# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Regression tests for Qwen3-VL processor.

Covers the fix for num_frames-based timestamp calculation
(issue vllm-project/vllm#35909).
"""

from typing import Any

import numpy as np
import pytest

from vllm.multimodal import MULTIMODAL_REGISTRY

from ...utils import build_model_context

MODEL_ID = "Qwen/Qwen3-VL-4B-Instruct"


def _build_video_mm_data(
    num_frames: int,
    width: int = 128,
    height: int = 128,
    original_fps: float = 30.0,
) -> dict[str, Any]:
    """Create synthetic video data with metadata indicating that
    HF processor should re-sample frames (do_sample_frames=True).

    ``total_num_frames`` is set equal to the ndarray frame count so
    that HF's ``sample_frames`` indices stay within bounds of the
    actual tensor that is passed."""
    video = np.zeros((num_frames, height, width, 3), dtype=np.uint8)
    metadata = {
        "fps": original_fps,
        "duration": num_frames / original_fps,
        "total_num_frames": num_frames,
        "frames_indices": list(range(num_frames)),
        "video_backend": "opencv",
        "do_sample_frames": True,
    }
    return {"video": [(video, metadata)]}


@pytest.mark.parametrize("model_id", [MODEL_ID])
@pytest.mark.parametrize(
    "num_frames",
    [8, 16],
)
def test_processor_num_frames_timestamp(
    model_id: str,
    num_frames: int,
) -> None:
    """Regression test: using ``num_frames`` (without ``fps``) must not
    cause a timestamp / token-count mismatch.

    Before the fix, ``_get_video_second_idx`` ignored the explicit
    ``num_frames`` and fell back to an fps-based calculation, which
    produced a different number of timestamp entries and ultimately led
    to shape mismatches in downstream token construction.

    We deliberately choose ``num_frames`` values (8, 16) that differ
    from what the default fps-based path would compute (which clamps
    to ``min_frames=4`` for a short video at 30 fps), so this test
    would fail without the fix.
    """
    ctx = build_model_context(
        model_id,
        limit_mm_per_prompt={"image": 0, "video": 1},
    )
    processor = MULTIMODAL_REGISTRY.create_processor(ctx.model_config)

    prompt = "<|vision_start|><|video_pad|><|vision_end|>"
    mm_data = _build_video_mm_data(num_frames=num_frames)

    # Process with explicit num_frames (no fps) -- this is the path
    # that was broken before the fix.
    hf_mm_kwargs: dict[str, Any] = {"num_frames": num_frames}
    processed = processor(
        prompt,
        mm_items=processor.info.parse_mm_data(mm_data),
        hf_processor_mm_kwargs=hf_mm_kwargs,
    )

    # Basic sanity: the processor must produce video tokens.
    token_ids = processed["prompt_token_ids"]
    assert len(token_ids) > 0, "Processor produced empty token list"

    # Verify that video placeholders were actually inserted.
    assert "mm_placeholders" in processed
    video_phs = processed["mm_placeholders"].get("video", [])
    assert len(video_phs) == 1, (
        f"Expected exactly 1 video placeholder, got {len(video_phs)}"
    )