"""Phase 2 component test: dense Wan2.2-TI2V-5B-Turbo pipeline + LoRA stacking.

Verifies:
- ``Wan22Pipeline`` loads successfully (exercises the real LightX2V
  set_config -> init_runner flow).
- ``load_loras`` / ``unload_loras`` survive with any user LoRAs at
  ``/cache/loras/*.safetensors`` (target='both', dense single DIT).

Supports any GGUF quant published in hum-ma/Wan2.2-TI2V-5B-Turbo-GGUF.
Set ``DIT_QUANT`` to switch (default: ``gguf-Q8_0``).

    DIT_QUANT=gguf-Q4_K_M docker compose exec voice-chat \
        python -m tests.component.test_02_wan22_loras

Requires GPU and a first-run download of the base repo + GGUF DIT.
If LightX2V isn't installed the test is skipped.

Run:
    docker compose exec voice-chat python -m tests.component.test_02_wan22_loras
"""
from __future__ import annotations

import glob
import os
import sys

from tests.component._common import get_logger

log = get_logger("test_02")

DIT_QUANT = os.environ.get("DIT_QUANT", "gguf-Q8_0")
CONFIG_JSON = "/app/configs/lightx2v/wan22_i2v_gguf_5b_turbo.json"
DIT_REPO = "hum-ma/Wan2.2-TI2V-5B-Turbo-GGUF"


def run():
    try:
        from server.video_models.wan22 import Wan22Pipeline
    except ImportError as e:
        log.error("Wan22Pipeline import failed: %s", e)
        log.warning("SKIP: phase 2 deps not installed")
        sys.exit(0)

    from server.video import LoRASpec

    log.info("[case 1] Instantiate Wan22Pipeline "
             "(quant=%s, dit_repo=%s)...", DIT_QUANT, DIT_REPO)
    try:
        pipe = Wan22Pipeline(
            base_repo="Wan-AI/Wan2.2-TI2V-5B",
            dit_repo=DIT_REPO,
            config_json=CONFIG_JSON,
            model_cls="wan2.2",
            resolution=480,
            fps=16,
            dit_quant_scheme=DIT_QUANT,
            t5_quantized=True,
        )
    except Exception as e:
        log.error("FAIL: Wan22Pipeline construction raised: %s", e)
        log.error("Check: LightX2V install, HF cache at /cache/huggingface, "
                  "VRAM headroom, and that %s exists inside the container.",
                  CONFIG_JSON)
        sys.exit(2)
    log.info("  PASS: pipeline constructed")

    # --- LoRAs ---
    log.info("[case 2] load_loras with empty list -> no-op")
    pipe.load_loras([])
    log.info("  PASS")

    lora_files = sorted(glob.glob("/cache/loras/*.safetensors"))
    if not lora_files:
        log.warning("SKIP: no LoRA files found in /cache/loras/")
        log.info("ALL PASSED (partial — LoRA cases skipped)")
        return

    lora_path = lora_files[0]
    log.info("[case 3] load_loras with one 5B-compatible LoRA (%s)", lora_path)
    specs = [
        LoRASpec(
            path=lora_path,
            weight=1.0,
            target="both",
            name=os.path.basename(lora_path),
        ),
    ]
    try:
        pipe.load_loras(specs)
    except Exception as e:
        log.error("FAIL: load_loras raised: %s", e)
        log.error("Check: LoRA checkpoint shape matches dense 5B DIT.")
        sys.exit(3)
    log.info("  PASS: LoRAs applied")

    log.info("[case 4] unload_loras")
    try:
        pipe.unload_loras()
    except Exception as e:
        log.error("FAIL: unload_loras raised: %s", e)
        sys.exit(4)
    log.info("  PASS")

    log.info("ALL PASSED")


if __name__ == "__main__":
    run()