app.py

import streamlit as st
import whisper
from tempfile import NamedTemporaryFile
import ffmpeg


st.title("MinuteBot App")

# upload audio file with streamlit
audio_file = st.file_uploader("Unggah Meeting Audio", type=["mp3", "wav", "m4a"])

# model = whisper.load_model("base") # loading the base model
st.text("MinuteBot Model telah dimuat:")

def load_whisper_model():

    return model

    
if st.sidebar.button("Transkripsikan Audio"):
    if audio_file is not None:
        with NamedTemporaryFile() as temp:
            temp.write(audio_file.getvalue())
            temp.seek(0)
            model = whisper.load_model("large")
            result = model.transcribe(temp.name)
            st.write(result["text"])
        
st.sidebar.header("Putar Berkas Audio")
st.sidebar.audio(audio_file)

# import streamlit as st
# from tempfile import NamedTemporaryFile
# import ffmpeg
# from transformers import Wav2Vec2ForCTC, Wav2Vec2Tokenizer
# import librosa

# # HF_TOKEN = os.environ.get("HUGGINGFACEHUB_API_TOKEN")

# st.title("TemplarX-Medium-Indonesian Transcription App")
# st.text("Model Whisper (TemplarX-medium-Indonesian) telah dimuat:")

# def load_whisper_model():
#     model_name = "jonnatakusuma/TemplarX-medium-Indonesian"
#     tokenizer = Wav2Vec2Tokenizer.from_pretrained(model_name)
#     model = Wav2Vec2ForCTC.from_pretrained(model_name, use_auth_token=True)
#     return tokenizer, model

# audio_file = st.file_uploader("Unggah Meeting Audio", type=["mp3", "wav", "m4a"])

# if st.sidebar.button("Transkripsikan Audio"):
#     if audio_file is not None:
#         with NamedTemporaryFile() as temp:
#             temp.write(audio_file.read())
#             temp.seek(0)
#             tokenizer, model = load_whisper_model()
#             # Read the audio file and transcribe using the fine-tuned model
#             audio_path = temp.name
#             audio_input, _ = librosa.load(audio_path, sr=16000)
#             transcription = model.stt(text)
#             st.write(transcription)

# st.sidebar.header("Putar Berkas Audio")
# st.sidebar.audio(audio_file, format='audio/wav')