# tests/unit/test_safety_checks_provider.py
"""Tests unitaires SafetyChecksProvider (QW4)."""
import json
import pytest
from unittest.mock import patch, MagicMock

from agent_v0.server_v1.safety_checks_provider import build_pause_payload, PausePayload


def _action(safety_level=None, declarative_checks=None, message="Validation"):
    params = {"message": message}
    if safety_level:
        params["safety_level"] = safety_level
    if declarative_checks is not None:
        params["safety_checks"] = declarative_checks
    return {"type": "pause_for_human", "parameters": params}


def test_only_declarative_when_no_safety_level():
    """Pas de safety_level → uniquement les checks déclaratifs, pas d'appel LLM."""
    decl = [{"id": "c1", "label": "Vérifier IPP", "required": True}]
    with patch("agent_v0.server_v1.safety_checks_provider._call_llm_for_contextual_checks") as mock_llm:
        payload = build_pause_payload(_action(declarative_checks=decl), {}, last_screenshot=None)
    mock_llm.assert_not_called()
    assert len(payload.checks) == 1
    assert payload.checks[0]["source"] == "declarative"


def test_default_pause_message_is_structured_not_validation_required():
    """Fallback humain: jamais 'Validation requise' seul."""
    payload = build_pause_payload({"type": "pause_for_human", "parameters": {}}, {}, last_screenshot=None)
    lines = payload.message.splitlines()
    assert len(lines) == 4
    assert lines[0].startswith("J'essaie de :")
    assert "Validation requise" not in payload.message


def test_hybrid_appends_llm_checks_on_medical_critical(monkeypatch):
    """safety_level=medical_critical → LLM appelé, checks concaténés."""
    decl = [{"id": "c1", "label": "Vérifier IPP", "required": True}]
    llm_resp = [{"label": "Nom patient suspect à l'écran", "evidence": "vu un nom différent"}]

    with patch("agent_v0.server_v1.safety_checks_provider._call_llm_for_contextual_checks",
               return_value=llm_resp) as mock_llm:
        payload = build_pause_payload(
            _action(safety_level="medical_critical", declarative_checks=decl),
            {}, last_screenshot="/tmp/fake.png",
        )
    mock_llm.assert_called_once()
    assert len(payload.checks) == 2
    assert payload.checks[0]["source"] == "declarative"
    assert payload.checks[1]["source"] == "llm_contextual"
    assert payload.checks[1]["evidence"] == "vu un nom différent"


def test_llm_timeout_falls_back_to_declarative_only():
    """LLM timeout → additional_checks=[], pas de crash, déclaratifs gardés."""
    decl = [{"id": "c1", "label": "Vérifier IPP", "required": True}]
    with patch("agent_v0.server_v1.safety_checks_provider._call_llm_for_contextual_checks",
               return_value=[]) as mock_llm:
        payload = build_pause_payload(
            _action(safety_level="medical_critical", declarative_checks=decl),
            {}, last_screenshot="/tmp/fake.png",
        )
    assert len(payload.checks) == 1
    assert payload.checks[0]["source"] == "declarative"


def test_llm_invalid_response_falls_back():
    """Si _call_llm retourne [] (parse échoué en interne) → fallback safe."""
    with patch("agent_v0.server_v1.safety_checks_provider._call_llm_for_contextual_checks",
               return_value=[]):
        payload = build_pause_payload(
            _action(safety_level="medical_critical", declarative_checks=[]),
            {}, last_screenshot="/tmp/fake.png",
        )
    assert payload.checks == []


def test_kill_switch_disables_llm_call(monkeypatch):
    """RPA_SAFETY_CHECKS_LLM_ENABLED=0 → LLM jamais appelé."""
    monkeypatch.setenv("RPA_SAFETY_CHECKS_LLM_ENABLED", "0")
    decl = [{"id": "c1", "label": "X", "required": True}]
    with patch("agent_v0.server_v1.safety_checks_provider._call_llm_for_contextual_checks") as mock_llm:
        payload = build_pause_payload(
            _action(safety_level="medical_critical", declarative_checks=decl),
            {}, last_screenshot="/tmp/fake.png",
        )
    mock_llm.assert_not_called()
    assert len(payload.checks) == 1


def test_max_checks_respected(monkeypatch):
    """RPA_SAFETY_CHECKS_LLM_MAX_CHECKS=2 → max 2 checks LLM ajoutés."""
    monkeypatch.setenv("RPA_SAFETY_CHECKS_LLM_MAX_CHECKS", "2")
    decl = []
    llm_resp = [
        {"label": f"Check {i}", "evidence": f"e{i}"} for i in range(5)
    ]
    with patch("agent_v0.server_v1.safety_checks_provider._call_llm_for_contextual_checks",
               return_value=llm_resp[:2]):  # provider tronque déjà
        payload = build_pause_payload(
            _action(safety_level="medical_critical", declarative_checks=decl),
            {}, last_screenshot="/tmp/fake.png",
        )
    assert len(payload.checks) == 2


def test_empty_declarative_with_llm_returns_only_llm():
    """Pas de déclaratif + LLM ajoute 2 checks → payload contient les 2."""
    llm_resp = [{"label": "Vérifier date", "evidence": "date 1900 suspecte"},
                {"label": "Vérifier devise", "evidence": "montant en USD au lieu d'EUR"}]
    with patch("agent_v0.server_v1.safety_checks_provider._call_llm_for_contextual_checks",
               return_value=llm_resp):
        payload = build_pause_payload(
            _action(safety_level="medical_critical", declarative_checks=[]),
            {}, last_screenshot="/tmp/fake.png",
        )
    assert len(payload.checks) == 2
    assert all(c["source"] == "llm_contextual" for c in payload.checks)


# ============================================================================
#  Dé-hardcodage VLM (P1.x) : modèle safety-checks résolu via vlm_config
# ============================================================================

def _capture_generate(captured):
    def fake_post(url, json=None, timeout=None):
        captured["url"] = url
        captured["model"] = (json or {}).get("model")
        resp = MagicMock()
        resp.status_code = 200
        resp.json.return_value = {"response": '{"additional_checks": []}'}
        return resp
    return fake_post


def test_safety_checks_model_default_via_vlm_config(monkeypatch):
    """Sans RPA_SAFETY_CHECKS_LLM_MODEL, le modèle vient de vlm_config (pas gemma4 en dur)."""
    monkeypatch.delenv("RPA_SAFETY_CHECKS_LLM_MODEL", raising=False)
    captured = {}

    import requests
    monkeypatch.setattr(requests, "post", _capture_generate(captured))

    from agent_v0.server_v1 import safety_checks_provider as scp
    with patch.object(scp.vlm_config, "get_vlm_model", return_value="modele-resolu:test"):
        scp._call_llm_for_contextual_checks({"parameters": {}}, {}, None, [])

    assert captured["model"] == "modele-resolu:test"
    assert ":11434" in captured["url"]


def test_safety_checks_model_env_override_preserved(monkeypatch):
    """RPA_SAFETY_CHECKS_LLM_MODEL reste prioritaire (override non cassé)."""
    monkeypatch.setenv("RPA_SAFETY_CHECKS_LLM_MODEL", "mon-modele-pin")
    captured = {}

    import requests
    monkeypatch.setattr(requests, "post", _capture_generate(captured))

    from agent_v0.server_v1 import safety_checks_provider as scp
    # get_vlm_model ne doit pas écraser l'override : on le fait lever pour le prouver
    with patch.object(scp.vlm_config, "get_vlm_model", side_effect=AssertionError("ne doit pas être appelé")):
        scp._call_llm_for_contextual_checks({"parameters": {}}, {}, None, [])

    assert captured["model"] == "mon-modele-pin"