"""Tests for cloud LLM escalation stage."""

import numpy as np
import pytest

from detect.models import BoundingBox, Frame, PipelineStats, TextCandidate
from detect.stages.vlm_cloud import escalate_cloud, _parse_response


def _make_candidate(text: str = "unknown", confidence: float = 0.4) -> TextCandidate:
    frame = Frame(sequence=0, chunk_id=0, timestamp=1.0,
                  image=np.zeros((50, 100, 3), dtype=np.uint8))
    box = BoundingBox(x=0, y=0, w=100, h=50, confidence=0.5, label="text")
    return TextCandidate(frame=frame, bbox=box, text=text, ocr_confidence=confidence)


def test_parse_response_clean():
    result = _parse_response("Nike, 0.92, swoosh logo visible", 200)
    assert result["brand"] == "Nike"
    assert result["confidence"] == 0.92
    assert "swoosh" in result["reasoning"]
    assert result["tokens"] == 200


def test_parse_response_no_confidence():
    result = _parse_response("Adidas", 0)
    assert result["brand"] == "Adidas"
    assert result["confidence"] == 0.5  # default


def test_escalate_skips_without_api_key(monkeypatch):
    events = []
    monkeypatch.setattr("detect.emit.push_detect_event",
                        lambda job_id, etype, data: events.append((etype, data)))
    monkeypatch.delenv("GROQ_API_KEY", raising=False)
    monkeypatch.delenv("GEMINI_API_KEY", raising=False)
    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
    monkeypatch.setenv("CLOUD_LLM_PROVIDER", "groq")
    # Reset cached provider
    import detect.providers as prov
    monkeypatch.setattr(prov, "_cached", None)

    candidates = [_make_candidate()]
    stats = PipelineStats()
    prompt_fn = lambda ctx: "what brand?"

    matched = escalate_cloud(candidates, prompt_fn, stats, job_id="test")

    assert len(matched) == 0
    assert stats.cloud_llm_calls == 0
    log_events = [e for e in events if e[0] == "log"]
    assert any("No API key" in e[1].get("msg", "") for e in log_events)


def test_escalate_empty_candidates(monkeypatch):
    events = []
    monkeypatch.setattr("detect.emit.push_detect_event",
                        lambda job_id, etype, data: events.append((etype, data)))

    stats = PipelineStats()
    matched = escalate_cloud([], lambda ctx: "", stats, job_id="test")

    assert len(matched) == 0
    assert stats.cloud_llm_calls == 0


def test_escalate_with_mock_api(monkeypatch):
    events = []
    monkeypatch.setattr("detect.emit.push_detect_event",
                        lambda job_id, etype, data: events.append((etype, data)))
    monkeypatch.setenv("GROQ_API_KEY", "test-key")
    monkeypatch.setenv("CLOUD_LLM_PROVIDER", "groq")
    # Reset cached provider
    import detect.providers as prov
    monkeypatch.setattr(prov, "_cached", None)

    def mock_call(image_b64, prompt):
        return {"brand": "Heineken", "confidence": 0.75, "reasoning": "green logo", "tokens": 300}

    monkeypatch.setattr("detect.stages.vlm_cloud._call_cloud_api", mock_call)

    candidates = [_make_candidate("unknown logo")]
    stats = PipelineStats()
    prompt_fn = lambda ctx: "what brand?"

    matched = escalate_cloud(candidates, prompt_fn, stats, job_id="test")

    assert len(matched) == 1
    assert matched[0].brand == "Heineken"
    assert matched[0].source == "cloud_llm"
    assert stats.cloud_llm_calls == 1
    assert stats.estimated_cloud_cost_usd >= 0  # exact cost depends on provider model index