Add Hugging Face Hub integration for safetensor files

- Add `tsr hf search` to search HF models with safetensor files
- Add `tsr hf get` to view model info and list safetensor files
- Add `tsr hf files` to list safetensor files in a model
- Add `tsr hf dl` to download safetensor files from HF

Uses official huggingface_hub library for API access.
Only safetensor files are supported (enforced at search and download).

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

README.md

@@ -92,6 +92,30 @@ tsr dl -H ABC123...
 tsr dl -m 12345 -o ./models
 ```
 
+### Hugging Face Integration
+
+Search and download safetensor files from Hugging Face Hub.
+
+```bash
+# Search for models with safetensor files
+tsr hf search "flux"
+
+# Filter by author or pipeline
+tsr hf search -a stabilityai -p text-to-image
+
+# Get model info and list safetensor files
+tsr hf get black-forest-labs/FLUX.1-schnell
+
+# List safetensor files only
+tsr hf files black-forest-labs/FLUX.1-schnell
+
+# Download a specific safetensor file
+tsr hf dl black-forest-labs/FLUX.1-schnell -f ae.safetensors
+
+# Download all safetensor files from a model
+tsr hf dl author/model --all -o ./models
+```
+
 ### Inspect Local Files
 
 ```bash
@@ -293,6 +317,18 @@ Data is stored in XDG-compliant paths:
 | `--commercial` | none, image, rent, sell |
 | `--page` | Page number for pagination |
 
+## Hugging Face Options
+
+| Option | Description |
+|--------|-------------|
+| `-a, --author` | Filter by author/organization |
+| `-p, --pipeline` | Pipeline tag (text-to-image, text-generation, etc.) |
+| `-s, --sort` | Sort by (downloads, likes, created_at, trending_score) |
+| `-n, --limit` | Number of results (default: 25) |
+| `-f, --file` | Specific file to download |
+| `--all` | Download all safetensor files |
+| `-o, --output` | Output directory |
+
 ## Generate Options
 
 | Option | Description |

pyproject.toml

@@ -10,6 +10,7 @@ dependencies = [
     "rich>=13.0.0",
     "typer>=0.15.0",
     "websocket-client>=1.9.0",
+    "huggingface_hub>=0.25.0",
 ]
 
 [project.optional-dependencies]
@@ -98,6 +99,10 @@ ignore_missing_imports = true
 module = ["scalar_fastapi.*"]
 ignore_missing_imports = true
 
+[[tool.mypy.overrides]]
+module = ["huggingface_hub.*"]
+ignore_missing_imports = true
+
 [tool.pytest.ini_options]
 testpaths = ["tests"]
 addopts = "-v --cov=tensors --cov-report=term-missing"

tensors/cli.py

@@ -37,10 +37,19 @@ from tensors.display import (
     _format_size,
     display_civitai_data,
     display_file_info,
+    display_hf_model_info,
+    display_hf_search_results,
     display_local_metadata,
     display_model_info,
     display_search_results,
 )
+from tensors.hf import (
+    download_all_safetensors,
+    download_hf_safetensor,
+    get_hf_model,
+    list_safetensor_files,
+    search_hf_models,
+)
 from tensors.safetensor import compute_sha256, get_base_name, read_safetensor_metadata
 
 # Key masking threshold
@@ -720,6 +729,124 @@ def db_stats(
     console.print(table)
 
 
+# =============================================================================
+# Hugging Face Commands
+# =============================================================================
+
+hf_app = typer.Typer(name="hf", help="Hugging Face Hub commands for safetensor files.")
+app.add_typer(hf_app)
+
+
+@hf_app.command("search")
+def hf_search(
+    query: Annotated[str | None, typer.Argument(help="Search query")] = None,
+    author: Annotated[str | None, typer.Option("-a", "--author", help="Filter by author/org")] = None,
+    pipeline: Annotated[str | None, typer.Option("-p", "--pipeline", help="Pipeline tag (text-to-image, etc.)")] = None,
+    sort: Annotated[str | None, typer.Option("-s", "--sort", help="Sort by (downloads, likes, created_at)")] = None,
+    limit: Annotated[int, typer.Option("-n", "--limit", help="Max results")] = 25,
+    json_output: Annotated[bool, typer.Option("--json", "-j", help="Output as JSON")] = False,
+) -> None:
+    """Search Hugging Face for models with safetensor files."""
+    results = search_hf_models(
+        query=query,
+        author=author,
+        pipeline_tag=pipeline,
+        sort=sort,
+        limit=limit,
+        console=console,
+    )
+
+    if json_output:
+        console.print_json(data=results)
+        return
+
+    display_hf_search_results(results, console)
+
+
+@hf_app.command("get")
+def hf_get(
+    model_id: Annotated[str, typer.Argument(help="Model ID (e.g., stabilityai/stable-diffusion-xl-base-1.0)")],
+    json_output: Annotated[bool, typer.Option("--json", "-j", help="Output as JSON")] = False,
+) -> None:
+    """Get Hugging Face model info and list safetensor files."""
+    model = get_hf_model(model_id, console=console)
+
+    if not model:
+        raise typer.Exit(1)
+
+    if json_output:
+        console.print_json(data=model)
+        return
+
+    display_hf_model_info(model, console)
+
+
+@hf_app.command("files")
+def hf_files(
+    model_id: Annotated[str, typer.Argument(help="Model ID")],
+    json_output: Annotated[bool, typer.Option("--json", "-j", help="Output as JSON")] = False,
+) -> None:
+    """List safetensor files in a Hugging Face model."""
+    files = list_safetensor_files(model_id, console=console)
+
+    if json_output:
+        console.print_json(data=files)
+        return
+
+    if not files:
+        console.print("[yellow]No safetensor files found.[/yellow]")
+        return
+
+    console.print(f"[bold]Safetensor files in {model_id}:[/bold]")
+    for i, f in enumerate(files, 1):
+        console.print(f"  {i}. {f}")
+
+
+@hf_app.command("dl")
+def hf_download(
+    model_id: Annotated[str, typer.Argument(help="Model ID (e.g., stabilityai/stable-diffusion-xl-base-1.0)")],
+    filename: Annotated[str | None, typer.Option("-f", "--file", help="Specific file to download")] = None,
+    output: Annotated[Path | None, typer.Option("-o", "--output", help="Output directory")] = None,
+    all_files: Annotated[bool, typer.Option("--all", "-a", help="Download all safetensor files")] = False,
+) -> None:
+    """Download safetensor files from Hugging Face.
+
+    Examples:
+        tsr hf dl stabilityai/stable-diffusion-xl-base-1.0 -f sd_xl_base_1.0.safetensors
+        tsr hf dl author/model --all
+    """
+    output_dir = output or Path.cwd()
+
+    if all_files:
+        downloaded = download_all_safetensors(model_id, output_dir, console=console)
+        if downloaded:
+            console.print(f"[green]Downloaded {len(downloaded)} files[/green]")
+        else:
+            console.print("[red]No files downloaded[/red]")
+            raise typer.Exit(1)
+        return
+
+    if not filename:
+        # List files and prompt or show help
+        files = list_safetensor_files(model_id, console=console)
+        if not files:
+            console.print("[red]No safetensor files found in model[/red]")
+            raise typer.Exit(1)
+
+        if len(files) == 1:
+            filename = files[0]
+            console.print(f"[dim]Downloading only safetensor file: {filename}[/dim]")
+        else:
+            console.print("[yellow]Multiple safetensor files found. Specify one with -f or use --all:[/yellow]")
+            for i, f in enumerate(files, 1):
+                console.print(f"  {i}. {f}")
+            raise typer.Exit(1)
+
+    result = download_hf_safetensor(model_id, filename, output_dir, console=console)
+    if not result:
+        raise typer.Exit(1)
+
+
 def main() -> int:
     """Main entry point."""
     # Handle legacy invocation: tsr <file.safetensors> -> tsr info <file>
@@ -732,6 +859,7 @@ def main() -> int:
         "config",
         "serve",
         "db",
+        "hf",
     )
     if len(sys.argv) > 1 and not sys.argv[1].startswith("-"):
         arg = sys.argv[1]

tensors/display.py

@@ -329,3 +329,135 @@ def display_search_results(results: dict[str, Any], console: Console) -> None:
     total = metadata.get("totalItems", len(items))
     console.print(f"\n[dim]Showing {len(items)} of {total:,} results[/dim]")
     console.print("[dim]Use 'tsr get <id>' to view details or 'tsr dl -m <id>' to download[/dim]")
+
+
+# =============================================================================
+# Hugging Face Display Functions
+# =============================================================================
+
+
+def _format_bytes(size_bytes: int) -> str:
+    """Format size in bytes to human-readable string."""
+    if size_bytes < KB:
+        return f"{size_bytes} B"
+    if size_bytes < KB * KB:
+        return f"{size_bytes / KB:.1f} KB"
+    if size_bytes < KB * KB * KB:
+        return f"{size_bytes / KB / KB:.1f} MB"
+    return f"{size_bytes / KB / KB / KB:.2f} GB"
+
+
+def _build_hf_search_table(console: Console) -> Table:
+    """Build Hugging Face search results table."""
+    id_width = 40
+    dls_width = 8
+    likes_width = 6
+    files_width = 5
+
+    terminal_width = console.size.width
+    fixed_width = id_width + dls_width + likes_width + files_width
+    overhead = 17
+    author_width = max(15, (terminal_width - fixed_width - overhead) // 2)
+
+    table = Table(show_header=True, header_style="bold magenta")
+    table.add_column("Model ID", style="cyan", width=id_width, no_wrap=True, overflow="ellipsis")
+    table.add_column("Author", style="yellow", width=author_width, no_wrap=True, overflow="ellipsis")
+    table.add_column("DLs", justify="right", width=dls_width, no_wrap=True)
+    table.add_column("Likes", justify="right", width=likes_width, no_wrap=True)
+    table.add_column("Files", justify="right", width=files_width, no_wrap=True)
+
+    return table
+
+
+def display_hf_search_results(models: list[dict[str, Any]], console: Console) -> None:
+    """Display Hugging Face search results in a table."""
+    if not models:
+        console.print("[yellow]No results found.[/yellow]")
+        return
+
+    table = _build_hf_search_table(console)
+
+    for model in models:
+        model_id = model.get("id", "N/A")
+        author = model.get("author", model_id.split("/")[0] if "/" in model_id else "N/A")
+        downloads = _format_count(model.get("downloads", 0))
+        likes = _format_count(model.get("likes", 0))
+        safetensor_files = model.get("_safetensor_files", [])
+        files_count = str(len(safetensor_files))
+
+        table.add_row(model_id, author, downloads, likes, files_count)
+
+    console.print()
+    console.print(table)
+    console.print(f"\n[dim]Showing {len(models)} models with safetensor files[/dim]")
+    console.print("[dim]Use 'tsr hf get <model_id>' to view details or 'tsr hf dl <model_id>' to download[/dim]")
+
+
+def _build_hf_model_table(console: Console) -> Table:
+    """Build Hugging Face model info table."""
+    prop_width = 12
+    terminal_width = console.size.width
+    overhead = 7
+    value_width = max(40, terminal_width - prop_width - overhead)
+
+    table = Table(title="Hugging Face Model", show_header=True, header_style="bold magenta")
+    table.add_column("Property", style="cyan", width=prop_width, no_wrap=True)
+    table.add_column("Value", style="green", width=value_width, no_wrap=True, overflow="ellipsis")
+
+    return table
+
+
+def display_hf_model_info(model: dict[str, Any], console: Console) -> None:
+    """Display Hugging Face model information."""
+    if not model:
+        console.print("[yellow]Model not found.[/yellow]")
+        return
+
+    table = _build_hf_model_table(console)
+
+    model_id = model.get("id", "N/A")
+    table.add_row("Model ID", model_id)
+    table.add_row("Author", model.get("author", "N/A"))
+    table.add_row("Downloads", f"{model.get('downloads', 0):,}")
+    table.add_row("Likes", f"{model.get('likes', 0):,}")
+
+    # Handle datetime or string values
+    created = model.get("created_at") or model.get("createdAt")
+    if created:
+        created_str = created.strftime("%Y-%m-%d") if hasattr(created, "strftime") else str(created)[:10]
+        table.add_row("Created", created_str)
+
+    updated = model.get("last_modified") or model.get("lastModified")
+    if updated:
+        updated_str = updated.strftime("%Y-%m-%d") if hasattr(updated, "strftime") else str(updated)[:10]
+        table.add_row("Updated", updated_str)
+
+    tags = model.get("tags", [])
+    if tags:
+        table.add_row("Tags", ", ".join(tags[:MAX_TAGS_DISPLAY]) + ("..." if len(tags) > MAX_TAGS_DISPLAY else ""))
+
+    pipeline = model.get("pipeline_tag")
+    if pipeline:
+        table.add_row("Pipeline", pipeline)
+
+    console.print()
+    console.print(table)
+
+    # Display safetensor files
+    safetensor_files = model.get("_safetensor_files", [])
+    if safetensor_files:
+        files_table = Table(title="Safetensor Files", show_header=True, header_style="bold magenta")
+        files_table.add_column("#", style="dim", width=3, justify="right")
+        files_table.add_column("Filename", style="cyan", no_wrap=True, overflow="ellipsis")
+        files_table.add_column("Size", style="green", justify="right", width=10)
+
+        for i, f in enumerate(safetensor_files, 1):
+            filename = f.get("rfilename", "N/A")
+            size = _format_bytes(f.get("size", 0)) if f.get("size") else "N/A"
+            files_table.add_row(str(i), filename, size)
+
+        console.print()
+        console.print(files_table)
+
+    console.print()
+    console.print(f"[bold blue]View on HuggingFace:[/bold blue] https://huggingface.co/{model_id}")

tensors/hf.py

@@ -0,0 +1,246 @@
+"""Hugging Face Hub integration for safetensor files."""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import TYPE_CHECKING, Any
+
+from huggingface_hub import HfApi, hf_hub_download, list_repo_files
+from huggingface_hub.errors import RepositoryNotFoundError
+
+if TYPE_CHECKING:
+    from rich.console import Console
+
+# Shared API instance
+_api: HfApi | None = None
+
+
+def _get_api(token: str | None = None) -> HfApi:
+    """Get or create HfApi instance."""
+    global _api  # noqa: PLW0603
+    if _api is None:
+        _api = HfApi(token=token)
+    return _api
+
+
+def search_hf_models(
+    query: str | None = None,
+    *,
+    author: str | None = None,
+    tags: list[str] | None = None,
+    pipeline_tag: str | None = None,
+    sort: str | None = None,
+    limit: int = 25,
+    token: str | None = None,
+    console: Console | None = None,
+) -> list[dict[str, Any]]:
+    """Search Hugging Face models with safetensor files.
+
+    Args:
+        query: Search query string
+        author: Filter by author/organization
+        tags: Additional tags to filter by
+        pipeline_tag: Pipeline type (text-generation, text-to-image, etc.)
+        sort: Sort field (downloads, likes, created_at, trending_score)
+        limit: Maximum results
+        token: HuggingFace API token
+        console: Rich console for output
+
+    Returns:
+        List of model info dictionaries with safetensor files
+    """
+    api = _get_api(token)
+
+    # Build filter list - always include safetensors
+    filters = ["safetensors"]
+    if tags:
+        filters.extend(tags)
+
+    try:
+        models = api.list_models(
+            search=query,
+            author=author,
+            filter=filters,
+            pipeline_tag=pipeline_tag,
+            sort=sort or "downloads",
+            limit=limit,
+            expand=["siblings", "downloads", "likes", "author", "lastModified", "createdAt", "tags"],
+        )
+
+        results = []
+        for model in models:
+            model_dict = model.__dict__.copy()
+
+            # Get safetensor files from siblings
+            siblings = getattr(model, "siblings", None) or []
+            safetensor_files = [
+                {"rfilename": s.rfilename, "size": getattr(s, "size", None)}
+                for s in siblings
+                if s.rfilename.endswith(".safetensors")
+            ]
+
+            if safetensor_files:
+                model_dict["_safetensor_files"] = safetensor_files
+                results.append(model_dict)
+
+        return results
+
+    except Exception as e:
+        if console:
+            console.print(f"[red]Error searching models: {e}[/red]")
+        return []
+
+
+def get_hf_model(
+    model_id: str,
+    token: str | None = None,
+    console: Console | None = None,
+) -> dict[str, Any] | None:
+    """Get detailed model information from Hugging Face.
+
+    Args:
+        model_id: Model ID (e.g., "stabilityai/stable-diffusion-xl-base-1.0")
+        token: HuggingFace API token
+        console: Rich console for output
+
+    Returns:
+        Model info dictionary or None if not found
+    """
+    api = _get_api(token)
+
+    try:
+        model = api.model_info(model_id, files_metadata=True)
+        model_dict = model.__dict__.copy()
+
+        # Get safetensor files
+        siblings = getattr(model, "siblings", None) or []
+        safetensor_files = [
+            {"rfilename": s.rfilename, "size": getattr(s, "size", None)}
+            for s in siblings
+            if s.rfilename.endswith(".safetensors")
+        ]
+        model_dict["_safetensor_files"] = safetensor_files
+
+        return model_dict
+
+    except RepositoryNotFoundError:
+        if console:
+            console.print(f"[red]Model not found: {model_id}[/red]")
+        return None
+    except Exception as e:
+        if console:
+            console.print(f"[red]Error fetching model: {e}[/red]")
+        return None
+
+
+def list_safetensor_files(
+    model_id: str,
+    token: str | None = None,
+    console: Console | None = None,
+) -> list[str]:
+    """List all safetensor files in a Hugging Face model.
+
+    Args:
+        model_id: Model ID
+        token: HuggingFace API token
+        console: Rich console for output
+
+    Returns:
+        List of safetensor filenames
+    """
+    try:
+        files = list_repo_files(model_id, token=token)
+        return [f for f in files if f.endswith(".safetensors")]
+    except RepositoryNotFoundError:
+        if console:
+            console.print(f"[red]Model not found: {model_id}[/red]")
+        return []
+    except Exception as e:
+        if console:
+            console.print(f"[red]Error listing files: {e}[/red]")
+        return []
+
+
+def download_hf_safetensor(
+    model_id: str,
+    filename: str,
+    output_dir: Path,
+    token: str | None = None,
+    console: Console | None = None,
+    *,
+    resume: bool = True,
+) -> Path | None:
+    """Download a safetensor file from Hugging Face.
+
+    Args:
+        model_id: Model ID (e.g., "stabilityai/stable-diffusion-xl-base-1.0")
+        filename: File name within the model repo
+        output_dir: Directory to save the file
+        token: HuggingFace API token
+        console: Rich console for progress output
+        resume: Whether to resume partial downloads
+
+    Returns:
+        Path to downloaded file, or None on failure
+    """
+    if not filename.endswith(".safetensors"):
+        if console:
+            console.print("[red]Only .safetensors files are supported[/red]")
+        return None
+
+    try:
+        # hf_hub_download handles caching and resume automatically
+        downloaded_path = hf_hub_download(
+            repo_id=model_id,
+            filename=filename,
+            local_dir=output_dir,
+            token=token,
+            force_download=not resume,
+        )
+
+        if console:
+            console.print(f"[green]Downloaded: {downloaded_path}[/green]")
+
+        return Path(downloaded_path)
+
+    except RepositoryNotFoundError:
+        if console:
+            console.print(f"[red]Model not found: {model_id}[/red]")
+        return None
+    except Exception as e:
+        if console:
+            console.print(f"[red]Download failed: {e}[/red]")
+        return None
+
+
+def download_all_safetensors(
+    model_id: str,
+    output_dir: Path,
+    token: str | None = None,
+    console: Console | None = None,
+) -> list[Path]:
+    """Download all safetensor files from a model.
+
+    Args:
+        model_id: Model ID
+        output_dir: Directory to save files
+        token: HuggingFace API token
+        console: Rich console for output
+
+    Returns:
+        List of downloaded file paths
+    """
+    files = list_safetensor_files(model_id, token, console)
+    if not files:
+        return []
+
+    downloaded = []
+    for filename in files:
+        if console:
+            console.print(f"[dim]Downloading {filename}...[/dim]")
+
+        path = download_hf_safetensor(model_id, filename, output_dir, token, console)
+        if path:
+            downloaded.append(path)
+
+    return downloaded

uv.lock

@@ -180,6 +180,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b5/36/7fb70f04bf00bc646cd5bb45aa9eddb15e19437a28b8fb2b4a5249fac770/filelock-3.20.3-py3-none-any.whl", hash = "sha256:4b0dda527ee31078689fc205ec4f1c1bf7d56cf88b6dc9426c4f230e46c2dce1", size = 16701, upload-time = "2026-01-09T17:55:04.334Z" },
 ]
 
+[[package]]
+name = "fsspec"
+version = "2026.2.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/51/7c/f60c259dcbf4f0c47cc4ddb8f7720d2dcdc8888c8e5ad84c73ea4531cc5b/fsspec-2026.2.0.tar.gz", hash = "sha256:6544e34b16869f5aacd5b90bdf1a71acb37792ea3ddf6125ee69a22a53fb8bff", size = 313441, upload-time = "2026-02-05T21:50:53.743Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e6/ab/fb21f4c939bb440104cc2b396d3be1d9b7a9fd3c6c2a53d98c45b3d7c954/fsspec-2026.2.0-py3-none-any.whl", hash = "sha256:98de475b5cb3bd66bedd5c4679e87b4fdfe1a3bf4d707b151b3c07e58c9a2437", size = 202505, upload-time = "2026-02-05T21:50:51.819Z" },
+]
+
 [[package]]
 name = "h11"
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