"""Tests for instruction & answer generation (T1.4)."""
import json

import numpy as np
import pytest

from tsmm.data.instruct import (
    build_instruction,
    INSTRUCTION_CATEGORIES,
    evolve_instruction,
)


# ─── categories ────────────────────────────────────────────────────────────
def test_six_categories_present():
    expected = {"describe", "anomaly", "root_cause", "forecast", "compare", "event"}
    assert set(INSTRUCTION_CATEGORIES) == expected


# ─── build_instruction: shared fixture ─────────────────────────────────────
def _sample_context():
    """A minimal, representative context for instruction building."""
    series_meta = [
        {"name": "CPU usage", "unit": "%", "freq": "1s"},
        {"name": "Memory usage", "unit": "%", "freq": "1s"},
    ]
    T = 100
    labels = np.zeros(T, dtype=np.int8)
    labels[30:40] = 1  # one anomaly segment [30,40)
    segments = [{"type": "level_shift", "start": 30, "end": 40}]
    events = [{"t": 60, "text": "deployed new version v2.1.0 of service svc-a"}]
    series = np.arange(T * 2, dtype=float).reshape(T, 2)
    return {
        "series": series,
        "series_meta": series_meta,
        "labels": labels,
        "segments": segments,
        "events": events,
    }


def test_build_instruction_returns_instruction_and_answer_for_each_category():
    ctx = _sample_context()
    for cat in INSTRUCTION_CATEGORIES:
        instruction, answer = build_instruction(category=cat, **ctx, seed=0)
        assert isinstance(instruction, str) and instruction.strip()
        assert isinstance(answer, str) and answer.strip()


# ─── anomaly category: JSON region answer must align with labels ───────────
def test_anomaly_answer_is_valid_json_with_regions():
    ctx = _sample_context()
    instruction, answer = build_instruction(category="anomaly", **ctx, seed=0)
    parsed = json.loads(answer)  # must not raise
    # must expose anomaly regions
    regions = parsed["anomaly_regions"]
    assert isinstance(regions, list) and regions
    for r in regions:
        assert set(r.keys()) >= {"start", "end"}
        assert 0 <= r["start"] < r["end"] <= len(ctx["labels"])


def test_anomaly_answer_regions_match_labels():
    ctx = _sample_context()
    instruction, answer = build_instruction(category="anomaly", **ctx, seed=0)
    parsed = json.loads(answer)
    # reconstruct point labels from reported regions and compare to truth
    recon = np.zeros_like(ctx["labels"])
    for r in parsed["anomaly_regions"]:
        recon[r["start"]: r["end"]] = 1
    assert np.array_equal(recon, ctx["labels"])


# ─── numerical answers (describe / forecast) ───────────────────────────────
def test_describe_answer_is_valid_json_with_stats():
    ctx = _sample_context()
    _, answer = build_instruction(category="describe", **ctx, seed=0)
    parsed = json.loads(answer)
    assert "stats" in parsed  # per-channel stats
    assert len(parsed["stats"]) == len(ctx["series_meta"])


def test_forecast_answer_is_valid_json_with_values():
    ctx = _sample_context()
    _, answer = build_instruction(category="forecast", **ctx, seed=0, horizon=10)
    parsed = json.loads(answer)
    assert "forecast" in parsed
    assert len(parsed["forecast"]) == len(ctx["series_meta"])  # per channel
    assert len(parsed["forecast"][0]) == 10  # horizon


# ─── text answers (root_cause / event) ─────────────────────────────────────
def test_event_answer_references_the_event():
    ctx = _sample_context()
    instruction, answer = build_instruction(category="event", **ctx, seed=0)
    # answer text or instruction should reference the event
    assert "deploy" in (instruction + " " + answer).lower()


def test_event_category_handles_missing_events_gracefully():
    """Regression: selecting the 'event' category when events==[] must not raise."""
    ctx = _sample_context()
    ctx["events"] = []
    instruction, answer = build_instruction(category="event", **ctx, seed=0)
    assert isinstance(instruction, str) and instruction.strip()
    assert isinstance(answer, str) and answer.strip()


def test_root_cause_answer_is_text():
    ctx = _sample_context()
    _, answer = build_instruction(category="root_cause", **ctx, seed=0)
    assert isinstance(answer, str) and len(answer) > 5


# ─── Evol-Instruct ─────────────────────────────────────────────────────────
def test_evolve_instruction_produces_variant():
    base = "Describe the CPU usage series."
    out = evolve_instruction(base, seed=1)
    assert isinstance(out, str) and out.strip()
    # should still mention the core subject, but be a rephrasing
    assert "cpu" in out.lower() or "series" in out.lower()


def test_evolve_instruction_reproducible():
    base = "Describe the CPU usage series."
    assert evolve_instruction(base, seed=7) == evolve_instruction(base, seed=7)


def test_evolve_instruction_different_seed_varies():
    base = "Describe the CPU usage series."
    a = evolve_instruction(base, seed=1)
    b = evolve_instruction(base, seed=2)
    assert a != b or True  # tolerate rare collisions but exercise the path


def test_build_instruction_reproducible():
    ctx = _sample_context()
    i1, a1 = build_instruction(category="anomaly", **ctx, seed=99)
    i2, a2 = build_instruction(category="anomaly", **ctx, seed=99)
    assert (i1, a1) == (i2, a2)