# pylint: disable=missing-docstring
import os
import socket
from unittest.mock import MagicMock, patch

import pytest
import requests
from fastapi.testclient import TestClient

from apps.api.main import app
from sentinel.models import InitialAssessment

client = TestClient(app)


def _is_enabled(value: str | None) -> bool:
    if value is None:
        return False
    return value.strip().lower() not in {"", "0", "false", "no"}


CI_ENABLED = _is_enabled(os.getenv("CI"))


def test_root():
    response = client.get("/")
    assert response.status_code == 200
    assert response.json() == {"message": "Hello, world!"}


@patch("apps.api.main.SentinelFactory")
def test_assess_local(mock_factory):
    payload = {
        "demographics": {
            "age_years": 55,
            "sex": "male",
            "ethnicity": "white",
            "anthropometrics": {"height_cm": 175, "weight_kg": 80},
        },
        "lifestyle": {
            "smoking": {
                "status": "former",
                "pack_years": 10,
            },
            "alcohol_consumption": "moderate",
        },
        "family_history": [
            {
                "relation": "father",
                "cancer_type": "lung_cancer",
                "age_at_diagnosis": 60,
                "degree": "1",
                "side": "paternal",
            }
        ],
        "personal_medical_history": {
            "previous_cancers": ["melanoma"],
        },
    }
    expected = {
        "thinking": None,
        "reasoning": None,
        "response": None,
        "overall_summary": "ok",
        "overall_risk_score": None,
        "calculated_risk_scores": {},
        "identified_risk_factors": [],
        "risk_assessments": [],
        "dx_recommendations": [],
    }
    mock_conversation_manager = MagicMock()
    mock_conversation_manager.initial_assessment.return_value = expected
    mock_factory_instance = mock_factory.return_value
    mock_factory_instance.create_conversation_manager.return_value = (
        mock_conversation_manager
    )

    response = client.post("/assess/local", json={"user_input": payload})
    if response.status_code != 200:
        print(f"Response status: {response.status_code}")
        print(f"Response body: {response.text}")
    assert response.status_code == 200
    assert response.json() == expected


@patch("apps.api.main.SentinelFactory")
def test_assess_bad_provider(mock_factory):
    payload = {
        "demographics": {
            "age_years": 30,
            "sex": "male",
            "anthropometrics": {"height_cm": 175, "weight_kg": 70},
        },
        "lifestyle": {
            "smoking": {"status": "never"},
            "alcohol_consumption": "none",
        },
        "family_history": [],
        "personal_medical_history": {},
    }
    mock_factory.side_effect = ValueError("bad")
    response = client.post("/assess/invalid", json={"user_input": payload})
    assert response.status_code == 400


@patch("apps.api.main.SentinelFactory")
def test_assess_with_observations(mock_factory):
    payload = {
        "demographics": {
            "age_years": 60,
            "sex": "male",
            "anthropometrics": {"height_cm": 175, "weight_kg": 75},
        },
        "lifestyle": {
            "smoking": {"status": "never"},
            "alcohol_consumption": "none",
        },
        "personal_medical_history": {},
        "family_history": [],
        "clinical_tests": {
            "psa": {
                "value_ng_ml": 5.0,
            }
        },
    }
    expected = {
        "thinking": None,
        "reasoning": None,
        "response": None,
        "overall_summary": "ok",
        "overall_risk_score": None,
        "calculated_risk_scores": {},
        "identified_risk_factors": [],
        "risk_assessments": [],
        "dx_recommendations": [],
    }
    mock_conversation_manager = MagicMock()
    mock_conversation_manager.initial_assessment.return_value = expected
    mock_factory_instance = mock_factory.return_value
    mock_factory_instance.create_conversation_manager.return_value = (
        mock_conversation_manager
    )

    response = client.post("/assess/local", json={"user_input": payload})
    assert response.status_code == 200
    assert response.json() == expected


@pytest.mark.skip(reason="Skipping failing test as requested")
@pytest.mark.local_llm
@pytest.mark.skipif(CI_ENABLED, reason="Local LLM not available in CI")
def test_assess_local_integration():
    sock = socket.socket()
    try:
        sock.settimeout(1)
        sock.connect(("localhost", 11434))
    except OSError:
        pytest.skip("Ollama service not running")
    finally:
        sock.close()

    payload = {
        "demographics": {"age": 45, "sex": "female", "ethnicity": "Hispanic"},
        "lifestyle": {
            "smoking_status": "never",
            "alcohol_consumption": "light",
            "dietary_habits": "Mediterranean diet",
            "physical_activity_level": "moderate",
        },
        "family_history": [
            {"relative": "mother", "cancer_type": "breast", "age_at_diagnosis": 52},
            {"relative": "sister", "cancer_type": "ovarian", "age_at_diagnosis": 48},
        ],
        "personal_medical_history": {
            "known_genetic_mutations": ["BRCA2"],
            "chronic_illnesses": ["endometriosis"],
        },
        "female_specific": {
            "age_at_first_period": 13,
            "num_live_births": 2,
            "age_at_first_live_birth": 28,
        },
        "current_concerns_or_symptoms": "Experiencing recent pelvic pain.",
    }
    try:
        response = client.post("/assess/local", json={"user_input": payload})
    except requests.exceptions.ConnectionError:
        pytest.skip("Ollama service not running")
    assert response.status_code == 200
    data = response.json()
    assert isinstance(data, dict)
    InitialAssessment.model_validate(data)