Initial update

app.py

@@ -9,6 +9,10 @@ from transformers.pipelines.audio_utils import ffmpeg_read
 import tempfile
 import os
 
+#===============
+# Define main parameters
+#===============
+
 MODEL_NAME = "openai/whisper-large-v3-turbo"
 BATCH_SIZE = 8
 FILE_LIMIT_MB = 1000
@@ -23,90 +27,96 @@ pipe = pipeline(
     device=device,
 )
 
+#===============
+# Main functions
+#===============
 
 @spaces.GPU
 def transcribe(inputs, task):
     if inputs is None:
         raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
 
-    text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
+    result = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)
+    text = result["text"]
     return  text
 
 
-def _return_yt_html_embed(yt_url):
-    video_id = yt_url.split("?v=")[-1]
-    HTML_str = (
-        f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
-        " </center>"
-    )
-    return HTML_str
+# def _return_yt_html_embed(yt_url):
+#     video_id = yt_url.split("?v=")[-1]
+#     HTML_str = (
+#         f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
+#         " </center>"
+#     )
+#     return HTML_str
 
-def download_yt_audio(yt_url, filename):
-    info_loader = youtube_dl.YoutubeDL()
+# def download_yt_audio(yt_url, filename):
+#     info_loader = youtube_dl.YoutubeDL()
     
-    try:
-        info = info_loader.extract_info(yt_url, download=False)
-    except youtube_dl.utils.DownloadError as err:
-        raise gr.Error(str(err))
+#     try:
+#         info = info_loader.extract_info(yt_url, download=False)
+#     except youtube_dl.utils.DownloadError as err:
+#         raise gr.Error(str(err))
     
-    file_length = info["duration_string"]
-    file_h_m_s = file_length.split(":")
-    file_h_m_s = [int(sub_length) for sub_length in file_h_m_s]
+#     file_length = info["duration_string"]
+#     file_h_m_s = file_length.split(":")
+#     file_h_m_s = [int(sub_length) for sub_length in file_h_m_s]
     
-    if len(file_h_m_s) == 1:
-        file_h_m_s.insert(0, 0)
-    if len(file_h_m_s) == 2:
-        file_h_m_s.insert(0, 0)
-    file_length_s = file_h_m_s[0] * 3600 + file_h_m_s[1] * 60 + file_h_m_s[2]
+#     if len(file_h_m_s) == 1:
+#         file_h_m_s.insert(0, 0)
+#     if len(file_h_m_s) == 2:
+#         file_h_m_s.insert(0, 0)
+#     file_length_s = file_h_m_s[0] * 3600 + file_h_m_s[1] * 60 + file_h_m_s[2]
     
-    if file_length_s > YT_LENGTH_LIMIT_S:
-        yt_length_limit_hms = time.strftime("%HH:%MM:%SS", time.gmtime(YT_LENGTH_LIMIT_S))
-        file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
-        raise gr.Error(f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video.")
+#     if file_length_s > YT_LENGTH_LIMIT_S:
+#         yt_length_limit_hms = time.strftime("%HH:%MM:%SS", time.gmtime(YT_LENGTH_LIMIT_S))
+#         file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
+#         raise gr.Error(f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video.")
     
-    ydl_opts = {"outtmpl": filename, "format": "worstvideo[ext=mp4]+bestaudio[ext=m4a]/best[ext=mp4]/best"}
+#     ydl_opts = {"outtmpl": filename, "format": "worstvideo[ext=mp4]+bestaudio[ext=m4a]/best[ext=mp4]/best"}
     
-    with youtube_dl.YoutubeDL(ydl_opts) as ydl:
-        try:
-            ydl.download([yt_url])
-        except youtube_dl.utils.ExtractorError as err:
-            raise gr.Error(str(err))
-
-@spaces.GPU
-def yt_transcribe(yt_url, task, max_filesize=75.0):
-    html_embed_str = _return_yt_html_embed(yt_url)
-
-    with tempfile.TemporaryDirectory() as tmpdirname:
-        filepath = os.path.join(tmpdirname, "video.mp4")
-        download_yt_audio(yt_url, filepath)
-        with open(filepath, "rb") as f:
-            inputs = f.read()
-
-    inputs = ffmpeg_read(inputs, pipe.feature_extractor.sampling_rate)
-    inputs = {"array": inputs, "sampling_rate": pipe.feature_extractor.sampling_rate}
-
-    text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
-
-    return html_embed_str, text
-
-
-demo = gr.Blocks(theme=gr.themes.Ocean())
-
-mf_transcribe = gr.Interface(
-    fn=transcribe,
-    inputs=[
-        gr.Audio(sources="microphone", type="filepath"),
-        gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
-    ],
-    outputs="text",
-    title="Whisper Large V3 Turbo: Transcribe Audio",
-    description=(
-        "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
-        f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
-        " of arbitrary length."
-    ),
-    allow_flagging="never",
-)
+#     with youtube_dl.YoutubeDL(ydl_opts) as ydl:
+#         try:
+#             ydl.download([yt_url])
+#         except youtube_dl.utils.ExtractorError as err:
+#             raise gr.Error(str(err))
+
+# @spaces.GPU
+# def yt_transcribe(yt_url, task, max_filesize=75.0):
+#     html_embed_str = _return_yt_html_embed(yt_url)
+
+#     with tempfile.TemporaryDirectory() as tmpdirname:
+#         filepath = os.path.join(tmpdirname, "video.mp4")
+#         download_yt_audio(yt_url, filepath)
+#         with open(filepath, "rb") as f:
+#             inputs = f.read()
+
+#     inputs = ffmpeg_read(inputs, pipe.feature_extractor.sampling_rate)
+#     inputs = {"array": inputs, "sampling_rate": pipe.feature_extractor.sampling_rate}
+
+#     text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
+
+#     return html_embed_str, text
+
+
+#===============
+# Build the frontend
+#===============
+
+# mf_transcribe = gr.Interface(
+#     fn=transcribe,
+#     inputs=[
+#         gr.Audio(sources="microphone", type="filepath"),
+#         gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
+#     ],
+#     outputs="text",
+#     title="Whisper Large V3 Turbo: Transcribe Audio",
+#     description=(
+#         "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
+#         f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
+#         " of arbitrary length."
+#     ),
+#     allow_flagging="never",
+# )
 
 file_transcribe = gr.Interface(
     fn=transcribe,
@@ -124,24 +134,32 @@ file_transcribe = gr.Interface(
     allow_flagging="never",
 )
 
-yt_transcribe = gr.Interface(
-    fn=yt_transcribe,
-    inputs=[
-        gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
-        gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
-    ],
-    outputs=["html", "text"],
-    title="Whisper Large V3: Transcribe YouTube",
-    description=(
-        "Transcribe long-form YouTube videos with the click of a button! Demo uses the checkpoint"
-        f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe video files of"
-        " arbitrary length."
-    ),
-    allow_flagging="never",
-)
+# yt_transcribe = gr.Interface(
+#     fn=yt_transcribe,
+#     inputs=[
+#         gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
+#         gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
+#     ],
+#     outputs=["html", "text"],
+#     title="Whisper Large V3: Transcribe YouTube",
+#     description=(
+#         "Transcribe long-form YouTube videos with the click of a button! Demo uses the checkpoint"
+#         f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe video files of"
+#         " arbitrary length."
+#     ),
+#     allow_flagging="never",
+# )
+
+#===============
+# Launch
+#===============
 
-with demo:
-    gr.TabbedInterface([mf_transcribe, file_transcribe, yt_transcribe], ["Microphone", "Audio file", "YouTube"])
+demo = gr.Blocks(theme=gr.themes.Ocean())
 
-demo.queue().launch(ssr_mode=False)
+# with demo:
+#     gr.TabbedInterface([mf_transcribe, file_transcribe, yt_transcribe], ["Microphone", "Audio file", "YouTube"])
 
+with demo:
+    gr.TabbedInterface([file_transcribe], ["Audio file"])
+    
+demo.queue().launch(ssr_mode=False)