality", "problem_count", "mean_severity"]
    assert r["chart"].empty


def test_analytics_top():
    df = pd.DataFrame(
        {
            "municipality": ["А", "А", "Б"],
            "settlement": ["с1", "с1", "с2"],
            "incident_text": ["t1", "t2", "t3"],
            "is_problem": [True, True, False],
            "severity": [3, 5, 1],
            "core_issue": ["дороги", "дороги", "спасибо"],
        }
    )
    r = build_analytics(df)
    assert r["problems_count"] == 2
    assert r["top10"]["municipality"].iloc[0] == "А"