💬 Commit message: Update 2026-01-24 19:22:34, 7 files, 1285 lines

📁 Files changed: 7
📝 Lines changed: 1285

  • build.py
  • check.py
  • civit.md
  • main.py
  • pyproject.toml
  • sft_get.py
  • uv.lock

build.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+"""Build script for creating a standalone binary with Nuitka."""
+
+import subprocess
+import sys
+from pathlib import Path
+
+
+def main():
+    project_dir = Path(__file__).parent
+    main_file = project_dir / "sft_get.py"
+    output_dir = project_dir / "dist"
+
+    output_dir.mkdir(exist_ok=True)
+
+    cmd = [
+        sys.executable,
+        "-m",
+        "nuitka",
+        "--standalone",
+        "--onefile",
+        f"--output-dir={output_dir}",
+        "--output-filename=sft-get",
+        "--assume-yes-for-downloads",
+        "--remove-output",
+        # Include required packages
+        "--include-package=rich",
+        "--include-package=httpx",
+        "--include-package=safetensors",
+        str(main_file),
+    ]
+
+    print(f"Building with command:\n{' '.join(cmd)}\n")
+    subprocess.run(cmd, check=True)
+    print(f"\nBuild complete! Binary at: {output_dir / 'sft-get'}")
+
+
+if __name__ == "__main__":
+    main()

check.py

@@ -0,0 +1,51 @@
+#!/usr/bin/env python3
+"""Run all code quality checks."""
+
+import subprocess
+import sys
+
+
+def run(cmd: list[str], name: str) -> bool:
+    """Run a command and return success status."""
+    print(f"\n{'=' * 60}")
+    print(f"Running: {name}")
+    print(f"{'=' * 60}")
+    result = subprocess.run(cmd, check=False)
+    if result.returncode != 0:
+        print(f"FAILED: {name}")
+        return False
+    print(f"PASSED: {name}")
+    return True
+
+
+def main() -> int:
+    """Run all checks."""
+    fix_mode = "--fix" in sys.argv
+
+    checks = [
+        (["uv", "run", "ruff", "format", "." if fix_mode else "--check", "."], "Ruff Format"),
+        (
+            ["uv", "run", "ruff", "check", ".", *(["--fix"] if fix_mode else [])],
+            "Ruff Lint",
+        ),
+        (["uv", "run", "mypy", "sft_get.py"], "Mypy"),
+    ]
+
+    # Fix the format check command
+    if not fix_mode:
+        checks[0] = (["uv", "run", "ruff", "format", "--check", "."], "Ruff Format")
+
+    results = [run(cmd, name) for cmd, name in checks]
+
+    print(f"\n{'=' * 60}")
+    if all(results):
+        print("All checks passed!")
+        return 0
+    else:
+        failed = [name for (_, name), passed in zip(checks, results, strict=True) if not passed]
+        print(f"Failed checks: {', '.join(failed)}")
+        return 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

civit.md

@@ -0,0 +1,435 @@
+---
+source: https://developer.civitai.com/docs/api/public-rest
+additional_sources:
+  - https://github.com/civitai/civitai/wiki/REST-API-Reference
+  - https://education.civitai.com/civitais-guide-to-downloading-via-api/
+fetched: 2026-01-19
+---
+
+# CivitAI REST API Reference
+
+The Civitai REST API provides programmatic access to models, images, creators, and tags. The API is still in active development.
+
+## Base URL
+
+```
+https://civitai.com/api/v1
+```
+
+## Authorization
+
+Generate an API Key from [User Account Settings](https://civitai.com/user/account).
+
+### Authorization Header
+
+```http
+GET https://civitai.com/api/v1/models
+Content-Type: application/json
+Authorization: Bearer {api_key}
+```
+
+### Query String
+
+```http
+GET https://civitai.com/api/v1/models?token={api_key}
+```
+
+## Endpoints
+
+### GET /api/v1/creators
+
+List creators/users.
+
+**Query Parameters:**
+
+| Name | Type | Description |
+|------|------|-------------|
+| `limit` | number | Results per page (0-200, default 20). 0 returns all |
+| `page` | number | Page number |
+| `query` | string | Filter by username |
+
+**Response:**
+
+```json
+{
+  "items": [
+    {
+      "username": "Civitai",
+      "modelCount": 848,
+      "link": "https://civitai.com/api/v1/models?username=Civitai"
+    }
+  ],
+  "metadata": {
+    "totalItems": 46,
+    "currentPage": 1,
+    "pageSize": 20,
+    "totalPages": 3,
+    "nextPage": "https://civitai.com/api/v1/creators?page=2"
+  }
+}
+```
+
+---
+
+### GET /api/v1/images
+
+List images with generation metadata.
+
+**Query Parameters:**
+
+| Name | Type | Description |
+|------|------|-------------|
+| `limit` | number | Results per page (0-200, default 100) |
+| `postId` | number | Filter by post ID |
+| `modelId` | number | Filter by model ID (gallery) |
+| `modelVersionId` | number | Filter by model version |
+| `username` | string | Filter by creator |
+| `nsfw` | boolean/enum | `None`, `Soft`, `Mature`, `X` |
+| `sort` | enum | `Most Reactions`, `Most Comments`, `Newest` |
+| `period` | enum | `AllTime`, `Year`, `Month`, `Week`, `Day` |
+| `page` | number | Page number |
+
+**Response:**
+
+```json
+{
+  "items": [
+    {
+      "id": 469632,
+      "url": "https://imagecache.civitai.com/.../image.jpeg",
+      "hash": "UKHU@6H?_ND*...",
+      "width": 1024,
+      "height": 1536,
+      "nsfw": false,
+      "nsfwLevel": "None",
+      "createdAt": "2023-04-11T15:33:12.500Z",
+      "postId": 138779,
+      "stats": {
+        "cryCount": 0,
+        "laughCount": 0,
+        "likeCount": 0,
+        "heartCount": 0,
+        "commentCount": 0
+      },
+      "meta": {
+        "seed": 234871805,
+        "Model": "Meina",
+        "steps": 35,
+        "prompt": "...",
+        "sampler": "DPM++ SDE Karras",
+        "cfgScale": 7,
+        "negativePrompt": "..."
+      },
+      "username": "Cooler_Rider"
+    }
+  ],
+  "metadata": {
+    "nextCursor": 101,
+    "nextPage": "https://civitai.com/api/v1/images?page=2"
+  }
+}
+```
+
+> Note: Uses cursor-based pagination since July 2023.
+
+---
+
+### GET /api/v1/models
+
+List models (checkpoints, LoRAs, etc.).
+
+**Query Parameters:**
+
+| Name | Type | Description |
+|------|------|-------------|
+| `limit` | number | Results per page (1-100, default 100) |
+| `page` | number | Page number |
+| `query` | string | Search by name |
+| `tag` | string | Filter by tag |
+| `username` | string | Filter by creator |
+| `types` | enum[] | `Checkpoint`, `TextualInversion`, `Hypernetwork`, `AestheticGradient`, `LORA`, `Controlnet`, `Poses` |
+| `sort` | enum | `Highest Rated`, `Most Downloaded`, `Newest` |
+| `period` | enum | `AllTime`, `Year`, `Month`, `Week`, `Day` |
+| `favorites` | boolean | Filter to user favorites (auth required) |
+| `hidden` | boolean | Filter to hidden models (auth required) |
+| `primaryFileOnly` | boolean | Only include primary file |
+| `allowNoCredit` | boolean | Filter by credit requirements |
+| `allowDerivatives` | boolean | Filter by derivative permissions |
+| `allowCommercialUse` | enum | `None`, `Image`, `Rent`, `Sell` |
+| `nsfw` | boolean | Filter NSFW content |
+| `supportsGeneration` | boolean | Filter by generation support |
+
+**Response:**
+
+```json
+{
+  "items": [
+    {
+      "id": 1234,
+      "name": "Model Name",
+      "description": "<p>HTML description</p>",
+      "type": "Checkpoint",
+      "nsfw": false,
+      "tags": ["anime", "realistic"],
+      "mode": null,
+      "creator": {
+        "username": "creator",
+        "image": "https://..."
+      },
+      "stats": {
+        "downloadCount": 50000,
+        "favoriteCount": 1000,
+        "commentCount": 50,
+        "ratingCount": 200,
+        "rating": 4.8
+      },
+      "modelVersions": [
+        {
+          "id": 5678,
+          "name": "v1.0",
+          "description": "Changelog...",
+          "createdAt": "2023-01-01T00:00:00.000Z",
+          "downloadUrl": "https://civitai.com/api/download/models/5678",
+          "trainedWords": ["trigger_word"],
+          "files": [
+            {
+              "name": "model.safetensors",
+              "sizeKB": 2048000,
+              "type": "Model",
+              "primary": true,
+              "metadata": {
+                "fp": "fp16",
+                "size": "pruned",
+                "format": "SafeTensor"
+              },
+              "pickleScanResult": "Success",
+              "virusScanResult": "Success",
+              "scannedAt": "2023-01-01T00:00:00.000Z",
+              "hashes": {
+                "SHA256": "abc123...",
+                "AutoV2": "def456..."
+              },
+              "downloadUrl": "https://civitai.com/api/download/models/5678"
+            }
+          ],
+          "images": [
+            {
+              "id": "img123",
+              "url": "https://...",
+              "nsfw": "None",
+              "width": 512,
+              "height": 768,
+              "meta": { "prompt": "..." }
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "metadata": {
+    "totalItems": 1000,
+    "currentPage": 1,
+    "pageSize": 100,
+    "totalPages": 10,
+    "nextPage": "https://civitai.com/api/v1/models?page=2"
+  }
+}
+```
+
+---
+
+### GET /api/v1/models/:modelId
+
+Get a single model by ID.
+
+**Response:** Same as single item from `/api/v1/models`
+
+---
+
+### GET /api/v1/model-versions/:modelVersionId
+
+Get a specific model version.
+
+**Response:**
+
+```json
+{
+  "id": 5678,
+  "modelId": 1234,
+  "name": "v1.0",
+  "createdAt": "2023-01-01T00:00:00.000Z",
+  "downloadUrl": "https://civitai.com/api/download/models/5678",
+  "trainedWords": ["trigger_word"],
+  "files": [...],
+  "images": [...]
+}
+```
+
+---
+
+### GET /api/v1/model-versions/by-hash/:hash
+
+Get model version by file hash (SHA256 or AutoV2).
+
+**Response:** Same as `/api/v1/model-versions/:modelVersionId`
+
+---
+
+### GET /api/v1/tags
+
+List available tags.
+
+**Query Parameters:**
+
+| Name | Type | Description |
+|------|------|-------------|
+| `limit` | number | Results per page (0-200, default 20). 0 returns all |
+| `page` | number | Page number |
+| `query` | string | Search tags by name |
+
+**Response:**
+
+```json
+{
+  "items": [
+    {
+      "name": "anime",
+      "modelCount": 5000,
+      "link": "https://civitai.com/api/v1/models?tag=anime"
+    }
+  ],
+  "metadata": {
+    "totalItems": 100,
+    "currentPage": 1,
+    "pageSize": 20,
+    "totalPages": 5
+  }
+}
+```
+
+---
+
+## Downloading Models
+
+### Download URL
+
+```
+https://civitai.com/api/download/models/{modelVersionId}
+```
+
+Or with token for restricted models:
+
+```
+https://civitai.com/api/download/models/{modelVersionId}?token={api_key}
+```
+
+### Using wget
+
+```bash
+wget https://civitai.com/api/download/models/12345 --content-disposition
+```
+
+The `--content-disposition` flag ensures the correct filename is used.
+
+### Using curl
+
+```bash
+curl -L -o model.safetensors \
+  "https://civitai.com/api/download/models/12345?token=${CIVITAI_API_KEY}"
+```
+
+---
+
+## Python Examples
+
+### Search and Download
+
+```python
+import httpx
+import os
+
+API_KEY = os.environ.get("CIVITAI_API_KEY")
+BASE_URL = "https://civitai.com/api/v1"
+
+headers = {"Authorization": f"Bearer {API_KEY}"} if API_KEY else {}
+
+# Search for models
+response = httpx.get(
+    f"{BASE_URL}/models",
+    params={
+        "query": "illustrious",
+        "types": "Checkpoint",
+        "sort": "Most Downloaded",
+        "limit": 5,
+    },
+    headers=headers,
+)
+models = response.json()
+
+for model in models["items"]:
+    print(f"{model['name']} - {model['stats']['downloadCount']} downloads")
+
+    # Get download URL for latest version
+    latest = model["modelVersions"][0]
+    primary_file = next(f for f in latest["files"] if f.get("primary"))
+    print(f"  Download: {primary_file['downloadUrl']}")
+```
+
+### Download with Resume
+
+```python
+import httpx
+from pathlib import Path
+
+def download_model(version_id: int, dest: Path, api_key: str | None = None):
+    url = f"https://civitai.com/api/download/models/{version_id}"
+    params = {"token": api_key} if api_key else {}
+    headers = {}
+    mode = "wb"
+    initial = 0
+
+    if dest.exists():
+        initial = dest.stat().st_size
+        headers["Range"] = f"bytes={initial}-"
+        mode = "ab"
+
+    with httpx.stream("GET", url, params=params, headers=headers, follow_redirects=True) as r:
+        total = int(r.headers.get("content-length", 0)) + initial
+
+        with open(dest, mode) as f:
+            for chunk in r.iter_bytes(1024 * 1024):
+                f.write(chunk)
+                downloaded = f.tell()
+                print(f"\r{downloaded / 1e6:.1f} / {total / 1e6:.1f} MB", end="")
+
+    print("\nDone!")
+
+# Usage
+download_model(12345, Path("model.safetensors"), os.environ.get("CIVITAI_API_KEY"))
+```
+
+---
+
+## Model Types
+
+| Type | Description |
+|------|-------------|
+| `Checkpoint` | Full model weights (SD 1.5, SDXL, etc.) |
+| `LORA` | Low-rank adaptation weights |
+| `TextualInversion` | Textual inversion embeddings |
+| `Hypernetwork` | Hypernetwork weights |
+| `AestheticGradient` | Aesthetic gradient files |
+| `Controlnet` | ControlNet models |
+| `Poses` | Pose reference files |
+
+## File Metadata
+
+| Field | Values |
+|-------|--------|
+| `fp` | `fp16`, `fp32` |
+| `size` | `full`, `pruned` |
+| `format` | `SafeTensor`, `PickleTensor`, `Other` |
+
+## Rate Limits
+
+The API has rate limits in place. If you receive a 429 response, implement exponential backoff.

main.py

@@ -1,6 +0,0 @@
-def main():
-    print("Hello from sft-get!")
-
-
-if __name__ == "__main__":
-    main()

pyproject.toml

@@ -1,7 +1,76 @@
 [project]
 name = "sft-get"
 version = "0.1.0"
-description = "Add your description here"
+description = "Read safetensor metadata and fetch CivitAI model information"
 readme = "README.md"
 requires-python = ">=3.12"
-dependencies = []
+dependencies = [
+    "safetensors>=0.4.0",
+    "httpx>=0.27.0",
+    "rich>=13.0.0",
+]
+
+[project.scripts]
+sft-get = "sft_get:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["sft_get.py"]
+
+[dependency-groups]
+dev = [
+    "nuitka>=2.0",
+    "ruff>=0.9.0",
+    "mypy>=1.14.0",
+]
+
+[tool.ruff]
+target-version = "py312"
+line-length = 100
+
+[tool.ruff.lint]
+select = [
+    "E",      # pycodestyle errors
+    "W",      # pycodestyle warnings
+    "F",      # pyflakes
+    "I",      # isort
+    "B",      # flake8-bugbear
+    "C4",     # flake8-comprehensions
+    "UP",     # pyupgrade
+    "ARG",    # flake8-unused-arguments
+    "SIM",    # flake8-simplify
+    "TCH",    # flake8-type-checking
+    "PTH",    # flake8-use-pathlib
+    "PL",     # pylint
+    "RUF",    # ruff-specific
+]
+ignore = [
+    "PLR0913",  # too many arguments
+    "PLR2004",  # magic value comparison
+]
+
+[tool.ruff.lint.isort]
+known-first-party = ["sft_get"]
+
+[tool.mypy]
+python_version = "3.12"
+strict = true
+warn_return_any = true
+warn_unused_configs = true
+disallow_untyped_defs = true
+disallow_incomplete_defs = true
+check_untyped_defs = true
+disallow_untyped_decorators = true
+no_implicit_optional = true
+warn_redundant_casts = true
+warn_unused_ignores = true
+warn_no_return = true
+follow_imports = "silent"
+ignore_missing_imports = false
+
+[[tool.mypy.overrides]]
+module = ["safetensors.*"]
+ignore_missing_imports = true

sft_get.py

@@ -0,0 +1,306 @@
+#!/usr/bin/env python3
+"""
+sft-get: Read safetensor metadata and fetch CivitAI model information.
+"""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import struct
+import sys
+from pathlib import Path
+from typing import Any
+
+import httpx
+from rich.console import Console
+from rich.progress import (
+    BarColumn,
+    DownloadColumn,
+    Progress,
+    SpinnerColumn,
+    TaskProgressColumn,
+    TextColumn,
+    TimeRemainingColumn,
+    TransferSpeedColumn,
+)
+from rich.table import Table
+
+console = Console()
+
+CIVITAI_API_BASE = "https://civitai.com/api/v1"
+
+
+def read_safetensor_metadata(file_path: Path) -> dict[str, Any]:
+    """Read metadata from a safetensor file header."""
+    with file_path.open("rb") as f:
+        # First 8 bytes are the header size (little-endian u64)
+        header_size_bytes = f.read(8)
+        if len(header_size_bytes) < 8:
+            raise ValueError("Invalid safetensor file: too short")
+
+        header_size = struct.unpack("<Q", header_size_bytes)[0]
+
+        if header_size > 100_000_000:  # 100MB sanity check
+            raise ValueError(f"Invalid header size: {header_size}")
+
+        header_bytes = f.read(header_size)
+        if len(header_bytes) < header_size:
+            raise ValueError("Invalid safetensor file: header truncated")
+
+        header: dict[str, Any] = json.loads(header_bytes.decode("utf-8"))
+
+    # Extract __metadata__ if present
+    metadata: dict[str, Any] = header.get("__metadata__", {})
+
+    # Count tensors (keys that aren't __metadata__)
+    tensor_count = sum(1 for k in header if k != "__metadata__")
+
+    return {
+        "metadata": metadata,
+        "tensor_count": tensor_count,
+        "header_size": header_size,
+    }
+
+
+def compute_sha256(file_path: Path) -> str:
+    """Compute SHA256 hash of a file with progress display."""
+    file_size = file_path.stat().st_size
+    sha256 = hashlib.sha256()
+    chunk_size = 1024 * 1024 * 8  # 8MB chunks
+
+    with Progress(
+        SpinnerColumn(),
+        TextColumn("[progress.description]{task.description}"),
+        BarColumn(),
+        TaskProgressColumn(),
+        DownloadColumn(),
+        TransferSpeedColumn(),
+        TimeRemainingColumn(),
+        console=console,
+    ) as progress:
+        task = progress.add_task(f"[cyan]Hashing {file_path.name}...", total=file_size)
+
+        with file_path.open("rb") as f:
+            while chunk := f.read(chunk_size):
+                sha256.update(chunk)
+                progress.update(task, advance=len(chunk))
+
+    return sha256.hexdigest().upper()
+
+
+def fetch_civitai_by_hash(sha256_hash: str, api_key: str | None = None) -> dict[str, Any] | None:
+    """Fetch model information from CivitAI by SHA256 hash."""
+    url = f"{CIVITAI_API_BASE}/model-versions/by-hash/{sha256_hash}"
+    headers: dict[str, str] = {}
+    if api_key:
+        headers["Authorization"] = f"Bearer {api_key}"
+
+    with Progress(
+        SpinnerColumn(),
+        TextColumn("[progress.description]{task.description}"),
+        console=console,
+        transient=True,
+    ) as progress:
+        progress.add_task("[cyan]Fetching from CivitAI...", total=None)
+
+        try:
+            response = httpx.get(url, headers=headers, timeout=30.0)
+            if response.status_code == 404:
+                return None
+            response.raise_for_status()
+            result: dict[str, Any] = response.json()
+            return result
+        except httpx.HTTPStatusError as e:
+            console.print(f"[red]API error: {e.response.status_code}[/red]")
+            return None
+        except httpx.RequestError as e:
+            console.print(f"[red]Request error: {e}[/red]")
+            return None
+
+
+def _display_file_info(file_path: Path, local_metadata: dict[str, Any], sha256_hash: str) -> None:
+    """Display file information table."""
+    file_table = Table(title="File Information", show_header=True, header_style="bold magenta")
+    file_table.add_column("Property", style="cyan")
+    file_table.add_column("Value", style="green")
+
+    file_table.add_row("File", str(file_path.name))
+    file_table.add_row("Path", str(file_path.parent))
+    file_table.add_row("Size", f"{file_path.stat().st_size / (1024**3):.2f} GB")
+    file_table.add_row("SHA256", sha256_hash)
+    file_table.add_row("Header Size", f"{local_metadata['header_size']:,} bytes")
+    file_table.add_row("Tensor Count", str(local_metadata["tensor_count"]))
+
+    console.print()
+    console.print(file_table)
+
+
+def _display_local_metadata(local_metadata: dict[str, Any]) -> None:
+    """Display local safetensor metadata table."""
+    if local_metadata["metadata"]:
+        meta_table = Table(
+            title="Safetensor Metadata", show_header=True, header_style="bold magenta"
+        )
+        meta_table.add_column("Key", style="cyan")
+        meta_table.add_column("Value", style="green", max_width=80)
+
+        for key, value in sorted(local_metadata["metadata"].items()):
+            display_value = str(value)
+            if len(display_value) > 200:
+                display_value = display_value[:200] + "..."
+            meta_table.add_row(key, display_value)
+
+        console.print()
+        console.print(meta_table)
+    else:
+        console.print()
+        console.print("[yellow]No embedded metadata found in safetensor file.[/yellow]")
+
+
+def _display_civitai_data(civitai_data: dict[str, Any] | None) -> None:
+    """Display CivitAI model information table."""
+    if not civitai_data:
+        console.print()
+        console.print("[yellow]Model not found on CivitAI.[/yellow]")
+        return
+
+    civit_table = Table(
+        title="CivitAI Model Information", show_header=True, header_style="bold magenta"
+    )
+    civit_table.add_column("Property", style="cyan")
+    civit_table.add_column("Value", style="green", max_width=80)
+
+    civit_table.add_row("Model ID", str(civitai_data.get("modelId", "N/A")))
+    civit_table.add_row("Version ID", str(civitai_data.get("id", "N/A")))
+    civit_table.add_row("Version Name", str(civitai_data.get("name", "N/A")))
+    civit_table.add_row("Base Model", str(civitai_data.get("baseModel", "N/A")))
+    civit_table.add_row("Created At", str(civitai_data.get("createdAt", "N/A")))
+
+    # Trained words
+    trained_words: list[str] = civitai_data.get("trainedWords", [])
+    if trained_words:
+        civit_table.add_row("Trigger Words", ", ".join(trained_words))
+
+    # Download URL
+    download_url = str(civitai_data.get("downloadUrl", "N/A"))
+    civit_table.add_row("Download URL", download_url)
+
+    # File info from CivitAI
+    files: list[dict[str, Any]] = civitai_data.get("files", [])
+    for f in files:
+        if f.get("primary"):
+            civit_table.add_row("Primary File", str(f.get("name", "N/A")))
+            civit_table.add_row(
+                "File Size (CivitAI)",
+                f"{f.get('sizeKB', 0) / 1024:.2f} MB",
+            )
+            meta: dict[str, Any] = f.get("metadata", {})
+            if meta:
+                civit_table.add_row("Format", str(meta.get("format", "N/A")))
+                civit_table.add_row("Precision", str(meta.get("fp", "N/A")))
+                civit_table.add_row("Size Type", str(meta.get("size", "N/A")))
+
+    console.print()
+    console.print(civit_table)
+
+    # Model page link
+    model_id = civitai_data.get("modelId")
+    if model_id:
+        console.print()
+        console.print(
+            f"[bold blue]View on CivitAI:[/bold blue] https://civitai.com/models/{model_id}"
+        )
+
+
+def display_results(
+    file_path: Path,
+    local_metadata: dict[str, Any],
+    sha256_hash: str,
+    civitai_data: dict[str, Any] | None,
+) -> None:
+    """Display results in rich tables."""
+    _display_file_info(file_path, local_metadata, sha256_hash)
+    _display_local_metadata(local_metadata)
+    _display_civitai_data(civitai_data)
+
+
+def main() -> int:
+    """Main entry point."""
+    parser = argparse.ArgumentParser(
+        description="Read safetensor metadata and fetch CivitAI model information.",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+    )
+    parser.add_argument(
+        "file",
+        type=Path,
+        help="Path to the safetensor file",
+    )
+    parser.add_argument(
+        "--api-key",
+        type=str,
+        default=None,
+        help="CivitAI API key for authenticated requests",
+    )
+    parser.add_argument(
+        "--skip-civitai",
+        action="store_true",
+        help="Skip CivitAI API lookup",
+    )
+    parser.add_argument(
+        "--json",
+        action="store_true",
+        dest="json_output",
+        help="Output results as JSON",
+    )
+
+    args = parser.parse_args()
+
+    file_path: Path = args.file.resolve()
+
+    if not file_path.exists():
+        console.print(f"[red]Error: File not found: {file_path}[/red]")
+        return 1
+
+    if file_path.suffix.lower() not in (".safetensors", ".sft"):
+        console.print("[yellow]Warning: File does not have .safetensors extension[/yellow]")
+
+    try:
+        # Read local metadata
+        console.print(f"[bold]Reading safetensor file:[/bold] {file_path.name}")
+        local_metadata = read_safetensor_metadata(file_path)
+
+        # Compute SHA256
+        sha256_hash = compute_sha256(file_path)
+
+        # Fetch from CivitAI
+        civitai_data = None
+        if not args.skip_civitai:
+            civitai_data = fetch_civitai_by_hash(sha256_hash, args.api_key)
+
+        if args.json_output:
+            output = {
+                "file": str(file_path),
+                "sha256": sha256_hash,
+                "header_size": local_metadata["header_size"],
+                "tensor_count": local_metadata["tensor_count"],
+                "metadata": local_metadata["metadata"],
+                "civitai": civitai_data,
+            }
+            console.print_json(data=output)
+        else:
+            display_results(file_path, local_metadata, sha256_hash, civitai_data)
+
+        return 0
+
+    except ValueError as e:
+        console.print(f"[red]Error reading safetensor: {e}[/red]")
+        return 1
+    except Exception as e:
+        console.print(f"[red]Unexpected error: {e}[/red]")
+        return 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

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