make gradio working with treads
This commit is contained in:
@@ -1,5 +1,5 @@
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from .qtfaststart import *
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from .activity_tracker import *
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from .multi import *
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from .interface import *
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from .stg import *
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from .interactions import *
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@@ -3,7 +3,16 @@ Stores global variables for the app.
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"""
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# Global variable to store the model
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from threading import Event
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import time
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MODEL = None
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MODEL_THREAD_PARAMS = None
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MODEL_THREAD = None
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# Global variable to track user activity
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USER_ACTIVE = False
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LAST_USED = time.time()
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TIMEOUT = 30 #seconds
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TRANSCRIBE_ACTIVE = Event()
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@@ -3,10 +3,12 @@ This file contains ervery function that will be called when the user interacts w
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UI like pressing a button or uploading a file.
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"""
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from math import pi
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import time
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import gradio as gr
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import scraibe.app.global_var as gv
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from scraibe import Transcript
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from scraibe.app.stg import GradioTranscriptionInterface
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import threading
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def select_task(choice):
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# tell the app that it is still in use
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@@ -86,9 +88,16 @@ def run_scraibe(task,
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# get *args which are not None
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pipe = gv.MODEL
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if gv.MODEL is None and gv.MODEL_THREAD_PARAMS is not None:
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progress(0, desc='Model was not loaded to conserve resources. Loading model...')
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time.sleep(1)
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gv.MODEL_THREAD = threading.Thread(**gv.MODEL_THREAD_PARAMS)
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gv.MODEL_THREAD.start()
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gv.MODEL_THREAD.join()
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progress(0, desc='Starting task...')
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pipe = GradioTranscriptionInterface()
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progress(0.1, desc='Starting task...')
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source = audio1 or audio2 or video1 or video2 or file_in
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if isinstance(source, list):
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@@ -9,8 +9,6 @@ import scraibe.app.global_var as gv
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from .interactions import *
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from .stg import *
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from scraibe import Scraibe
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theme = gr.themes.Soft(
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primary_hue="green",
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secondary_hue='orange',
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@@ -36,10 +34,7 @@ LANGUAGES = [
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CURRENT_PATH = os.path.dirname(os.path.realpath(__file__))
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def gradio_Interface(pipe : Scraibe = None):
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if pipe is not None:
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gv.MODEL = GradioTranscriptionInterface(pipe)
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def gradio_Interface():
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with gr.Blocks(theme=theme,title='ScrAIbe: Automatic Audio Transcription') as demo:
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@@ -0,0 +1,44 @@
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"""
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This file contains the functions which are related to monitoring the actual app usage.
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Therefore, the app is to be more efficient in the usage of the resources.
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By for example, unloading or reloading the model.
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"""
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import time
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import gc
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from typing import Union
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import torch
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import scraibe.app.global_var as gv
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from scraibe.autotranscript import Scraibe
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def load_model_thread(model : Union[Scraibe, dict] = None):
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if model is None:
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gv.MODEL = Scraibe()
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elif type(model) is Scraibe:
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gv.MODEL = model
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elif type(model) is dict:
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gv.MODEL = Scraibe(**model)
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else:
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raise TypeError("model must be of type Scraibe, or dict")
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gv.LAST_USED = time.time()
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# Create a thread to monitor user activity
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def delete_unused_model():
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while True:
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_unload_porperty = (not gv.TRANSCRIBE_ACTIVE.is_set() and (time.time() - gv.LAST_USED > gv.TIMEOUT) and gv.MODEL is not None)
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if _unload_porperty:
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del gv.MODEL
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gv.MODEL = None
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gc.collect()
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torch.cuda.empty_cache()
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gv.MODEL_THREAD.join()
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time.sleep(int(gv.TIMEOUT/5))
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+28
-5
@@ -9,7 +9,8 @@ It makes adds gradio interactions to the scraibe class in the back.
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import json
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import gradio as gr
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from tqdm import tqdm
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from scraibe import Scraibe
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import scraibe.app.global_var as gv
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class GradioTranscriptionInterface:
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@@ -17,14 +18,14 @@ class GradioTranscriptionInterface:
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Interface handling the interaction between Gradio UI and the Audio Transcription system.
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"""
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def __init__(self, model: Scraibe):
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def __init__(self):
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"""
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Initializes the GradioTranscriptionInterface with a transcription model.
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Args:
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model (Scraibe): Model responsible for audio transcription tasks.
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"""
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self.model = model
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self.model = gv.MODEL
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def auto_transcribe(self, source,
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num_speakers : int,
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@@ -37,6 +38,8 @@ class GradioTranscriptionInterface:
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tuple: Transcribed text (str), JSON output (dict)
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"""
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gv.TRANSCRIBE_ACTIVE.set()
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kwargs = {
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"num_speakers": num_speakers if num_speakers != 0 else None,
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"language": language if language != "None" else None,
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@@ -46,9 +49,11 @@ class GradioTranscriptionInterface:
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try:
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result = self.model.autotranscribe(source, **kwargs)
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except ValueError:
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gv.TRANSCRIBE_ACTIVE.clear()
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raise gr.Error("Couldn't detect any speech in the provided audio. \
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Please try again!")
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gv.TRANSCRIBE_ACTIVE.clear()
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return str(result), result.get_json()
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elif isinstance(source, list):
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@@ -75,9 +80,13 @@ class GradioTranscriptionInterface:
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else:
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out_dict[source_names[i]] = r.get_dict()
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gv.TRANSCRIBE_ACTIVE.clear()
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return out, json.dumps(out_dict, indent=4)
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else:
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gv.TRANSCRIBE_ACTIVE.clear()
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raise gr.Error("Please provide a valid audio file.")
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@@ -88,6 +97,9 @@ class GradioTranscriptionInterface:
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Returns:
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str: Transcribed text.
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"""
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gv.TRANSCRIBE_ACTIVE.set()
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kwargs = {
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"language": language if language != "None" else None,
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"task": 'translate' if translation == "Yes" else None
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@@ -95,7 +107,7 @@ class GradioTranscriptionInterface:
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if isinstance(source, str):
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result = self.model.transcribe(source, **kwargs)
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gv.TRANSCRIBE_ACTIVE.clear()
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return str(result)
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elif isinstance(source, list):
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@@ -111,9 +123,12 @@ class GradioTranscriptionInterface:
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out += str(res)
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out += "\n\n"
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gv.TRANSCRIBE_ACTIVE.clear()
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return out
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else:
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gv.TRANSCRIBE_ACTIVE.clear()
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raise gr.Error("Please provide a valid audio file.")
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def perform_diarisation(self, source, num_speakers):
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@@ -123,6 +138,9 @@ class GradioTranscriptionInterface:
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Returns:
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str: JSON output of diarisation result.
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"""
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gv.TRANSCRIBE_ACTIVE.set()
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kwargs = {
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"num_speakers": num_speakers if num_speakers != 0 else None,
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}
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@@ -131,9 +149,10 @@ class GradioTranscriptionInterface:
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try:
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result = self.model.diarization(source, **kwargs)
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except ValueError:
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gv.TRANSCRIBE_ACTIVE.clear()
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raise gr.Error("Couldn't detect any speech in the provided audio. \
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Please try again!")
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gv.TRANSCRIBE_ACTIVE.clear()
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return json.dumps(result, indent=2)
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elif isinstance(source, list):
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source_names = [s.split("/")[-1] for s in source]
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@@ -142,6 +161,7 @@ class GradioTranscriptionInterface:
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try:
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res = self.model.diarization(s, **kwargs)
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except ValueError:
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res = f"NO DIARISATION FOUND FOR {s}"
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gr.Warning(f"Couldn't detect any speech in {s} will skip this file.")
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result.append(res)
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@@ -151,7 +171,10 @@ class GradioTranscriptionInterface:
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for i, res in enumerate(result):
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out[source_names[i]] = res
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gv.TRANSCRIBE_ACTIVE.clear()
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return json.dumps(out, indent=4)
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else:
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gv.TRANSCRIBE_ACTIVE.clear()
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gr.Error("Please provide a valid audio file.")
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