"""Tests for the judge-prompt localizer (no RAGAS dependency; uses fake prompts)."""

import json

from pydantic import BaseModel

from rag_eval.metrics import judge_prompts as jp


class _In(BaseModel):
    question: str


class _Out(BaseModel):
    statements: list[str]


class _FakePrompt:
    """Minimal stand-in for a RAGAS BasePrompt with overridable attributes."""

    def __init__(self):
        self.input_model = _In
        self.output_model = _Out
        self.instruction = "English instruction."
        self.examples = [(_In(question="q"), _Out(statements=["s"]))]
        self.language = "english"


class _FakeMetric:
    def __init__(self):
        self.prompt = _FakePrompt()


def _cache_dict(prompt):
    """Build a valid cache dict for the given fake prompt."""
    return {
        "metric": "context_recall",
        "prompt_attr": "prompt",
        "language": "chinese",
        "ragas_version": "0.4.3",
        "source_hash": jp.prompt_source_hash(prompt),
        "instruction": "中文指令。",
        "examples": [{"input": {"question": "问题"}, "output": {"statements": ["陈述"]}}],
    }


def setup_function(_):
    jp.reset_cache()


def test_apply_localized_prompt_overrides_instruction_and_examples():
    """apply_localized_prompt swaps instruction/examples and rebuilds example models."""
    prompt = _FakePrompt()
    jp.apply_localized_prompt(prompt, _cache_dict(prompt))
    assert prompt.instruction == "中文指令。"
    assert prompt.examples[0][0].question == "问题"
    assert prompt.examples[0][1].statements == ["陈述"]
    assert prompt.language == "chinese"


def test_localize_english_is_noop():
    """language='en' leaves the registry untouched."""
    metric = _FakeMetric()
    report = jp.localize_pipeline_prompts({"context_recall": metric}, "en")
    assert report.applied == []
    assert metric.prompt.instruction == "English instruction."


def test_localize_applies_from_cache_file(tmp_path, monkeypatch):
    """localize reads <root>/zh/context_recall__prompt.json and applies it."""
    metric = _FakeMetric()
    root = tmp_path / "configs" / "judge_prompts"
    (root / "zh").mkdir(parents=True)
    (root / "zh" / "context_recall__prompt.json").write_text(
        json.dumps(_cache_dict(metric.prompt), ensure_ascii=False), encoding="utf-8"
    )
    monkeypatch.setattr(jp, "CACHE_ROOT", root)
    report = jp.localize_pipeline_prompts({"context_recall": metric}, "zh")
    assert "context_recall.prompt" in report.applied
    assert metric.prompt.instruction == "中文指令。"


def test_localize_missing_cache_keeps_english(tmp_path, monkeypatch):
    """A missing cache file degrades gracefully to the English prompt with a warning."""
    metric = _FakeMetric()
    monkeypatch.setattr(jp, "CACHE_ROOT", tmp_path / "empty")
    report = jp.localize_pipeline_prompts({"context_recall": metric}, "zh")
    assert metric.prompt.instruction == "English instruction."
    assert "context_recall.prompt" in report.skipped
    assert report.warnings


def test_localize_stale_hash_warns_but_applies(tmp_path, monkeypatch):
    """A source_hash mismatch still applies Chinese but records a stale warning."""
    metric = _FakeMetric()
    data = _cache_dict(metric.prompt)
    data["source_hash"] = "deadbeef"
    root = tmp_path / "configs" / "judge_prompts"
    (root / "zh").mkdir(parents=True)
    (root / "zh" / "context_recall__prompt.json").write_text(
        json.dumps(data, ensure_ascii=False), encoding="utf-8"
    )
    monkeypatch.setattr(jp, "CACHE_ROOT", root)
    report = jp.localize_pipeline_prompts({"context_recall": metric}, "zh")
    assert metric.prompt.instruction == "中文指令。"
    assert any("stale" in w for w in report.warnings)


def test_cache_memoized(tmp_path, monkeypatch):
    """A second localize call does not re-read the file (in-memory memo)."""
    metric = _FakeMetric()
    root = tmp_path / "configs" / "judge_prompts"
    (root / "zh").mkdir(parents=True)
    path = root / "zh" / "context_recall__prompt.json"
    path.write_text(json.dumps(_cache_dict(metric.prompt), ensure_ascii=False), encoding="utf-8")
    monkeypatch.setattr(jp, "CACHE_ROOT", root)
    jp.localize_pipeline_prompts({"context_recall": _FakeMetric()}, "zh")
    path.unlink()  # delete file; memo should still serve the parsed data
    metric2 = _FakeMetric()
    report = jp.localize_pipeline_prompts({"context_recall": metric2}, "zh")
    assert "context_recall.prompt" in report.applied