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#!/usr/bin/env python3
"""Production safety tests for key pipeline utilities."""

from __future__ import annotations

import json
import sys
import tempfile
import unittest
from unittest import mock
from pathlib import Path

try:
    from datasets import Dataset
except ModuleNotFoundError:  # pragma: no cover - optional test dependency in this environment
    Dataset = None

ROOT = Path(__file__).resolve().parents[1]
if str(ROOT) not in sys.path:
    sys.path.insert(0, str(ROOT))

try:
    import app
except Exception:  # pragma: no cover - optional test dependency in this environment
    app = None

try:
    from scripts import eval_sota
except Exception:  # pragma: no cover - optional test dependency in this environment
    eval_sota = None

try:
    from scripts import train_sota
except Exception:  # pragma: no cover - optional test dependency in this environment
    train_sota = None


@unittest.skipUnless(app is not None, "app runtime dependencies are not installed")
class AppUtilityTests(unittest.TestCase):
    def test_validate_repo_id_accepts_valid(self) -> None:
        self.assertEqual(
            app.validate_repo_id("NorthernTribe-Research/math_trainer", "Model repo"),
            "NorthernTribe-Research/math_trainer",
        )

    def test_validate_repo_id_rejects_invalid(self) -> None:
        with self.assertRaises(ValueError):
            app.validate_repo_id("invalid repo id", "Model repo")

    def test_merge_log_chunk_truncates(self) -> None:
        merged = app._merge_log_chunk("a" * 9, "b" * 9, max_chars=10)
        self.assertEqual(len(merged), 10)
        self.assertTrue(merged.endswith("b" * 9))

    def test_build_stage_timeline_returns_list_markup(self) -> None:
        stage_meta = {"start_stage": 1, "stage_count": 2, "completed": 1, "active_stage": 2}
        html = app._build_stage_timeline({}, stage_meta)
        self.assertIn("ops-stage-list", html)
        self.assertIn("ops-stage-item", html)

    def test_validate_stage_window_rejects_overflow(self) -> None:
        with self.assertRaises(ValueError):
            app.validate_stage_window(app.TEMPLATE_STAGE_COUNT, 2)

    def test_build_recent_runs_panel_markup(self) -> None:
        summary = {
            "recent_runs": [
                {
                    "run_label": "run-20260101-000000",
                    "result": "completed",
                    "duration_seconds": 42,
                    "finished_at_utc": "2026-01-01 00:00:42 UTC",
                    "evaluation": {"pass_at_1": 0.11, "pass_at_k": 0.27, "evaluated_rows": 128},
                }
            ]
        }
        html = app._build_recent_runs_panel(summary)
        self.assertIn("ops-run-list", html)
        self.assertIn("run-20260101-000000", html)
        self.assertIn("completed", html)

    def test_run_result_badge_class_handles_preflight_variants(self) -> None:
        self.assertEqual(app._run_result_badge_class("preflight_passed"), "ok")
        self.assertEqual(app._run_result_badge_class("preflight passed"), "ok")

    def test_persist_run_artifacts_updates_history(self) -> None:
        with tempfile.TemporaryDirectory() as tmpdir:
            history_path = Path(tmpdir) / "run_history.json"
            records_dir = Path(tmpdir) / "run_records"
            summary = {
                "run_label": "run-20260102-030405",
                "result": "completed",
                "started_at_utc": "2026-01-02 03:04:05 UTC",
                "finished_at_utc": "2026-01-02 03:04:35 UTC",
                "evaluation": {"pass_at_1": 0.1, "pass_at_k": 0.2, "evaluated_rows": 64},
            }

            with mock.patch.object(app, "RUN_HISTORY_PATH", history_path):
                with mock.patch.object(app, "RUN_RECORDS_DIR", records_dir):
                    warning = app.persist_run_artifacts(summary)

            self.assertIsNone(warning)
            self.assertTrue(history_path.exists())
            payload = json.loads(history_path.read_text(encoding="utf-8"))
            self.assertEqual(payload[0]["run_label"], "run-20260102-030405")
            self.assertEqual(payload[0]["result"], "completed")
            self.assertTrue((records_dir / "run-20260102-030405.json").exists())


@unittest.skipUnless(eval_sota is not None, "eval_sota runtime dependencies are not installed")
class EvalUtilityTests(unittest.TestCase):
    def test_parse_numeric_fraction(self) -> None:
        value = eval_sota.parse_numeric_value("3/4")
        self.assertIsNotNone(value)
        assert value is not None
        self.assertAlmostEqual(value, 0.75, places=8)

    def test_match_candidate_boxed(self) -> None:
        result = eval_sota.match_candidate(r"\boxed{42}", ["42"])
        self.assertTrue(result["match"])
        self.assertTrue(result["boxed"] or result["exact"])

    def test_infer_response_profile_handles_formal_and_non_formal_rows(self) -> None:
        formal_row = {"family": "formal_proof", "difficulty": "formal_proof"}
        simple_row = {"family": "problem_solving", "difficulty": "basic"}

        self.assertEqual(eval_sota.infer_response_profile(formal_row), "lean_formal")
        self.assertEqual(eval_sota.infer_response_profile(simple_row), "simple")


@unittest.skipUnless(train_sota is not None, "train_sota runtime dependencies are not installed")
class TrainUtilityTests(unittest.TestCase):
    def test_as_bool_conversions(self) -> None:
        self.assertTrue(train_sota.as_bool("yes"))
        self.assertFalse(train_sota.as_bool("no"))
        self.assertTrue(train_sota.as_bool(True))
        self.assertFalse(train_sota.as_bool(None, default=False))

    def test_canonical_difficulty_mappings(self) -> None:
        self.assertEqual(train_sota.canonical_difficulty("basic_to_intermediate"), "simple")
        self.assertEqual(train_sota.canonical_difficulty("formal_proof"), "lean_formal")
        self.assertEqual(train_sota.canonical_difficulty("olympiad"), "advanced")

    def test_apply_filters_include_bands_and_require_lean_formal(self) -> None:
        if Dataset is None:
            self.skipTest("datasets is not installed")

        dataset = Dataset.from_dict(
            {
                "family": ["formal_proof", "problem_solving", "competition"],
                "task_type": ["theorem_proving", "word_problem", "olympiad"],
                "source_dataset": ["src-a", "src-b", "src-c"],
                "difficulty": ["formal_proof", "basic_to_intermediate", "olympiad"],
                "conjecture_id": ["c1", "c2", "c3"],
                "sample_weight": [1.0, 1.0, 1.0],
            }
        )

        filtered = train_sota.apply_filters(
            dataset,
            {
                "include_difficulty_bands": ["lean_formal", "simple"],
                "require_lean_formal": True,
            },
        )

        self.assertEqual(len(filtered), 1)
        self.assertEqual(filtered[0]["family"], "formal_proof")
        self.assertEqual(filtered[0]["difficulty"], "formal_proof")

    def test_build_tokenizer_falls_back_when_protobuf_missing(self) -> None:
        class DummyTokenizer:
            def __init__(self) -> None:
                self.pad_token = None
                self.eos_token = "<eos>"
                self.unk_token = "<unk>"

            def add_special_tokens(self, tokens):
                self.pad_token = tokens.get("pad_token")

        calls = []

        def fake_from_pretrained(*args, **kwargs):
            calls.append(kwargs.get("use_fast"))
            if kwargs.get("use_fast"):
                raise ImportError("requires the protobuf library")
            return DummyTokenizer()

        with mock.patch.object(train_sota.AutoTokenizer, "from_pretrained", side_effect=fake_from_pretrained):
            tok = train_sota.build_tokenizer({"base_model": "dummy/model", "trust_remote_code": False})

        self.assertEqual(calls, [True, False])
        self.assertEqual(tok.pad_token, "<eos>")


@unittest.skipUnless(eval_sota is not None, "eval_sota runtime dependencies are not installed")
class EvalTokenizerFallbackTests(unittest.TestCase):
    def test_eval_tokenizer_falls_back_when_protobuf_missing(self) -> None:
        class DummyTokenizer:
            def __init__(self) -> None:
                self.pad_token = None
                self.eos_token = "<eos>"
                self.unk_token = "<unk>"

            def add_special_tokens(self, tokens):
                self.pad_token = tokens.get("pad_token")

        class DummyModel:
            def eval(self):
                return None

        calls = []

        def fake_tok_from_pretrained(*args, **kwargs):
            calls.append(kwargs.get("use_fast"))
            if kwargs.get("use_fast"):
                raise ImportError("requires the protobuf library")
            return DummyTokenizer()

        with mock.patch.object(eval_sota.AutoTokenizer, "from_pretrained", side_effect=fake_tok_from_pretrained):
            with mock.patch.object(eval_sota.AutoModelForCausalLM, "from_pretrained", return_value=DummyModel()):
                model, tok = eval_sota.load_model_and_tokenizer(
                    base_model="dummy/model",
                    adapter_path=None,
                    trust_remote_code=False,
                )

        self.assertIsNotNone(model)
        self.assertEqual(calls, [True, False])
        self.assertEqual(tok.pad_token, "<eos>")


@unittest.skipUnless(app is not None, "app runtime dependencies are not installed")
class ContinuousModeSafetyTests(unittest.TestCase):
    def test_continuous_mode_halts_after_consecutive_failures(self) -> None:
        original_max = app.CONTINUOUS_MAX_CONSECUTIVE_FAILURES
        original_delay = app.CONTINUOUS_RESTART_DELAY_SECONDS
        app.CONTINUOUS_MAX_CONSECUTIVE_FAILURES = 2
        app.CONTINUOUS_RESTART_DELAY_SECONDS = 0
        self.addCleanup(setattr, app, "CONTINUOUS_MAX_CONSECUTIVE_FAILURES", original_max)
        self.addCleanup(setattr, app, "CONTINUOUS_RESTART_DELAY_SECONDS", original_delay)

        def fake_pipeline_core(**kwargs):
            summary = json.dumps({"result": "failed"})
            yield "line-1", "Failed", summary

        with mock.patch.object(app, "run_pipeline_core", side_effect=fake_pipeline_core):
            outputs = list(
                app.run_pipeline(
                    dataset_repo_id="owner/dataset",
                    model_repo_id="owner/model",
                    base_model_id="model/base",
                    autonomous_mode=False,
                    continuous_mode=True,
                    start_stage=1,
                    max_stages=1,
                    run_eval=False,
                    eval_k=1,
                    eval_samples=50,
                    enforce_quality_gate=False,
                    gate_min_pass_at_1=0.0,
                    gate_min_pass_at_k=0.0,
                    gate_min_rows=10,
                    push_to_hub=False,
                    force_redownload=False,
                    preflight_only=False,
                )
            )

        self.assertGreaterEqual(len(outputs), 3)
        last_status = outputs[-1][1]
        self.assertIn("halted", last_status.lower())

    def test_continuous_mode_cooldown_stops_on_cancel(self) -> None:
        original_max = app.CONTINUOUS_MAX_CONSECUTIVE_FAILURES
        original_delay = app.CONTINUOUS_RESTART_DELAY_SECONDS
        app.CONTINUOUS_MAX_CONSECUTIVE_FAILURES = 3
        app.CONTINUOUS_RESTART_DELAY_SECONDS = 1
        self.addCleanup(setattr, app, "CONTINUOUS_MAX_CONSECUTIVE_FAILURES", original_max)
        self.addCleanup(setattr, app, "CONTINUOUS_RESTART_DELAY_SECONDS", original_delay)

        def fake_pipeline_core(**kwargs):
            summary = json.dumps({"result": "completed"})
            yield "line-1", "Completed", summary

        with mock.patch.object(app, "run_pipeline_core", side_effect=fake_pipeline_core):
            with mock.patch.object(app, "is_cancel_requested", return_value=True):
                outputs = list(
                    app.run_pipeline(
                        dataset_repo_id="owner/dataset",
                        model_repo_id="owner/model",
                        base_model_id="model/base",
                        autonomous_mode=False,
                        continuous_mode=True,
                        start_stage=1,
                        max_stages=1,
                        run_eval=False,
                        eval_k=1,
                        eval_samples=50,
                        enforce_quality_gate=False,
                        gate_min_pass_at_1=0.0,
                        gate_min_pass_at_k=0.0,
                        gate_min_rows=10,
                        push_to_hub=False,
                        force_redownload=False,
                        preflight_only=False,
                    )
                )

        self.assertGreaterEqual(len(outputs), 3)
        self.assertIn("stopped", outputs[-1][1].lower())


if __name__ == "__main__":
    unittest.main(verbosity=2)