Make cache path configurable to save auto converted ct2 models

Signed-off-by: makaveli10 <vineet.suryan@collabora.com>

README.md

@@ -44,10 +44,11 @@ The server supports 3 backends `faster_whisper`, `tensorrt` and `openvino`. If r
 python3 run_server.py --port 9090 \
                       --backend faster_whisper
   
-# running with custom model
+# running with custom model and cache_dir to save auto-converted ctranslate2 models
 python3 run_server.py --port 9090 \
                       --backend faster_whisper \
                       -fw "/path/to/custom/faster/whisper/model"
+                      -c ~/.cache/whisper-live/
 ```
 
 - TensorRT backend. Currently, we recommend to only use the docker setup for TensorRT. Follow [TensorRT_whisper readme](https://github.com/collabora/WhisperLive/blob/main/TensorRT_whisper.md) which works as expected. Make sure to build your TensorRT Engines before running the server with TensorRT backend.

run_server.py

@@ -31,6 +31,10 @@ if __name__ == "__main__":
     parser.add_argument('--no_single_model', '-nsm',
                         action='store_true',
                         help='Set this if every connection should instantiate its own model. Only relevant for custom model, passed using -trt or -fw.')
+    parser.add_argument('--cache_path', '-c',
+                        type=str,
+                        default="~/.cache/whisper-live/",
+                        help='Path to cache the converted ctranslate2 models.')
     args = parser.parse_args()
 
     if args.backend == "tensorrt":
@@ -51,4 +55,5 @@ if __name__ == "__main__":
         trt_multilingual=args.trt_multilingual,
         trt_py_session=args.trt_py_session,
         single_model=not args.no_single_model,
+        cache_path=args.cache_path
     )

whisper_live/backend/faster_whisper_backend.py

@@ -31,6 +31,7 @@ class ServeClientFasterWhisper(ServeClientBase):
         no_speech_thresh=0.45,
         clip_audio=False,
         same_output_threshold=10,
+        cache_path="~/.cache/whisper-live/"
     ):
         """
         Initialize a ServeClient instance.
@@ -61,6 +62,7 @@ class ServeClientFasterWhisper(ServeClientBase):
             clip_audio,
             same_output_threshold,
         )
+        self.cache_path = cache_path
         self.model_sizes = [
             "tiny", "tiny.en", "base", "base.en", "small", "small.en",
             "medium", "medium.en", "large-v2", "large-v3", "distil-small.en",
@@ -140,7 +142,7 @@ class ServeClientFasterWhisper(ServeClientBase):
                 if ctranslate2.contains_model(local_snapshot):
                     model_to_load = local_snapshot
                 else:
-                    cache_root = os.path.expanduser("~/.cache/whisper-live/whisper-ct2-models/")
+                    cache_root = os.path.expanduser(os.path.join(self.cache_path, "whisper-ct2-models/"))
                     os.makedirs(cache_root, exist_ok=True)
                     safe_name = model_ref.replace("/", "--")
                     ct2_dir = os.path.join(cache_root, safe_name)

whisper_live/server.py

@@ -233,6 +233,7 @@ class TranscriptionServer:
                     no_speech_thresh=options.get("no_speech_thresh", 0.45),
                     clip_audio=options.get("clip_audio", False),
                     same_output_threshold=options.get("same_output_threshold", 10),
+                    cache_path=self.cache_path,
                 )
 
                 logging.info("Running faster_whisper backend.")
@@ -369,7 +370,8 @@ class TranscriptionServer:
             whisper_tensorrt_path=None,
             trt_multilingual=False,
             trt_py_session=False,
-            single_model=False):
+            single_model=False,
+            cache_path="~/.cache/whisper-live/"):
         """
         Run the transcription server.
 
@@ -377,6 +379,7 @@ class TranscriptionServer:
             host (str): The host address to bind the server.
             port (int): The port number to bind the server.
         """
+        self.cache_path = cache_path
         if faster_whisper_custom_model_path is not None and not os.path.exists(faster_whisper_custom_model_path):
             raise ValueError(f"Custom faster_whisper model '{faster_whisper_custom_model_path}' is not a valid path.")
         if whisper_tensorrt_path is not None and not os.path.exists(whisper_tensorrt_path):