update app.py

app.py

@@ -21,46 +21,36 @@ if LANGUAGE not in SUPPORTED_LANGUAGES:
 else:
     MODEL_PATH = MODEL_PATHS[LANGUAGE]
 
-@spaces.GPU
-def init_pipeline():
-    return pipeline(
-    "automatic-speech-recognition",
-    model=MODEL_PATH,
-    device=0 if torch.cuda.is_available() else -1,
-    chunk_length_s=30,
-    stride_length_s=(4, 2),
-    batch_size=8,
-    token=os.getenv("HF_TOKEN"),
-)
-
-wave2vec_pipeline = init_pipeline()
-
+_asr_pipeline = None
 
+@spaces.GPU
 def transcribe_gradio(audio_path: str | None) -> str:
-    """
-    Transcribe an uploaded or recorded audio file and report inference time.
-
-    Args:
-        audio_path: Local filesystem path to the audio file provided by Gradio;
-                    None or empty if the user hasn't recorded/uploaded anything.
-
-    Returns:
-        A string containing either:
-          - A warning if no file was provided,
-          - An error message if loading/decoding failed,
-          - Or the transcript followed by the elapsed inference time.
-    """
     if not audio_path:
         return "⚠️  Please record something or choose a file first."
 
+    global _asr_pipeline
+
+    if _asr_pipeline is None:
+
+        _asr_pipeline = pipeline(
+            "automatic-speech-recognition",
+            model=MODEL_PATH,
+            device=0 if torch.cuda.is_available() else -1,
+            chunk_length_s=30,
+            stride_length_s=(4, 2),
+            batch_size=8,
+            token=os.getenv("HF_TOKEN"),
+        )
+
     start = time.time()
     try:
-        transcript = utils.transcribe_file(audio_path, wave2vec_pipeline)
-    except ValueError as err:
+        result = _asr_pipeline(audio_path)
+        transcript = result["text"] if isinstance(result, dict) else str(result)
+    except Exception as err:
         return f"❌ {err}"
     runtime = time.time() - start
-    return f"{transcript}\n\n⌛ Inference time: {runtime:.2f} s"
 
+    return f"{transcript}\n\n⌛ Inference time: {runtime:.2f} s"
 
 # gradio interface
 with gr.Blocks(title="Wave2Vec (Luxembourgish) ", theme="soft", css=CUSTOM_CSS) as demo: