Update app.py

app.py

@@ -1,6 +1,7 @@
+import gradio as gr
 import torch
 from transformers import pipeline
-import gradio as gr
+from timestamp import format_timestamp
 
 MODEL_NAME = "openai/whisper-medium"
 BATCH_SIZE = 8
@@ -14,28 +15,6 @@ pipe = pipeline(
     device=device,
 )
 
-
-# Copied from https://github.com/openai/whisper/blob/c09a7ae299c4c34c5839a76380ae407e7d785914/whisper/utils.py#L50
-def format_timestamp(seconds: float, always_include_hours: bool = False, decimal_marker: str = "."):
-    if seconds is not None:
-        milliseconds = round(seconds * 1000.0)
-
-        hours = milliseconds // 3_600_000
-        milliseconds -= hours * 3_600_000
-
-        minutes = milliseconds // 60_000
-        milliseconds -= minutes * 60_000
-
-        seconds = milliseconds // 1_000
-        milliseconds -= seconds * 1_000
-
-        hours_marker = f"{hours:02d}:" if always_include_hours or hours > 0 else ""
-        return f"{hours_marker}{minutes:02d}:{seconds:02d}{decimal_marker}{milliseconds:03d}"
-    else:
-        # we have a malformed timestamp so just return it as is
-        return seconds
-
-
 def transcribe(file, task, return_timestamps):
     outputs = pipe(file, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=return_timestamps)
     text = outputs["text"]