Update app.py

app.py

@@ -14,7 +14,7 @@ app = FastAPI()
 device = 0 if torch.cuda.is_available() else -1
 
 # Load Whisper model and processor
-model_name = "openai/whisper-large-v2"  # You can change to other variants like "openai/whisper-small"
+model_name = "openai/whisper-large-v2"  # Use the model of your choice, e.g., whisper-small or whisper-large
 model = WhisperForConditionalGeneration.from_pretrained(model_name)
 processor = WhisperProcessor.from_pretrained(model_name)
 
@@ -27,8 +27,9 @@ asr_pipeline = pipeline(
     "automatic-speech-recognition",
     model=model,
     tokenizer=processor.tokenizer,  # Explicitly set the tokenizer from the processor
-    feature_extractor=processor.feature_extractor,  # Also set the feature extractor
-    device=device
+    feature_extractor=processor.feature_extractor,  # Set the feature extractor for audio input
+    device=device,
+    language="portuguese"  # Add language explicitly in the pipeline to force Portuguese
 )