make gradio working with treads

scraibe/app/__init__.py

@@ -1,5 +1,5 @@
 from .qtfaststart import *
-from .activity_tracker import *
+from .multi import *
 from .interface import *
 from .stg import *
 from .interactions import *

scraibe/app/global_var.py

@@ -3,7 +3,16 @@ Stores global variables for the app.
 """
 
 # Global variable to store the model
+from threading import Event
+
+import time
+
+
 MODEL = None
+MODEL_THREAD_PARAMS = None
+MODEL_THREAD = None
 
 # Global variable to track user activity
-USER_ACTIVE = False
+LAST_USED = time.time()
+TIMEOUT = 30 #seconds
+TRANSCRIBE_ACTIVE = Event()

scraibe/app/interactions.py

@@ -3,10 +3,12 @@ This file contains ervery function that will be called when the user interacts w
 UI like pressing a button or uploading a file.
 """
 
-from math import pi
+import time
 import gradio as gr 
 import scraibe.app.global_var as gv
 from scraibe import Transcript
+from scraibe.app.stg import GradioTranscriptionInterface
+import threading
 
 def select_task(choice):
         # tell the app that it is still in use
@@ -86,9 +88,16 @@ def run_scraibe(task,
     
     # get *args which are not None 
     
-    pipe = gv.MODEL
+    if gv.MODEL is None and gv.MODEL_THREAD_PARAMS is not None:
+        progress(0, desc='Model was not loaded to conserve resources. Loading model...')
+        time.sleep(1)
+        gv.MODEL_THREAD = threading.Thread(**gv.MODEL_THREAD_PARAMS)
+        gv.MODEL_THREAD.start()
+        gv.MODEL_THREAD.join()
       
-    progress(0, desc='Starting task...')
+    pipe = GradioTranscriptionInterface()
+        
+    progress(0.1, desc='Starting task...')
     source = audio1 or audio2 or video1 or video2 or file_in
     
     if isinstance(source, list):

scraibe/app/interface.py

@@ -9,8 +9,6 @@ import scraibe.app.global_var as gv
 from .interactions import *
 from .stg import *
 
-from scraibe import Scraibe
-
 theme = gr.themes.Soft(
     primary_hue="green",
     secondary_hue='orange',
@@ -36,10 +34,7 @@ LANGUAGES = [
 CURRENT_PATH = os.path.dirname(os.path.realpath(__file__))
 
 
-def gradio_Interface(pipe : Scraibe = None):
+def gradio_Interface():
-    
-    if pipe is not None:
-        gv.MODEL = GradioTranscriptionInterface(pipe)
     
     with gr.Blocks(theme=theme,title='ScrAIbe: Automatic Audio Transcription') as demo:
             

scraibe/app/multi.py

@@ -0,0 +1,44 @@
+"""
+This file contains the functions which are related to monitoring the actual app usage. 
+Therefore, the app is to be more efficient in the usage of the resources. 
+By for example, unloading or reloading the model.
+"""
+
+import time
+import gc
+from typing import Union
+import torch
+
+import scraibe.app.global_var as gv
+from scraibe.autotranscript import Scraibe 
+
+
+def load_model_thread(model : Union[Scraibe, dict] = None):
+    if model is None:
+        gv.MODEL = Scraibe()
+    elif type(model) is Scraibe:
+        gv.MODEL = model
+    elif type(model) is dict:
+        gv.MODEL = Scraibe(**model)
+    else:
+        raise TypeError("model must be of type Scraibe, or dict")
+
+    gv.LAST_USED = time.time()
+
+# Create a thread to monitor user activity
+def delete_unused_model():
+    while True:
+        
+        _unload_porperty = (not gv.TRANSCRIBE_ACTIVE.is_set() and (time.time() - gv.LAST_USED > gv.TIMEOUT) and gv.MODEL is not None)
+
+        if _unload_porperty:
+            
+            del gv.MODEL
+            gv.MODEL = None
+            
+            gc.collect()
+            torch.cuda.empty_cache()
+
+            gv.MODEL_THREAD.join()
+            
+        time.sleep(int(gv.TIMEOUT/5))

scraibe/app/stg.py

@@ -9,7 +9,8 @@ It makes adds gradio interactions to the scraibe class in the back.
 import json
 import gradio as gr
 from tqdm import tqdm
-from scraibe import Scraibe
+
+import scraibe.app.global_var as gv
 
 
 class GradioTranscriptionInterface:
@@ -17,14 +18,14 @@ class GradioTranscriptionInterface:
     Interface handling the interaction between Gradio UI and the Audio Transcription system.
     """
 
-    def __init__(self, model: Scraibe):
+    def __init__(self):
         """
         Initializes the GradioTranscriptionInterface with a transcription model.
 
         Args:
             model (Scraibe): Model responsible for audio transcription tasks.
         """
-        self.model = model
+        self.model = gv.MODEL
 
     def auto_transcribe(self, source,
                         num_speakers : int,
@@ -37,6 +38,8 @@ class GradioTranscriptionInterface:
             tuple: Transcribed text (str), JSON output (dict)
         """
         
+        gv.TRANSCRIBE_ACTIVE.set()
+        
         kwargs = {
             "num_speakers": num_speakers if num_speakers != 0 else None,
             "language": language if language != "None" else None,
@@ -46,9 +49,11 @@ class GradioTranscriptionInterface:
             try:
                 result = self.model.autotranscribe(source, **kwargs)
             except ValueError:
+                gv.TRANSCRIBE_ACTIVE.clear()
                 raise gr.Error("Couldn't detect any speech in the provided audio. \
                         Please try again!")
     
+            gv.TRANSCRIBE_ACTIVE.clear()
             return str(result), result.get_json()
         
         elif isinstance(source, list):
@@ -75,9 +80,13 @@ class GradioTranscriptionInterface:
                 else:
                     out_dict[source_names[i]] = r.get_dict()
              
+            
+            gv.TRANSCRIBE_ACTIVE.clear()
+              
             return out, json.dumps(out_dict, indent=4)
         
         else:
+            gv.TRANSCRIBE_ACTIVE.clear()
             raise gr.Error("Please provide a valid audio file.")
 
 
@@ -88,6 +97,9 @@ class GradioTranscriptionInterface:
         Returns:
             str: Transcribed text.
         """
+        
+        gv.TRANSCRIBE_ACTIVE.set()
+        
         kwargs = {
             "language": language if language != "None" else None,
             "task": 'translate' if translation == "Yes" else None
@@ -95,7 +107,7 @@ class GradioTranscriptionInterface:
     
         if isinstance(source, str):
             result = self.model.transcribe(source, **kwargs)
-            
+            gv.TRANSCRIBE_ACTIVE.clear()
             return str(result)
         
         elif isinstance(source, list):
@@ -111,9 +123,12 @@ class GradioTranscriptionInterface:
                 out += str(res)
                 out += "\n\n"
             
+            gv.TRANSCRIBE_ACTIVE.clear()
+            
             return out
         
         else:
+            gv.TRANSCRIBE_ACTIVE.clear()
             raise gr.Error("Please provide a valid audio file.")
 
     def perform_diarisation(self, source, num_speakers):
@@ -123,6 +138,9 @@ class GradioTranscriptionInterface:
         Returns:
             str: JSON output of diarisation result.
         """
+        
+        gv.TRANSCRIBE_ACTIVE.set()
+        
         kwargs = {
             "num_speakers": num_speakers if num_speakers != 0 else None,
         }
@@ -131,9 +149,10 @@ class GradioTranscriptionInterface:
             try:
                 result = self.model.diarization(source, **kwargs)
             except ValueError:
+                gv.TRANSCRIBE_ACTIVE.clear()
                 raise gr.Error("Couldn't detect any speech in the provided audio. \
                         Please try again!")
-        
+            gv.TRANSCRIBE_ACTIVE.clear()
             return json.dumps(result, indent=2)
         elif isinstance(source, list):
             source_names = [s.split("/")[-1] for s in source]
@@ -142,6 +161,7 @@ class GradioTranscriptionInterface:
                 try:
                     res = self.model.diarization(s, **kwargs)
                 except ValueError:
+    
                     res = f"NO DIARISATION FOUND FOR {s}"
                     gr.Warning(f"Couldn't detect any speech in {s} will skip this file.")
                 result.append(res)
@@ -151,7 +171,10 @@ class GradioTranscriptionInterface:
             for i, res in enumerate(result):
                 out[source_names[i]] = res
             
+            gv.TRANSCRIBE_ACTIVE.clear()    
+            
             return json.dumps(out, indent=4)
         
         else:
+            gv.TRANSCRIBE_ACTIVE.clear()
             gr.Error("Please provide a valid audio file.")