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| # # import os | |
| # # import streamlit as st | |
| # # from pydub import AudioSegment | |
| # # from groq import Groq | |
| # # # Set ffmpeg path | |
| # # ffmpeg_path = r"ffmpeg.exe" | |
| # # os.environ["PATH"] += os.pathsep + os.path.dirname(ffmpeg_path) | |
| # # AudioSegment.converter = ffmpeg_path | |
| # # # Groq API configuration | |
| # # groq_api_key = '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' # Replace with your actual API key | |
| # # client = Groq(api_key=groq_api_key) | |
| # # model = 'whisper-large-v3' | |
| # # # Function to ensure the file is in a suitable format | |
| # # def ensure_suitable_format(file_path): | |
| # # allowed_formats = ["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"] | |
| # # file_extension = file_path.split('.')[-1].lower() | |
| # # if file_extension not in allowed_formats: | |
| # # new_file_path = f"{os.path.splitext(file_path)[0]}.wav" | |
| # # os.rename(file_path, new_file_path) | |
| # # return new_file_path | |
| # # return file_path | |
| # # # Function to convert audio to WAV | |
| # # def convert_audio_to_wav(input_path, output_path): | |
| # # audio = AudioSegment.from_file(input_path) | |
| # # audio.export(output_path, format="wav") | |
| # # return output_path | |
| # # # Function to transcribe audio using Groq | |
| # # def audio_to_text(filepath): | |
| # # with open(filepath, "rb") as file: | |
| # # translation = client.audio.translations.create( | |
| # # file=(filepath, file.read()), | |
| # # model=model, | |
| # # ) | |
| # # return translation.text | |
| # # # Streamlit App UI | |
| # # st.title("Audio-to-Text Transcription") | |
| # # st.write("Upload an audio file to get the transcribed text.") | |
| # # # File upload | |
| # # uploaded_file = st.file_uploader("Upload your audio file", type=["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"]) | |
| # # if uploaded_file: | |
| # # # Save the uploaded file locally | |
| # # file_path = os.path.join("uploaded_audio", uploaded_file.name) | |
| # # os.makedirs("uploaded_audio", exist_ok=True) | |
| # # with open(file_path, "wb") as f: | |
| # # f.write(uploaded_file.getbuffer()) | |
| # # st.write(f"File uploaded: {uploaded_file.name}") | |
| # # # Ensure file format is suitable | |
| # # suitable_audio_path = ensure_suitable_format(file_path) | |
| # # # Convert audio to WAV | |
| # # wav_path = f"{os.path.splitext(suitable_audio_path)[0]}.wav" | |
| # # converted_audio = convert_audio_to_wav(suitable_audio_path, wav_path) | |
| # # # Transcribe audio | |
| # # st.write("Processing transcription...") | |
| # # try: | |
| # # transcription = audio_to_text(converted_audio) | |
| # # st.success("Transcription complete!") | |
| # # st.text_area("Transcribed Text", transcription, height=200) | |
| # # except Exception as e: | |
| # # st.error(f"Error during transcription: {e}") | |
| # from pydub import AudioSegment | |
| # from groq import Groq | |
| # import os | |
| # import streamlit as st | |
| # # Groq API configuration | |
| # groq_api_key = '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' # Replace with your actual API key | |
| # client = Groq(api_key=groq_api_key) | |
| # model = 'whisper-large-v3' | |
| # # Function to ensure the file is in a suitable format | |
| # def ensure_suitable_format(file_path): | |
| # allowed_formats = ["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"] | |
| # file_extension = file_path.split('.')[-1].lower() | |
| # if file_extension not in allowed_formats: | |
| # new_file_path = f"{os.path.splitext(file_path)[0]}.wav" | |
| # os.rename(file_path, new_file_path) | |
| # return new_file_path | |
| # return file_path | |
| # # Function to convert audio to WAV | |
| # def convert_audio_to_wav(input_path, output_path): | |
| # audio = AudioSegment.from_file(input_path) | |
| # audio.export(output_path, format="wav") | |
| # return output_path | |
| # # Function to transcribe audio using Groq | |
| # def audio_to_text(filepath): | |
| # with open(filepath, "rb") as file: | |
| # translation = client.audio.translations.create( | |
| # file=(filepath, file.read()), | |
| # model=model, | |
| # ) | |
| # return translation.text | |
| # # Streamlit App UI | |
| # st.title("Audio-to-Text Transcription") | |
| # st.write("Upload an audio file to get the transcribed text.") | |
| # # File upload | |
| # uploaded_file = st.file_uploader("Upload your audio file", type=["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"]) | |
| # if uploaded_file: | |
| # # Save the uploaded file locally | |
| # file_path = os.path.join("uploaded_audio", uploaded_file.name) | |
| # os.makedirs("uploaded_audio", exist_ok=True) | |
| # with open(file_path, "wb") as f: | |
| # f.write(uploaded_file.getbuffer()) | |
| # st.write(f"File uploaded: {uploaded_file.name}") | |
| # # Ensure file format is suitable | |
| # suitable_audio_path = ensure_suitable_format(file_path) | |
| # # Convert audio to WAV | |
| # wav_path = f"{os.path.splitext(suitable_audio_path)[0]}.wav" | |
| # converted_audio = convert_audio_to_wav(suitable_audio_path, wav_path) | |
| # # Transcribe audio | |
| # st.write("Processing transcription...") | |
| # try: | |
| # transcription = audio_to_text(converted_audio) | |
| # st.success("Transcription complete!") | |
| # st.text_area("Transcribed Text", transcription, height=200) | |
| # except Exception as e: | |
| # st.error(f"Error during transcription: {e}") | |
| import os | |
| import streamlit as st | |
| from pydub import AudioSegment | |
| from groq import Groq | |
| # Function to ensure the file is in a suitable format | |
| def ensure_suitable_format(file_path): | |
| allowed_formats = ["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"] | |
| file_extension = file_path.split('.')[-1].lower() | |
| if file_extension not in allowed_formats: | |
| new_file_path = f"{os.path.splitext(file_path)[0]}.wav" | |
| os.rename(file_path, new_file_path) | |
| return new_file_path | |
| return file_path | |
| # Function to convert audio to WAV | |
| def convert_audio_to_wav(input_path, output_path): | |
| audio = AudioSegment.from_file(input_path) | |
| audio.export(output_path, format="wav") | |
| return output_path | |
| # Function to transcribe audio using Groq | |
| def audio_to_text(filepath, groq_api_key): | |
| client = Groq(api_key=groq_api_key) | |
| model = 'whisper-large-v3' | |
| with open(filepath, "rb") as file: | |
| translation = client.audio.translations.create( | |
| file=(filepath, file.read()), | |
| model=model, | |
| ) | |
| return translation.text | |
| # Streamlit App UI | |
| st.title("Audio-to-Text Transcription") | |
| st.write("Upload an audio file to get the transcribed text.") | |
| # Input for API key | |
| groq_api_key = st.text_input("Enter your Groq API Key", type="password") | |
| # File upload | |
| uploaded_file = st.file_uploader("Upload your audio file", type=["flac", "mp3", "mp4", "mpeg", "mpga", "m4a", "ogg", "opus", "wav", "webm"]) | |
| if groq_api_key and uploaded_file: | |
| # Save the uploaded file locally | |
| file_path = os.path.join("uploaded_audio", uploaded_file.name) | |
| os.makedirs("uploaded_audio", exist_ok=True) | |
| with open(file_path, "wb") as f: | |
| f.write(uploaded_file.getbuffer()) | |
| st.write(f"File uploaded: {uploaded_file.name}") | |
| # Ensure file format is suitable | |
| suitable_audio_path = ensure_suitable_format(file_path) | |
| # Convert audio to WAV | |
| wav_path = f"{os.path.splitext(suitable_audio_path)[0]}.wav" | |
| converted_audio = convert_audio_to_wav(suitable_audio_path, wav_path) | |
| # Transcribe audio | |
| st.write("Processing transcription...") | |
| try: | |
| transcription = audio_to_text(converted_audio, groq_api_key) | |
| st.success("Transcription complete!") | |
| st.text_area("Transcribed Text", transcription, height=200) | |
| except Exception as e: | |
| st.error(f"Error during transcription: {e}") | |
| elif not groq_api_key: | |
| st.warning("Please enter your Groq API Key to proceed.") | |