#!/usr/bin/env python3
"""Build and optionally deploy the final PolyGuard artifact Space.

The script is intentionally packaging-only: it does not train or modify model
weights. It mirrors the best tracked evidence into docs/results, packages the
available model artifacts into a separate Hugging Face Space, and records
missing artifacts honestly in a manifest.
"""

from __future__ import annotations

import argparse
import html
import json
import os
from pathlib import Path
import shutil
from typing import Any

import matplotlib

matplotlib.use("Agg")
import matplotlib.pyplot as plt  # noqa: E402

from huggingface_hub import HfApi  # noqa: E402


ROOT = Path(__file__).resolve().parents[1]
DEFAULT_SPACE_ID = "adithya9903/polyguard-openenv-final-artifacts"
DEFAULT_DOCS_DIR = ROOT / "docs" / "results" / "final_submission_evidence"
DEFAULT_SPACE_DIR = Path("/tmp/polyguard-final-artifact-space")
EVIDENCE_DIR = ROOT / "docs" / "results" / "submission_evidence_qwen_0_5b_1_5b_3b"
SWEEP_REPORT_DIR = ROOT / "outputs" / "reports" / "sweeps"
SWEEP_CHECKPOINT_DIR = ROOT / "checkpoints" / "sweeps"


RUNS = {
    "qwen-qwen2-5-0-5b-instruct": {
        "label": "Qwen 0.5B",
        "model_id": "Qwen/Qwen2.5-0.5B-Instruct",
    },
    "qwen-qwen2-5-1-5b-instruct": {
        "label": "Qwen 1.5B",
        "model_id": "Qwen/Qwen2.5-1.5B-Instruct",
    },
    "qwen-qwen2-5-3b-instruct": {
        "label": "Qwen 3B",
        "model_id": "Qwen/Qwen2.5-3B-Instruct",
    },
}


FRONTPAGE_CHARTS = {
    "01_basic_llm_vs_full_pipeline_reward.png": (
        EVIDENCE_DIR / "charts" / "generated" / "basic_llm_vs_full_pipeline_reward.png"
    ),
    "02_reward_delta_by_seed.png": (
        EVIDENCE_DIR / "charts" / "generated" / "basic_llm_vs_full_pipeline_reward_delta_by_seed.png"
    ),
    "03_policy_ablation_reward.png": (
        EVIDENCE_DIR / "charts" / "generated" / "policy_ablation_avg_reward.png"
    ),
    "04_reward_components.png": (
        EVIDENCE_DIR / "charts" / "generated" / "reward_component_bars.png"
    ),
    "05_train_holdout_gap.png": (
        EVIDENCE_DIR / "charts" / "local_available_combined" / "train_holdout_gap.png"
    ),
    "06_inference_latency_validity.png": (
        EVIDENCE_DIR / "charts" / "local_available_combined" / "inference_latency_validity.png"
    ),
    "07_sft_vs_grpo_reward.png": (
        EVIDENCE_DIR / "charts" / "local_available_combined" / "sft_vs_grpo_reward.png"
    ),
}


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(description="Deploy the final PolyGuard artifact Space.")
    parser.add_argument("--space-id", default=DEFAULT_SPACE_ID)
    parser.add_argument("--docs-dir", default=str(DEFAULT_DOCS_DIR))
    parser.add_argument("--space-dir", default=str(DEFAULT_SPACE_DIR))
    parser.add_argument("--public", action="store_true", help="Create/update the Space as public.")
    parser.add_argument("--deploy", action="store_true", help="Upload the Space bundle to Hugging Face.")
    parser.add_argument("--skip-docs", action="store_true")
    return parser.parse_args()


def load_json(path: Path, default: Any) -> Any:
    if not path.exists():
        return default
    try:
        return json.loads(path.read_text(encoding="utf-8"))
    except json.JSONDecodeError:
        return default


def write_json(path: Path, payload: Any) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    path.write_text(json.dumps(payload, ensure_ascii=True, indent=2) + "\n", encoding="utf-8")


def write_text(path: Path, text: str) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    path.write_text(text, encoding="utf-8")


def copy_file(src: Path, dst: Path) -> bool:
    if not src.exists():
        return False
    dst.parent.mkdir(parents=True, exist_ok=True)
    shutil.copy2(src, dst)
    return True


def copy_tree(src: Path, dst: Path) -> dict[str, Any]:
    if not src.exists():
        return {"exists": False, "file_count": 0, "bytes": 0}
    if dst.exists():
        shutil.rmtree(dst)
    shutil.copytree(src, dst, ignore=shutil.ignore_patterns(".DS_Store", "__pycache__", "*.pyc"))
    files = [path for path in dst.rglob("*") if path.is_file()]
    return {
        "exists": True,
        "file_count": len(files),
        "bytes": sum(path.stat().st_size for path in files),
    }


def dir_size(path: Path) -> int:
    if not path.exists():
        return 0
    return sum(item.stat().st_size for item in path.rglob("*") if item.is_file())


def summarize_artifact_dir(path: Path) -> dict[str, Any]:
    return {
        "exists": path.exists(),
        "file_count": len([p for p in path.rglob("*") if p.is_file()]) if path.exists() else 0,
        "bytes": dir_size(path),
    }


def plot_model_reward(summary: dict[str, Any], path: Path) -> None:
    labels: list[str] = []
    sft: list[float] = []
    grpo: list[float | None] = []
    for model in summary.get("models", []):
        metrics = model.get("metrics", {})
        labels.append(str(model.get("label") or model.get("run_id")))
        sft.append(float(metrics.get("sft_avg_env_reward") or 0.0))
        value = metrics.get("grpo_avg_env_reward")
        grpo.append(float(value) if value is not None else None)

    if not labels:
        return
    path.parent.mkdir(parents=True, exist_ok=True)
    x = list(range(len(labels)))
    width = 0.35
    plt.figure(figsize=(9.5, 5))
    plt.bar([i - width / 2 for i in x], sft, width=width, label="SFT baseline")
    grpo_values = [value if value is not None else 0.0 for value in grpo]
    plt.bar([i + width / 2 for i in x], grpo_values, width=width, label="GRPO policy")
    for i, value in enumerate(grpo):
        if value is None:
            plt.text(i + width / 2, 0.025, "pending", ha="center", rotation=90, fontsize=8)
    plt.ylim(0, 1)
    plt.ylabel("Verifier reward")
    plt.title("SFT Baseline vs GRPO Policy Reward")
    plt.xticks(x, labels)
    plt.legend()
    plt.tight_layout()
    plt.savefig(path, dpi=180)
    plt.close()


def plot_sft_loss(summary: dict[str, Any], path: Path) -> None:
    labels: list[str] = []
    values: list[float] = []
    for model in summary.get("models", []):
        labels.append(str(model.get("label") or model.get("run_id")))
        values.append(float(model.get("metrics", {}).get("sft_train_loss") or 0.0))
    if not labels:
        return
    path.parent.mkdir(parents=True, exist_ok=True)
    plt.figure(figsize=(9.5, 5))
    plt.bar(labels, values, color=["#315f72", "#8a5a44", "#2f6f4e"][: len(labels)])
    plt.ylabel("Final SFT train loss")
    plt.title("SFT Training Loss By Qwen Size")
    plt.tight_layout()
    plt.savefig(path, dpi=180)
    plt.close()


def plot_grpo_curve(history_path: Path, output: Path) -> None:
    rows = load_json(history_path, [])
    points = [
        (int(row.get("step") or idx + 1), float(row.get("reward")))
        for idx, row in enumerate(rows)
        if isinstance(row, dict) and row.get("reward") is not None
    ]
    if not points:
        return
    output.parent.mkdir(parents=True, exist_ok=True)
    steps, rewards = zip(*points)
    window = 50
    smooth = []
    for idx in range(len(rewards)):
        start = max(0, idx - window + 1)
        smooth.append(sum(rewards[start : idx + 1]) / (idx - start + 1))
    plt.figure(figsize=(10, 5))
    plt.plot(steps, rewards, alpha=0.18, label="step reward")
    plt.plot(steps, smooth, linewidth=2.0, label="rolling mean (50)")
    plt.ylim(0, 1)
    plt.xlabel("GRPO step")
    plt.ylabel("Verifier reward")
    plt.title("Qwen 3B GRPO Reward Curve")
    plt.legend()
    plt.tight_layout()
    plt.savefig(output, dpi=180)
    plt.close()


def artifact_availability() -> dict[str, Any]:
    availability: dict[str, Any] = {}
    for run_id, meta in RUNS.items():
        checkpoint_dir = SWEEP_CHECKPOINT_DIR / run_id
        report_dir = SWEEP_REPORT_DIR / run_id
        sft_adapter = checkpoint_dir / "sft_adapter"
        grpo_adapter = checkpoint_dir / "grpo_adapter"
        availability[run_id] = {
            "label": meta["label"],
            "model_id": meta["model_id"],
            "checkpoint_tree": summarize_artifact_dir(checkpoint_dir),
            "sft_adapter": summarize_artifact_dir(sft_adapter),
            "grpo_adapter": summarize_artifact_dir(grpo_adapter),
            "reports": summarize_artifact_dir(report_dir),
            "sft_report": (report_dir / "sft_trl_run.json").exists(),
            "grpo_report": (report_dir / "grpo_trl_run.json").exists(),
            "postsave_sft": (report_dir / "postsave_inference_sft.json").exists(),
            "postsave_grpo": (report_dir / "postsave_inference_grpo.json").exists(),
            "policy_ablation": (report_dir / "grpo_ablation_report.json").exists(),
        }
        missing: list[str] = []
        if not sft_adapter.exists():
            missing.append("sft_adapter")
        if not grpo_adapter.exists():
            missing.append("grpo_adapter")
        availability[run_id]["missing_trained_files"] = missing
        availability[run_id]["status"] = "complete" if not missing else "reports_only_or_partial"
    return availability


def build_docs(docs_dir: Path, manifest: dict[str, Any]) -> None:
    if docs_dir.exists():
        shutil.rmtree(docs_dir)
    (docs_dir / "charts" / "frontpage").mkdir(parents=True, exist_ok=True)
    (docs_dir / "charts" / "all").mkdir(parents=True, exist_ok=True)
    (docs_dir / "reports").mkdir(parents=True, exist_ok=True)

    summary = load_json(EVIDENCE_DIR / "submission_summary.json", {})
    plot_model_reward(summary, docs_dir / "charts" / "frontpage" / "00_sft_vs_grpo_reward_by_model.png")
    plot_sft_loss(summary, docs_dir / "charts" / "frontpage" / "08_sft_loss_by_model.png")
    plot_grpo_curve(
        SWEEP_REPORT_DIR / "qwen-qwen2-5-3b-instruct" / "grpo_history.json",
        docs_dir / "charts" / "frontpage" / "09_qwen_3b_grpo_reward_curve.png",
    )

    copied: list[str] = []
    for name, source in FRONTPAGE_CHARTS.items():
        if copy_file(source, docs_dir / "charts" / "frontpage" / name):
            copied.append(name)

    for source_dir in [
        EVIDENCE_DIR / "charts" / "generated",
        EVIDENCE_DIR / "charts" / "local_available_combined",
    ]:
        if source_dir.exists():
            for item in sorted(source_dir.glob("*.png")):
                copy_file(item, docs_dir / "charts" / "all" / item.name)

    report_sources = [
        EVIDENCE_DIR / "submission_summary.json",
        EVIDENCE_DIR / "reports" / "basic_llm_vs_polyguard_report.json",
        EVIDENCE_DIR / "reports" / "policy_ablation_report.json",
        EVIDENCE_DIR / "reports" / "basic_llm_failure_cases.md",
        EVIDENCE_DIR / "reports" / "action_traces.jsonl",
        SWEEP_REPORT_DIR / "qwen-qwen2-5-3b-instruct" / "grpo_trl_run.json",
        SWEEP_REPORT_DIR / "qwen-qwen2-5-3b-instruct" / "postsave_inference_grpo.json",
        SWEEP_REPORT_DIR / "qwen-qwen2-5-3b-instruct" / "grpo_ablation_report.json",
    ]
    for source in report_sources:
        copy_file(source, docs_dir / "reports" / source.name)

    write_json(docs_dir / "manifest.json", manifest)
    write_text(docs_dir / "README.md", final_docs_readme(manifest))


def final_docs_readme(manifest: dict[str, Any]) -> str:
    availability = manifest["artifact_availability"]
    rows = []
    for run_id, data in availability.items():
        rows.append(
            "| {label} | {sft} | {grpo} | {checkpoints} | {reports} | {status} |".format(
                label=data["label"],
                sft="yes" if data["sft_adapter"]["exists"] else "missing",
                grpo="yes" if data["grpo_adapter"]["exists"] else "missing",
                checkpoints="yes" if data["checkpoint_tree"]["exists"] else "missing",
                reports="yes" if data["reports"]["exists"] else "missing",
                status=data["status"],
            )
        )
    return """# PolyGuard Final Submission Evidence

This folder is the current curated evidence set for the final submission. It
replaces the earlier Qwen 0.5B/1.5B-only view with a single location for the
best charts, reports, action traces, and model-artifact availability.

## Hugging Face Artifact Space

- Space: [{space_id}](https://huggingface.co/spaces/{space_id})
- Download command:

```bash
HF_TOKEN=<token> ./.venv/bin/hf download {space_id} --repo-type space --local-dir ./hf_final_artifacts
```

## Artifact Availability

| Model | SFT adapter | GRPO adapter | Checkpoints | Reports | Status |
| --- | --- | --- | --- | --- | --- |
{rows}

Qwen 0.5B and 1.5B currently have SFT histories/reports and post-save SFT
evidence in this repository, but no downloadable SFT/GRPO adapter directories
were present in the local checkout or authenticated artifact repos at packaging
time. Qwen 3B has both SFT and GRPO adapters, checkpoint metadata/intermediate
checkpoints, GRPO history, post-save GRPO inference, and policy ablation
evidence.

## Frontpage Charts

- `charts/frontpage/00_sft_vs_grpo_reward_by_model.png`
- `charts/frontpage/01_basic_llm_vs_full_pipeline_reward.png`
- `charts/frontpage/02_reward_delta_by_seed.png`
- `charts/frontpage/03_policy_ablation_reward.png`
- `charts/frontpage/04_reward_components.png`
- `charts/frontpage/05_train_holdout_gap.png`
- `charts/frontpage/06_inference_latency_validity.png`
- `charts/frontpage/07_sft_vs_grpo_reward.png`
- `charts/frontpage/08_sft_loss_by_model.png`
- `charts/frontpage/09_qwen_3b_grpo_reward_curve.png`

## Improvement Evidence

- Basic LLM proxy vs full PolyGuard pipeline reward delta:
  `{delta}` average reward.
- Full pipeline legality rate: `{pipeline_legality}`.
- Basic LLM failure/exploit rate: `{basic_failure_rate}`.
- Full pipeline failure/exploit rate: `{pipeline_failure_rate}`.

Reward values in the tracked API/reports remain numeric and clamped to
`[0.001, 0.999]` at three decimal precision.
""".format(
        space_id=manifest["space_id"],
        rows="\n".join(rows),
        delta=manifest.get("basic_vs_pipeline", {}).get("reward_delta"),
        pipeline_legality=manifest.get("basic_vs_pipeline", {}).get("pipeline_legality"),
        basic_failure_rate=manifest.get("basic_vs_pipeline", {}).get("basic_failure_rate"),
        pipeline_failure_rate=manifest.get("basic_vs_pipeline", {}).get("pipeline_failure_rate"),
    )


def build_space(space_dir: Path, manifest: dict[str, Any]) -> None:
    if space_dir.exists():
        shutil.rmtree(space_dir)
    space_dir.mkdir(parents=True)
    write_text(
        space_dir / "README.md",
        """---
title: PolyGuard Final Artifacts
sdk: static
pinned: false
---

# PolyGuard Final Artifacts

This Space stores the final PolyGuard evidence bundle and the available trained
adapter artifacts. It is separate from the training Spaces and does not run
training.

Open `index.html` or inspect the `artifacts/`, `reports/`, and `evidence/`
folders in the Space file browser.
""",
    )
    write_text(
        space_dir / ".gitattributes",
        """*.safetensors filter=lfs diff=lfs merge=lfs -text
*.bin filter=lfs diff=lfs merge=lfs -text
*.pt filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
""",
    )
    write_json(space_dir / "manifest.json", manifest)

    evidence_target = space_dir / "evidence" / "final_submission_evidence"
    copy_tree(Path(manifest["docs_dir"]), evidence_target)

    for run_id in RUNS:
        checkpoint_dir = SWEEP_CHECKPOINT_DIR / run_id
        report_dir = SWEEP_REPORT_DIR / run_id
        if checkpoint_dir.exists():
            copy_tree(checkpoint_dir, space_dir / "checkpoints" / run_id)
        for stage in ["sft_adapter", "grpo_adapter"]:
            source = checkpoint_dir / stage
            if source.exists():
                copy_tree(source, space_dir / "artifacts" / run_id / stage)
        if report_dir.exists():
            copy_tree(report_dir, space_dir / "reports" / run_id)

    write_text(space_dir / "index.html", index_html(manifest))


def index_html(manifest: dict[str, Any]) -> str:
    rows = []
    for run_id, data in manifest["artifact_availability"].items():
        rows.append(
            "<tr><td>{label}</td><td>{sft}</td><td>{grpo}</td><td>{checkpoints}</td><td>{reports}</td><td>{status}</td></tr>".format(
                label=html.escape(data["label"]),
                sft="available" if data["sft_adapter"]["exists"] else "missing",
                grpo="available" if data["grpo_adapter"]["exists"] else "missing",
                checkpoints="available" if data["checkpoint_tree"]["exists"] else "missing",
                reports="available" if data["reports"]["exists"] else "missing",
                status=html.escape(data["status"]),
            )
        )
    return """<!doctype html>
<html lang="en">
<head>
  <meta charset="utf-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1" />
  <title>PolyGuard Final Artifacts</title>
  <style>
    body {{ font-family: Inter, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; margin: 40px; line-height: 1.5; color: #17212b; }}
    table {{ border-collapse: collapse; width: 100%; margin: 20px 0; }}
    th, td {{ border-bottom: 1px solid #d8dee4; padding: 10px; text-align: left; }}
    code {{ background: #f4f6f8; padding: 2px 5px; border-radius: 4px; }}
    .grid {{ display: grid; grid-template-columns: repeat(auto-fit, minmax(260px, 1fr)); gap: 16px; }}
    .panel {{ border: 1px solid #d8dee4; padding: 16px; border-radius: 6px; }}
  </style>
</head>
<body>
  <h1>PolyGuard Final Artifacts</h1>
  <p>This Space stores the final evidence bundle and available trained adapters. It does not retrain models.</p>
  <table>
    <thead><tr><th>Model</th><th>SFT adapter</th><th>GRPO adapter</th><th>Checkpoints</th><th>Reports</th><th>Status</th></tr></thead>
    <tbody>{rows}</tbody>
  </table>
  <div class="grid">
    <div class="panel"><strong>Evidence</strong><br /><code>evidence/final_submission_evidence/</code></div>
    <div class="panel"><strong>Adapters</strong><br /><code>artifacts/qwen-qwen2-5-3b-instruct/</code></div>
    <div class="panel"><strong>Checkpoints</strong><br /><code>checkpoints/qwen-qwen2-5-3b-instruct/</code></div>
    <div class="panel"><strong>Reports</strong><br /><code>reports/</code></div>
    <div class="panel"><strong>Manifest</strong><br /><code>manifest.json</code></div>
  </div>
</body>
</html>
""".format(rows="\n".join(rows))


def deploy_space(space_id: str, space_dir: Path, public: bool) -> None:
    token = os.getenv("HF_TOKEN")
    if not token:
        raise SystemExit("HF_TOKEN is required for --deploy")
    api = HfApi(token=token)
    api.create_repo(
        repo_id=space_id,
        repo_type="space",
        space_sdk="static",
        private=not public,
        exist_ok=True,
    )
    ignore_patterns = [".DS_Store", "**/.DS_Store", "__pycache__/*", "*.pyc", ".cache/*", ".cache/**"]
    if dir_size(space_dir) > 100 * 1024 * 1024:
        api.upload_folder(
            repo_id=space_id,
            repo_type="space",
            folder_path=str(space_dir),
            commit_message="Upload PolyGuard final evidence and adapters",
            ignore_patterns=ignore_patterns + ["checkpoints/*", "checkpoints/**"],
        )
        checkpoint_root = space_dir / "checkpoints"
        for run_dir in sorted(path for path in checkpoint_root.glob("*") if path.is_dir()):
            for file_path in sorted(path for path in run_dir.iterdir() if path.is_file()):
                api.upload_file(
                    repo_id=space_id,
                    repo_type="space",
                    path_or_fileobj=str(file_path),
                    path_in_repo=f"checkpoints/{run_dir.name}/{file_path.name}",
                    commit_message=f"Upload {run_dir.name} checkpoint metadata",
                )
            for subdir in sorted(path for path in run_dir.iterdir() if path.is_dir()):
                nested_dirs = sorted(path for path in subdir.iterdir() if path.is_dir())
                if nested_dirs:
                    for file_path in sorted(path for path in subdir.iterdir() if path.is_file()):
                        api.upload_file(
                            repo_id=space_id,
                            repo_type="space",
                            path_or_fileobj=str(file_path),
                            path_in_repo=f"checkpoints/{run_dir.name}/{subdir.name}/{file_path.name}",
                            commit_message=f"Upload {run_dir.name} {subdir.name} metadata",
                        )
                    for nested in nested_dirs:
                        api.upload_folder(
                            repo_id=space_id,
                            repo_type="space",
                            folder_path=str(nested),
                            path_in_repo=f"checkpoints/{run_dir.name}/{subdir.name}/{nested.name}",
                            commit_message=f"Upload {run_dir.name} {subdir.name}/{nested.name}",
                            ignore_patterns=ignore_patterns,
                        )
                else:
                    api.upload_folder(
                        repo_id=space_id,
                        repo_type="space",
                        folder_path=str(subdir),
                        path_in_repo=f"checkpoints/{run_dir.name}/{subdir.name}",
                        commit_message=f"Upload {run_dir.name} {subdir.name}",
                        ignore_patterns=ignore_patterns,
                    )
    else:
        api.upload_folder(
            repo_id=space_id,
            repo_type="space",
            folder_path=str(space_dir),
            commit_message="Upload PolyGuard final evidence and trained adapters",
            ignore_patterns=ignore_patterns,
        )


def main() -> None:
    args = parse_args()
    docs_dir = Path(args.docs_dir)
    space_dir = Path(args.space_dir)

    summary = load_json(EVIDENCE_DIR / "submission_summary.json", {})
    basic = load_json(EVIDENCE_DIR / "reports" / "basic_llm_vs_polyguard_report.json", {})
    basic_summary = basic.get("summaries", {})
    manifest = {
        "status": "ok",
        "space_id": args.space_id,
        "space_url": f"https://huggingface.co/spaces/{args.space_id}",
        "docs_dir": str(docs_dir.relative_to(ROOT) if docs_dir.is_relative_to(ROOT) else docs_dir),
        "evidence_source": str(EVIDENCE_DIR.relative_to(ROOT)),
        "artifact_availability": artifact_availability(),
        "submission_models": summary.get("models", []),
        "basic_vs_pipeline": {
            "reward_delta": basic.get("pipeline_minus_basic_reward_delta"),
            "basic_reward": basic_summary.get("basic_llm", {}).get("avg_reward"),
            "pipeline_reward": basic_summary.get("full_polyguard_pipeline", {}).get("avg_reward"),
            "basic_failure_rate": basic_summary.get("basic_llm", {}).get("exploit_or_failure_rate"),
            "pipeline_failure_rate": basic_summary.get("full_polyguard_pipeline", {}).get("exploit_or_failure_rate"),
            "pipeline_legality": basic_summary.get("full_polyguard_pipeline", {}).get("legality_rate"),
        },
        "download_command": (
            f"HF_TOKEN=<token> ./.venv/bin/hf download {args.space_id} "
            "--repo-type space --local-dir ./hf_final_artifacts"
        ),
        "notes": [
            "Packaging-only run; no retraining is performed.",
            "Qwen 3B has SFT and GRPO adapter directories plus checkpoint metadata/intermediate checkpoints in this artifact Space.",
            "Qwen 0.5B and 1.5B adapter directories were not present locally or in the checked artifact repos; reports remain included.",
        ],
    }

    if not args.skip_docs:
        build_docs(docs_dir, manifest)
        manifest = load_json(docs_dir / "manifest.json", manifest)
    build_space(space_dir, manifest)

    if args.deploy:
        deploy_space(args.space_id, space_dir, public=args.public)

    print(json.dumps({"status": "ok", "space_url": manifest["space_url"], "space_dir": str(space_dir), "docs_dir": str(docs_dir)}, indent=2))


if __name__ == "__main__":
    main()