Remove Hugging Face Support (#60)

README.md

@@ -13,7 +13,7 @@ Despite this, models are not scanned with the rigor of a PDF file in your inbox.
 
 This needs to change, and proper tooling is the first step.
 
-![ModelScan Preview](https://github.com/protectai/modelscan/raw/main/imgs/modelscan_hf_demo.gif)
+![ModelScan Preview](/imgs/modelscan-unsafe-model.gif)
 
 ModelScan is an open source project that scans models to determine if they contain 
 unsafe code. It is the first model scanning tool to support multiple model formats. 
@@ -34,12 +34,6 @@ With it installed, scan a model:
 modelscan -p /path/to/model_file.h5
 ```
 
-Or if you want to scan all the models in a Hugging Face Repository:
-
-```bash
-modelscan -hf owner/model-repository-name
-```
-
 ## Why You Should Scan Models
 
 Models are often created from automated pipelines, others may come from a data scientist’s laptop. In either case the model needs to move from one machine to another before it is used. That process of saving a model to disk is called serialization.
@@ -75,8 +69,7 @@ ModelScan ranks the unsafe code as:
 * MEDIUM
 * LOW
 
-Things are ranked consistently if the models are local or stored in Hugging Face
-![ModelScan Flow Chart](https://github.com/protectai/modelscan/raw/main/imgs/model_scan_flow_chart.png)
+![ModelScan Flow Chart](/imgs/model_scan_flow_chart.png)
 
 If an issue is detected, reach out to the author's of the model immediately to determine the cause.
 
@@ -123,7 +116,7 @@ ModelScan supports the following arguments via the CLI:
 | ```modelscan -h ```                   | -h or --help         | View usage help                            |
 | ```modelscan -v ```                   | -v or --version      | View version information                   |
 | ```modelscan -p /path/to/model_file```| -p or --path         | Scan a locally stored model                |
-| ```modelscan -hf repo/model_file```   |-hf or --huggingface  | Scan all the models in a Hugging Face model repository| 
+
 
 Remember models are just like any other form of digital media, you should scan content from any untrusted source before use.
 

modelscan/cli.py

@@ -35,16 +35,6 @@ def format_usage(self, ctx: click.Context, formatter: click.HelpFormatter) -> No
     default=None,
     help="Path to the file or folder to scan",
 )
-# @click.option(
-#     "-u", "--url", type=str, default=None, help="URL to the file or folder to scan"
-# )
-@click.option(
-    "-hf",
-    "--huggingface",
-    type=str,
-    default=None,
-    help="Name of the Hugging Face model to scan",
-)
 @click.option(
     "-l",
     "--log",
@@ -62,8 +52,6 @@ def format_usage(self, ctx: click.Context, formatter: click.HelpFormatter) -> No
 def cli(
     ctx: click.Context,
     log: str,
-    # url: Optional[str],
-    huggingface: Optional[str],
     path: Optional[str],
     show_skipped: bool,
 ) -> int:
@@ -80,14 +68,9 @@ def cli(
             raise FileNotFoundError(f"Path {path} does not exist")
         else:
             modelscan.scan_path(pathlibPath)
-    # elif url is not None:
-    #     modelscan.scan_url(url)
-    elif huggingface is not None:
-        modelscan.scan_huggingface_model(huggingface)
+
     else:
-        raise click.UsageError(
-            "Command line must include either a path or a Hugging Face model"
-        )
+        raise click.UsageError("Command line must include a path")
     ConsoleReport.generate(
         modelscan.issues,
         modelscan.errors,

modelscan/modelscan.py

@@ -14,7 +14,7 @@
 from modelscan.models.keras.scan import KerasScan
 from modelscan.models.scan import ScanBase
 from modelscan.tools.utils import _is_zipfile
-from modelscan.utils import fetch_huggingface_repo_files, read_huggingface_file
+
 
 logger = logging.getLogger("modelscan")
 
@@ -61,52 +61,6 @@ def _scan_directory(self, directory_path: Path) -> None:
             if not path.is_dir():
                 self.scan_path(path)
 
-    def scan_huggingface_model(self, repo_id: str) -> None:
-        # List model files
-        file_names = fetch_huggingface_repo_files(repo_id)
-        if not file_names:
-            logger.error(f"Hugging face repo {repo_id} didn't return any files")
-            return
-
-        for file_name in file_names:
-            fq_file_name = f"{repo_id}/{file_name}"
-            file_ext = os.path.splitext(file_name)[1]
-            if (
-                file_ext not in self.supported_extensions
-                and file_ext not in self.supported_zip_extensions
-            ):
-                logger.debug(f"Skipping: {fq_file_name} is not supported")
-                self._skipped.append(fq_file_name)
-                continue
-
-            raw_bytes = read_huggingface_file(repo_id, file_name)
-            if not raw_bytes:
-                logger.debug(f"Skipping: Failed to read {fq_file_name}")
-                self._skipped.append(fq_file_name)
-                continue
-
-            data = io.BytesIO(raw_bytes)
-            if (
-                _is_zipfile(source=fq_file_name, data=data)
-                or file_ext in self.supported_zip_extensions
-            ):
-                try:
-                    self._scan_zip(source=fq_file_name, data=data)
-                except:
-                    logger.debug(f"Skipped: Failed to read")
-            else:
-                self._scan_source(source=fq_file_name, extension=file_ext, data=data)
-
-    def scan_url(self, url: str) -> None:
-        # Todo: before it was just scanning scanning_pickle_bytes
-        # We need to validate this url and determine what type of file it is
-        # self._scan_bytes(
-        #     data=io.BytesIO(_http_get(url)),
-        #     source=url,
-        #     extension=file_ext,
-        # )
-        pass
-
     def _scan_source(
         self,
         source: Union[str, Path],