"""One-shot script — duplicate upstream Wan-AI / lightx2v repos into our account
for Phase 1 resilience. Run BEFORE create_space.py.

Idempotent — skips destinations that already exist.

Phase 1 scope:
  - 5 base model repos (T2V / I2V on Wan 2.1 14B + Wan 2.2 A14B)
  - 3 Lightning LoRA upstream repos consolidated into a single mirror via curated
    file uploads (avoids mirroring all of Kijai/WanVideo_comfy's terabytes)

Usage:
  python scripts/duplicate_upstream.py --dry-run    # print plan
  python scripts/duplicate_upstream.py              # execute
"""
from __future__ import annotations

import argparse
import sys
import tempfile

from huggingface_hub import HfApi, hf_hub_download


# Base model duplicates — full repo copies.
PHASE_1_BASE_DUPLICATES: list[tuple[str, str]] = [
    ("Wan-AI/Wan2.1-T2V-14B-Diffusers",      "techfreakworm/wan2.1-t2v-14b"),
    ("Wan-AI/Wan2.1-I2V-14B-480P-Diffusers", "techfreakworm/wan2.1-i2v-14b-480p"),
    ("Wan-AI/Wan2.1-I2V-14B-720P-Diffusers", "techfreakworm/wan2.1-i2v-14b-720p"),
    ("Wan-AI/Wan2.2-T2V-A14B-Diffusers",     "techfreakworm/wan2.2-t2v-a14b"),
    ("Wan-AI/Wan2.2-I2V-A14B-Diffusers",     "techfreakworm/wan2.2-i2v-a14b"),
]

# Lightning LoRA files — pulled from various upstream and uploaded into ONE mirror.
# (upstream_repo, upstream_filename, mirror_path_inside_techfreakworm/wan-lightning-loras)
LIGHTNING_FILES: list[tuple[str, str, str]] = [
    # Wan 2.1 T2V-14B (single LoRA — community-recommended rank-128 v2)
    (
        "Kijai/WanVideo_comfy",
        "Lightx2v/lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank128_bf16.safetensors",
        "wan2.1-t2v-14b/lightning.safetensors",
    ),
    # Wan 2.1 I2V-14B 480P
    (
        "lightx2v/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v",
        "loras/Wan21_I2V_14B_lightx2v_cfg_step_distill_lora_rank64.safetensors",
        "wan2.1-i2v-14b-480p/lightning.safetensors",
    ),
    # Wan 2.1 I2V-14B 720P (same LoRA file actually works per RESEARCH §5.1; we
    # mirror the 720P-tagged copy for clarity)
    (
        "lightx2v/Wan2.1-I2V-14B-720P-StepDistill-CfgDistill-Lightx2v",
        "loras/Wan21_I2V_14B_lightx2v_cfg_step_distill_lora_rank64.safetensors",
        "wan2.1-i2v-14b-720p/lightning.safetensors",
    ),
    # Wan 2.2 T2V-A14B — paired HIGH + LOW (V2.0 / 250928 — latest stable)
    (
        "Kijai/WanVideo_comfy",
        "LoRAs/Wan22-Lightning/Wan22_A14B_T2V_HIGH_Lightning_4steps_lora_250928_rank128_fp16.safetensors",
        "wan2.2-t2v-a14b/lightning_high.safetensors",
    ),
    (
        "Kijai/WanVideo_comfy",
        "LoRAs/Wan22-Lightning/Wan22_A14B_T2V_LOW_Lightning_4steps_lora_250928_rank64_fp16.safetensors",
        "wan2.2-t2v-a14b/lightning_low.safetensors",
    ),
    # Wan 2.2 I2V-A14B — V1 Seko (no V2 as of May 2026 per RESEARCH §5.1.3)
    (
        "Kijai/WanVideo_comfy",
        "LoRAs/Wan22-Lightning/old/Wan2.2-Lightning_I2V-A14B-4steps-lora_HIGH_fp16.safetensors",
        "wan2.2-i2v-a14b/lightning_high.safetensors",
    ),
    (
        "Kijai/WanVideo_comfy",
        "LoRAs/Wan22-Lightning/old/Wan2.2-Lightning_I2V-A14B-4steps-lora_LOW_fp16.safetensors",
        "wan2.2-i2v-a14b/lightning_low.safetensors",
    ),
]

LIGHTNING_MIRROR = "techfreakworm/wan-lightning-loras"


def duplicate_base(api: HfApi, dry_run: bool) -> None:
    for upstream, dest in PHASE_1_BASE_DUPLICATES:
        if dry_run:
            print(f"  [dry] duplicate_repo({upstream!r} → {dest!r})")
            continue
        try:
            api.model_info(dest)
            print(f"  ✓ already exists: {dest}")
            continue
        except Exception:
            pass
        print(f"  ↻ duplicating {upstream} → {dest}", flush=True)
        api.duplicate_repo(from_id=upstream, to_id=dest, repo_type="model")
        print(f"  ✓ done: https://huggingface.co/{dest}")


def build_lightning_mirror(api: HfApi, dry_run: bool) -> None:
    if dry_run:
        print(f"  [dry] create_repo({LIGHTNING_MIRROR!r})")
        for src_repo, src_file, dst_path in LIGHTNING_FILES:
            print(f"    [dry] {src_repo}/{src_file} → {LIGHTNING_MIRROR}/{dst_path}")
        return

    try:
        api.model_info(LIGHTNING_MIRROR)
        print(f"  ✓ mirror repo exists: {LIGHTNING_MIRROR}")
    except Exception:
        api.create_repo(repo_id=LIGHTNING_MIRROR, repo_type="model", private=False)
        print(f"  ✓ created mirror repo: {LIGHTNING_MIRROR}")

    with tempfile.TemporaryDirectory() as tmpdir:
        for src_repo, src_file, dst_path in LIGHTNING_FILES:
            print(f"  ↻ {src_repo}/{src_file}  →  {LIGHTNING_MIRROR}/{dst_path}", flush=True)
            local = hf_hub_download(
                repo_id=src_repo, filename=src_file, cache_dir=tmpdir,
            )
            api.upload_file(
                path_or_fileobj=local,
                path_in_repo=dst_path,
                repo_id=LIGHTNING_MIRROR,
                repo_type="model",
                commit_message=f"Mirror {src_file}",
            )
            print(f"  ✓ uploaded {dst_path}")


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--dry-run", action="store_true")
    args = parser.parse_args()

    api = HfApi()
    print(f"Logged in as: {api.whoami()['name']}")

    print("=== Phase 1 base model duplicates ===")
    duplicate_base(api, args.dry_run)

    print("\n=== Phase 1 Lightning LoRA mirror ===")
    build_lightning_mirror(api, args.dry_run)


if __name__ == "__main__":
    sys.exit(main())