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import requests | |
import pytz | |
import streamlit as st | |
import os | |
from datetime import datetime | |
from audio_recorder_streamlit import audio_recorder | |
# Filepath for saving the text | |
file_path = 'text_output.txt' | |
API_URL = 'https://tonpixzfvq3791u9.us-east-1.aws.endpoints.huggingface.cloud' | |
headers = { | |
"Authorization": "Bearer XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX", | |
"Content-Type": "audio/wav" | |
} | |
def query(filename): | |
with open(filename, "rb") as f: | |
data = f.read | |
#try: | |
response = requests.post(API_URL, headers=headers, data=data) | |
#except: | |
# st.write('Whisper Voice Speech to Text Model is asleep. Starting up now on T4 - please give 3 minutes then retry as KEDA scales up from zero to activate running container(s).') | |
return response.json() | |
def generate_filename(prompt, file_type): | |
central = pytz.timezone('US/Central') | |
safe_date_time = datetime.now(central).strftime("%m%d_%H%M") | |
replaced_prompt = prompt.replace(" ", "_").replace("\n", "_") | |
safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:90] | |
return f"{safe_date_time}_{safe_prompt}.{file_type}" | |
def save_and_play_audio(audio_recorder): | |
audio_bytes = audio_recorder() | |
if audio_bytes: | |
filename = generate_filename("Recording", "wav") | |
with open(filename, 'wb') as f: | |
f.write(audio_bytes) | |
st.audio(audio_bytes, format="audio/wav") | |
return filename | |
def transcribe_audio(filename): | |
output = query(filename) | |
return output | |
def save_transcription(transcription): | |
with open(file_path, 'a') as f: | |
f.write(f"{transcription}\n") | |
def load_previous_transcriptions(): | |
if os.path.exists(file_path): | |
with open(file_path, 'r') as f: | |
return f.read() | |
return "" | |
def main(): | |
st.title("Speech to Text π€π") | |
st.write("Record your speech and get the text. π¨οΈ") | |
previous_transcriptions = load_previous_transcriptions() | |
text_area = st.text_area("Transcriptions:", previous_transcriptions, height=400) | |
filename = save_and_play_audio(audio_recorder) | |
if filename is not None: | |
try: | |
transcription = transcribe_audio(filename) | |
# Update the text area with new transcription | |
updated_transcriptions = f"{previous_transcriptions}\n{transcription}" | |
st.text_area("Transcriptions:", updated_transcriptions, height=400) | |
# Save the new transcription to file | |
save_transcription(transcription) | |
except: | |
st.write('Whisperer loading..') | |
if __name__ == "__main__": | |
main() | |