from transformers import AutoProcessor, CohereAsrForConditionalGeneration
from transformers.audio_utils import load_audio
from huggingface_hub import hf_hub_download

# Load model
print("Loading model...")
processor = AutoProcessor.from_pretrained("CohereLabs/cohere-transcribe-03-2026")
model = CohereAsrForConditionalGeneration.from_pretrained(
    "CohereLabs/cohere-transcribe-03-2026",
    device_map="auto"
)

def transcribe_audio(audio, language="en"):
    inputs = processor(audio, sampling_rate=16000, return_tensors="pt", language=language)
    inputs.to(model.device, dtype=model.dtype)
    
    outputs = model.generate(**inputs, max_new_tokens=256)
    text = processor.decode(outputs, skip_special_tokens=True)
    return text

# Use demo audio file from Hugging Face
print("Loading demo audio...")
audio_file = hf_hub_download(
    repo_id="CohereLabs/cohere-transcribe-03-2026",
    filename="demo/voxpopuli_test_en_demo.wav",
)
audio = load_audio(audio_file, sampling_rate=16000)

print("Transcribing...")
text = transcribe_audio(audio)
print(f"\nTranscription:\n{text}\n")