"""Tests for the LangGraph detection pipeline."""

import os

import pytest

from detect.graph import NODES, build_graph, get_pipeline
from detect.models import PipelineStats
from detect.state import DetectState

VIDEO = "media/out/chunks/95043d50-4df6-4ac8-bbd5-2ba873117c6e/chunk_0000.mp4"


def _has_inference() -> bool:
    if os.environ.get("INFERENCE_URL"):
        return True
    try:
        import ultralytics
        return True
    except ImportError:
        return False


requires_inference = pytest.mark.skipif(
    not _has_inference(),
    reason="Needs INFERENCE_URL or ultralytics installed",
)


def test_graph_compiles():
    pipeline = get_pipeline()
    assert pipeline is not None


def test_graph_has_all_nodes():
    graph = build_graph()
    for node in NODES:
        assert node in graph.nodes


@requires_inference
def test_graph_runs_end_to_end(monkeypatch):
    """Run the full graph with mocked event emission."""
    events = []
    monkeypatch.setattr("detect.emit.push_detect_event",
                        lambda job_id, etype, data: events.append((etype, data)))

    pipeline = get_pipeline()
    initial_state = DetectState(
        video_path=VIDEO,
        job_id="test-graph",
        profile_name="soccer_broadcast",
    )

    result = pipeline.invoke(initial_state)

    # All nodes should have transitioned
    graph_events = [e for e in events if e[0] == "graph_update"]
    assert len(graph_events) > 0

    # Should have frames
    assert len(result["frames"]) > 0
    assert len(result["filtered_frames"]) > 0

    # Report should exist
    assert result["report"] is not None
    assert result["report"].content_type == "soccer_broadcast"

    # job_complete should have been emitted
    complete_events = [e for e in events if e[0] == "job_complete"]
    assert len(complete_events) == 1


@requires_inference
def test_graph_node_transitions(monkeypatch):
    """Verify each node emits running → done transitions."""
    events = []
    monkeypatch.setattr("detect.emit.push_detect_event",
                        lambda job_id, etype, data: events.append((etype, data)))

    pipeline = get_pipeline()
    initial_state = DetectState(
        video_path=VIDEO,
        job_id="test-transitions",
        profile_name="soccer_broadcast",
    )

    pipeline.invoke(initial_state)

    graph_events = [e[1] for e in events if e[0] == "graph_update"]

    # Each node should appear as "running" then "done"
    for node_name in NODES:
        running = [e for e in graph_events
                   if any(n["id"] == node_name and n["status"] == "running" for n in e["nodes"])]
        done = [e for e in graph_events
                if any(n["id"] == node_name and n["status"] == "done" for n in e["nodes"])]
        assert len(running) >= 1, f"{node_name} never entered 'running'"
        assert len(done) >= 1, f"{node_name} never reached 'done'"