Switched large model to v3-turbo

AutoSubs-App/src/GlobalContext.tsx

@@ -234,7 +234,7 @@ export function GlobalProvider({ children }: React.PropsWithChildren<{}>) {
                     } else {
                         console.log(`Transcription Server INFO: "${line}"`);
                     }
-                } else if (line.includes("model.bin:")) {
+                } else if (line.includes("model.bin:") || line.includes("weights.safetensors:")) {
                     const percentageMatch = line.match(/(\d+)%/);
                     if (percentageMatch && percentageMatch[1]) {
                         const percentage = parseInt(percentageMatch[1], 10);

AutoSubs-App/src/pages/home-page.tsx

@@ -1,4 +1,5 @@
-import { useState } from "react"
+import { useState } from "react";
+import { platform } from '@tauri-apps/plugin-os';
 import { cn } from "@/lib/utils"
 import {
     Bird,
@@ -605,7 +606,7 @@ export function HomePage() {
                                                     <p>
                                                         Whisper{" "}
                                                         <span className="font-medium text-foreground">
-                                                            Large-V3
+                                                            Large
                                                         </span>
                                                     </p>
                                                     <p className="text-xs" data-description>
@@ -683,18 +684,21 @@ export function HomePage() {
                                     <Input value={maxChars} id="maxChars" type="number" placeholder="30" onChange={(e) => setMaxChars(Math.abs(Number.parseInt(e.target.value)))} />
                                 </div>
                             </div>
-                            <div className="flex items-center space-x-4 rounded-md border p-4">
-                                <Pickaxe className="w-5" />
-                                <div className="flex-1 space-y-1">
-                                    <p className="text-sm font-medium leading-none">
-                                        Force Align Words
-                                    </p>
-                                    <p className="text-xs text-muted-foreground">
-                                        Improve word level timing
-                                    </p>
+
+                            {platform() === 'windows' && (
+                                <div className="flex items-center space-x-4 rounded-md border p-4">
+                                    <Pickaxe className="w-5" />
+                                    <div className="flex-1 space-y-1">
+                                        <p className="text-sm font-medium leading-none">
+                                            Force Align Words
+                                        </p>
+                                        <p className="text-xs text-muted-foreground">
+                                            Improve word level timing
+                                        </p>
+                                    </div>
+                                    <Switch checked={alignWords} onCheckedChange={(checked) => setAlignWords(checked)} />
                                 </div>
-                                <Switch checked={alignWords} onCheckedChange={(checked) => setAlignWords(checked)} />
-                            </div>
+                            )}
 
                         </CardContent>
                     </Card>

Transcription-Server/server.py

@@ -71,6 +71,7 @@ def __getattr__(self, attr):
 
 from huggingface_hub import HfApi, HfFolder, login, snapshot_download
 from huggingface_hub.utils import RepositoryNotFoundError, HfHubHTTPError
+import torch
 
 if getattr(sys, 'frozen', False):
     base_path = sys._MEIPASS
@@ -106,27 +107,34 @@ def __getattr__(self, attr):
     "base": "base",
     "small": "small",
     "medium": "medium",
-    "large": "large-v3",
+    "large": "large-v3-turbo",
     "tiny.en": "tiny.en",
     "base.en": "base.en",
     "small.en": "small.en",
     "medium.en": "medium.en",
-    "large.en": "large-v3",
+    "large.en": "large-v3-turbo",
 }
 
 mac_models = {
     "tiny": "mlx-community/whisper-tiny-mlx",
     "base": "mlx-community/whisper-base-mlx-q4",
     "small": "mlx-community/whisper-small-mlx",
     "medium": "mlx-community/whisper-medium-mlx",
-    "large": "mlx-community/distil-whisper-large-v3",
+    "large": "mlx-community/whisper-large-v3-turbo",
     "tiny.en": "mlx-community/whisper-tiny.en-mlx",
     "base.en": "mlx-community/whisper-base.en-mlx",
     "small.en": "mlx-community/whisper-small.en-mlx",
     "medium.en": "mlx-community/whisper-medium.en-mlx",
-    "large.en": "mlx-community/distil-whisper-large-v3",
+    "large.en": "mlx-community/whisper-large-v3-turbo",
+    "large.de": "mlx-community/whisper-large-v3-turbo-german-f16",
 }
 
+def sanitize_result(result):
+    # Convert the result to a JSON string
+    result_json = json.dumps(result, default=lambda o: None)
+    # Parse the JSON string back to a dictionary
+    sanitized_result = json.loads(result_json)
+    return sanitized_result
 
 def is_model_cached_locally(model_id, revision=None):
     try:
@@ -227,7 +235,6 @@ def transcribe_audio(audio_file, kwargs, max_words, max_chars, sensitive_words):
     else:
         result = stable_whisper.transcribe_any(
             inference, audio_file, inference_kwargs=kwargs, vad=False, regroup=True)
-        result.pad()
 
     result = modify_result(result, max_words, max_chars, sensitive_words)
 
@@ -429,18 +436,6 @@ class TranscriptionRequest(BaseModel):
 async def transcribe(request: TranscriptionRequest):
     try:
         start_time = time.time()
-        if request.language == "en":
-            request.model = request.model + ".en"
-            task = "transcribe"
-        else:
-            task = request.task
-
-        if platform.system() == 'Windows':
-            model = win_models[request.model]
-        else:
-            model = mac_models[request.model]
-
-        print(model)
 
         file_path = request.file_path
         timeline = request.timeline
@@ -457,15 +452,6 @@ async def transcribe(request: TranscriptionRequest):
         else:
             print(f"Processing file: {file_path}")
 
-        import torch
-        kwargs = {
-            "model": model,
-            "task": task,
-            "language": request.language,
-            "align_words": request.align_words,
-            "device": "cuda" if torch.cuda.is_available() else "cpu"
-        }
-
         # Select device
         if torch.cuda.is_available():
             device = torch.device("cuda")
@@ -476,6 +462,29 @@ async def transcribe(request: TranscriptionRequest):
 
         print(f"Using device: {device}")
 
+        if request.language == "en":
+            request.model = request.model + ".en"
+            task = "transcribe"
+        elif request.language == "de" and request.model == "large" and platform.system() != 'Windows':
+            request.model = request.model + ".de"
+        else:
+            task = request.task
+
+        if platform.system() == 'Windows':
+            model = win_models[request.model]
+        else:
+            model = mac_models[request.model]
+
+        print(model)
+
+        kwargs = {
+            "model": model,
+            "task": task,
+            "language": request.language,
+            "align_words": request.align_words,
+            "device": "cuda" if torch.cuda.is_available() else "cpu"
+        }
+
         # Process audio (transcription and optionally diarization)
         try:
             result = await process_audio(
@@ -498,7 +507,7 @@ async def transcribe(request: TranscriptionRequest):
 
             # Save the transcription to a JSON file
             with open(json_filepath, 'w', encoding='utf-8') as f:
-                json.dump(result, f, indent=4, ensure_ascii=False)
+                json.dump(sanitize_result(result), f, indent=4, ensure_ascii=False)
 
             print(f"Transcription saved to: {json_filepath}")
         except Exception as e: