#!/usr/bin/env python3
"""Update every repo's README *and* the helper scripts in one run.

Korean  README  <- WORKFLOW.md        -> JSHNSL/humanoid-imitation-learning     (model)
English README  <- WORKFLOW_en.md     -> JSHNSL/humanoid-imitation-learning-en  (model)
HDF5 hub README <- HDF5_HUB_README.md -> JSHNSL/ffw_sg2_hdf5                    (dataset)
Scripts (push_dataset.py, push_hdf5.py, hpo_optuna.py, ...) -> Korean repo root

Whenever you edit a WORKFLOW/README or a script, run:
    lerobot-python sync_docs.py

Note: recent huggingface_hub versions accept keyword arguments only.
"""
import os

from huggingface_hub import create_repo, upload_file

KO = "JSHNSL/humanoid-imitation-learning"
EN = "JSHNSL/humanoid-imitation-learning-en"
HDF5_HUB = "JSHNSL/ffw_sg2_hdf5"

# Scripts published at the repo root (must match the tree in WORKFLOW.md).
SCRIPTS = [
    "push_dataset.py",      # LeRobot dataset -> training dataset repo
    "push_hdf5.py",         # raw HDF5 -> HDF5 hub dataset repo
    "merge_hdf5_demos.py",  # HDF5 merge
    "hpo_optuna.py",        # Optuna HPO + train from tuned params
    "hpo_train_shim.py",    # lerobot_train w/ EpisodeAwareSampler fixed for subsets
    "sync_docs.py",         # this file
]

# (local_file, path_in_repo, repo_id, repo_type)
DOCS = [
    ("WORKFLOW.md", "README.md", KO, "model"),
    ("WORKFLOW.md", "WORKFLOW.md", KO, "model"),
    ("WORKFLOW_en.md", "README.md", EN, "model"),
    ("WORKFLOW_en.md", "WORKFLOW_en.md", EN, "model"),
    ("HDF5_HUB_README.md", "README.md", HDF5_HUB, "dataset"),
    # Guides published alongside the KO workflow.
    ("SETUP_CYCLO_GROOT.md", "SETUP_CYCLO_GROOT.md", KO, "model"),
    ("GROOT_FINETUNE.md", "GROOT_FINETUNE.md", KO, "model"),
    ("WRIST_CAM.md", "WRIST_CAM.md", KO, "model"),
]


def push(local: str, dest: str, repo_id: str, repo_type: str = "model") -> None:
    upload_file(
        path_or_fileobj=local,
        path_in_repo=dest,
        repo_id=repo_id,
        repo_type=repo_type,
    )


# The HDF5 hub may not exist yet (its README can land before any HDF5 does).
create_repo(repo_id=HDF5_HUB, repo_type="dataset", exist_ok=True)

print("Docs:")
for local, dest, repo, rtype in DOCS:
    if not os.path.exists(local):
        print(f"  skip (not found): {local}")
        continue
    push(local, dest, repo, rtype)
    print(f"  {local} -> {repo}:{dest}  [{rtype}]")

print("\nScripts:")
for s in SCRIPTS:
    if not os.path.exists(s):
        print(f"  skip (not found): {s}")
        continue
    push(s, s, KO, "model")
    print(f"  {s} -> {KO}:{s}")

print("\nDone:")
print("  KO       ->", "https://huggingface.co/" + KO)
print("  EN       ->", "https://huggingface.co/" + EN)
print("  HDF5 hub ->", "https://huggingface.co/datasets/" + HDF5_HUB)