Update app.py

app.py

@@ -4,24 +4,28 @@ import subprocess
 import os
 import tempfile
 
-
-def convert_ts_to_mp4(dataset_name, file_name):
+def convert_ts_to_mp4(dataset_name, file_name, hf_token):
     """
     Downloads a .ts video file from a Hugging Face dataset,
     converts it to .mp4 using ffmpeg, and returns the path
-    to the .mp4 file.
+    to the .mp4 file.  Handles both public and private datasets.
 
     Args:
         dataset_name (str): The name of the Hugging Face dataset.
         file_name (str): The name of the .ts file within the dataset.
                         It should be just the filename, not the full path.
+        hf_token (str):  The Hugging Face token.  If None or empty,
+                        it's assumed the dataset is public.
 
     Returns:
         str: The path to the converted .mp4 file, or None on error.
     """
     try:
         # 1. Load the dataset
-        dataset = load_dataset(dataset_name, streaming=True)
+        if hf_token:
+            dataset = load_dataset(dataset_name, use_auth_token=hf_token, streaming=True)
+        else:
+            dataset = load_dataset(dataset_name, streaming=True)
 
         # 2. Find the file.  This part assumes the filename is unique
         #    within the dataset.  For more complex datasets, you might
@@ -35,7 +39,7 @@ def convert_ts_to_mp4(dataset_name, file_name):
                 if "file" in example and os.path.basename(example["file"]) == file_name:
                     file_url = example["file"]
                     break
-                elif isinstance(example, dict):  # Check for nested file paths.
+                elif isinstance(example, dict): # Check for nested file paths.
                     for key, value in example.items():
                         if isinstance(value, str) and os.path.basename(value) == file_name:
                             file_url = value;
@@ -68,7 +72,7 @@ def convert_ts_to_mp4(dataset_name, file_name):
                             "-c:v",
                             "libx264",  # Use libx264 for H.264 encoding (common)
                             "-c:a",
-                            "aac",  # Use AAC for audio encoding (common)
+                            "aac",      # Use AAC for audio encoding (common)
                             "-y",  # Overwrite output file if it exists
                             mp4_file.name,
                         ],
@@ -89,6 +93,7 @@ def convert_ts_to_mp4(dataset_name, file_name):
         return f"An error occurred: {e}"
 
 
+
 def gradio_interface():
     """
     Defines the Gradio interface for the application.
@@ -96,12 +101,17 @@ def gradio_interface():
     inputs = [
         gr.Textbox(
             label="Hugging Face Dataset Name",
-            placeholder="e.g., 'PolyAI/minds-14'",
+            placeholder="e.g., 'PolyAI/minds-14' or 'my-org/my-private-dataset'",
         ),
         gr.Textbox(
             label="TS File Name (within the dataset)",
             placeholder="e.g., 'file_name.ts'",
         ),
+        gr.Textbox(
+            label="Hugging Face Token (for private datasets)",
+            placeholder="(Optional) Enter your Hugging Face token here, or set it as HF_TOKEN in Space settings",
+            type="password",
+        ),
     ]
     outputs = gr.File(label="Converted MP4 File")  # Use gr.File for downloadable files
 
@@ -109,18 +119,22 @@ def gradio_interface():
     description = (
         "Convert .ts video files from Hugging Face datasets to .mp4 format. "
         "Provide the dataset name and the name of the .ts file.  The converted "
-        ".mp4 file will be available for download."
+        ".mp4 file will be available for download.  "
+        "For private datasets, you *must* provide a Hugging Face token, either directly in the input box, or, preferably, by setting the `HF_TOKEN` secret in your Space's settings."
     )
 
     # Example Usage (Corrected)
     article = """
     Example Usage:
 
-    1.  For the 'PolyAI/minds-14' dataset and the file 'audio/en/common_voice_en_7722.ts', 
-        enter 'PolyAI/minds-14' in the \"Hugging Face Dataset Name\" field and 
-        'common_voice_en_7722.ts' in the \"TS File Name\" field (note: the example dataset in the original prompt did not contain .ts files, so I've provided a placeholder.  You'll need to adapt this to a dataset that actually *does* have .ts files).
-    2.  Click the 'Submit' button.
-    3.  The converted .mp4 file will be processed, and a download link will be provided.
+    1.  For a public dataset like 'PolyAI/minds-14' and the file 'audio/en/common_voice_en_7722.ts',
+        enter 'PolyAI/minds-14' in the "Hugging Face Dataset Name" field and
+        'common_voice_en_7722.ts' in the "TS File Name" field.  Leave the "Hugging Face Token" field empty.
+    2.  For a private dataset, enter the dataset name (e.g., 'my-org/my-private-dataset')
+        and the .ts file name.  Enter your Hugging Face token in the "Hugging Face Token" field
+        *or*, preferably, add your token as a secret named `HF_TOKEN` in your Space's settings.
+    3.  Click the 'Submit' button.
+    4.  The converted .mp4 file will be processed, and a download link will be provided.
     """
 
     return gr.Interface(
@@ -133,5 +147,6 @@ def gradio_interface():
     )
 
 
+
 if __name__ == "__main__":
     gradio_interface().launch()