"""Seed an HF Space with the trackio dashboard.

Background: when the agent creates a Space via `hf_repo_git create_repo` (or
the user pre-creates one), it ships with no app.py — so the iframe shows the
default Gradio "Get started" template instead of charts. Trackio's `init()`
detects the existing Space but does NOT auto-bootstrap dashboard files into it,
so the dashboard never materializes.

This helper writes the three files trackio's runtime expects (README.md,
requirements.txt, app.py) into the Space, idempotently, BEFORE the job that
will call `trackio.init()` runs. We deliberately omit `hf_oauth: true` from
the README so the embedded iframe in ml-intern renders without a login click —
per-user privacy is enforced by namespace ownership instead.

Beyond the dashboard files, the helper also creates the metrics bucket and
mounts it on the Space at `/data` (with `TRACKIO_DIR` / `TRACKIO_BUCKET_ID`
Space variables). Without this, the running job writes metrics into a bucket
that the dashboard Space can't read, and the iframe shows "No projects".
"""

from __future__ import annotations

import io
from typing import Callable, Optional

from huggingface_hub import (
    HfApi,
    Volume,
    add_space_variable,
    create_bucket,
    create_repo,
)
from huggingface_hub.utils import EntryNotFoundError, RepositoryNotFoundError


_README = """---
title: Trackio Dashboard
emoji: 📊
colorFrom: pink
colorTo: gray
sdk: gradio
app_file: app.py
pinned: false
tags:
  - trackio
---

Embedded trackio dashboard for ml-intern runs.
"""

_REQUIREMENTS = "trackio\n"
_APP_PY = "import trackio\ntrackio.show()\n"

# ml-intern brand mark surfaced inside the trackio dashboard. Trackio reads
# `TRACKIO_LOGO_LIGHT_URL` / `TRACKIO_LOGO_DARK_URL` from Space variables and
# renders them in place of its own logo. We point at the publicly-resolvable
# copy on the smolagents/ml-intern Space repo so any seeded dashboard inherits
# the ml-intern branding without each user having to host the asset.
_LOGO_URL = (
    "https://huggingface.co/spaces/smolagents/ml-intern/"
    "resolve/main/frontend/public/smolagents.webp"
)

_FILES = {
    "README.md": _README,
    "requirements.txt": _REQUIREMENTS,
    "app.py": _APP_PY,
}


def _already_seeded(api: HfApi, space_id: str) -> bool:
    """Cheap check: does the Space already have a trackio dashboard app.py?

    Avoids re-uploading the same three files on every job submission. We look
    for the literal `trackio.show` call which is the load-bearing line — any
    other app.py shape (the default gradio shell, a stale custom one) means
    we should re-seed.
    """
    try:
        path = api.hf_hub_download(
            repo_id=space_id, repo_type="space", filename="app.py"
        )
    except (EntryNotFoundError, RepositoryNotFoundError, OSError):
        return False
    try:
        with open(path, "r", encoding="utf-8") as f:
            return "trackio.show" in f.read()
    except OSError:
        return False


def _get_space_volumes(api: HfApi, space_id: str) -> list:
    """Return mounted volumes for a Space.

    `get_space_runtime()` doesn't always populate `volumes` even when the
    mount exists; mirror trackio's fallback to `space_info().runtime.volumes`.
    """
    runtime = api.get_space_runtime(space_id)
    if getattr(runtime, "volumes", None):
        return list(runtime.volumes)
    info = api.space_info(space_id)
    if info.runtime and getattr(info.runtime, "volumes", None):
        return list(info.runtime.volumes)
    return []


def _ensure_bucket_mounted(
    api: HfApi,
    space_id: str,
    bucket_id: str,
    hf_token: str,
    log: Optional[Callable[[str], None]] = None,
) -> None:
    """Create the bucket if missing, mount it at `/data` on the Space, and
    set the `TRACKIO_DIR` / `TRACKIO_BUCKET_ID` Space variables. Idempotent —
    skips work that has already been done.
    """
    create_bucket(bucket_id, private=True, exist_ok=True, token=hf_token)

    existing = _get_space_volumes(api, space_id)
    already_mounted = any(
        getattr(v, "type", None) == "bucket"
        and getattr(v, "source", None) == bucket_id
        and getattr(v, "mount_path", None) == "/data"
        for v in existing
    )
    if not already_mounted:
        preserved = [
            v
            for v in existing
            if not (
                getattr(v, "type", None) == "bucket"
                and (
                    getattr(v, "source", None) == bucket_id
                    or getattr(v, "mount_path", None) == "/data"
                )
            )
        ]
        api.set_space_volumes(
            space_id,
            preserved + [Volume(type="bucket", source=bucket_id, mount_path="/data")],
        )
        if log:
            log(f"mounted bucket {bucket_id} at /data on {space_id}")

    variables = api.get_space_variables(space_id)
    desired = {
        "TRACKIO_DIR": "/data/trackio",
        "TRACKIO_BUCKET_ID": bucket_id,
        "TRACKIO_LOGO_LIGHT_URL": _LOGO_URL,
        "TRACKIO_LOGO_DARK_URL": _LOGO_URL,
    }
    for key, value in desired.items():
        if getattr(variables.get(key), "value", None) != value:
            add_space_variable(space_id, key, value, token=hf_token)


def ensure_trackio_dashboard(
    space_id: str,
    hf_token: str,
    log: Optional[Callable[[str], None]] = None,
) -> bool:
    """Make sure *space_id* is fully wired for trackio:
    1. Space exists with our dashboard files (README without `hf_oauth`,
       `requirements.txt`, `app.py` calling `trackio.show`).
    2. Bucket `<space_id>-bucket` exists, is mounted at `/data`, and the
       Space has `TRACKIO_DIR` / `TRACKIO_BUCKET_ID` variables set.

    Idempotent — re-running is cheap. Returns True if any seeding happened
    in step (1), False if the dashboard files were already in place. Bucket
    mount is always re-checked.
    """
    api = HfApi(token=hf_token)

    create_repo(
        repo_id=space_id,
        repo_type="space",
        space_sdk="gradio",
        exist_ok=True,
        token=hf_token,
    )

    seeded_files = False
    if _already_seeded(api, space_id):
        if log:
            log(f"trackio dashboard already seeded on {space_id}")
    else:
        if log:
            log(f"seeding trackio dashboard files into {space_id}")
        for path_in_repo, content in _FILES.items():
            api.upload_file(
                path_or_fileobj=io.BytesIO(content.encode("utf-8")),
                path_in_repo=path_in_repo,
                repo_id=space_id,
                repo_type="space",
                commit_message=f"ml-intern: seed trackio dashboard ({path_in_repo})",
            )
        seeded_files = True

    bucket_id = f"{space_id}-bucket"
    _ensure_bucket_mounted(api, space_id, bucket_id, hf_token, log)

    if log:
        log(f"trackio dashboard ready: https://huggingface.co/spaces/{space_id}")
    return seeded_files