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| import base64 | |
| import streamlit as st | |
| import os | |
| import openai | |
| from dotenv import load_dotenv | |
| from gtts import gTTS | |
| import textwrap | |
| # Function to accept OpenAI API Key as input from the user | |
| def get_api_key(): | |
| """Prompt the user for their OpenAI API Key.""" | |
| api_key = st.text_input("Enter your OpenAI API Key", type="password") | |
| if api_key: | |
| openai.api_key = api_key | |
| return api_key | |
| else: | |
| return None | |
| def speech_to_text(audio_data): | |
| """Transcribes audio data to text using OpenAI's API.""" | |
| with open(audio_data, "rb") as audio_file: | |
| transcript = openai.Audio.transcribe( | |
| model="whisper-1", # Ensure the model is correct | |
| file=audio_file | |
| ) | |
| return transcript["text"] # Extract the text from the response | |
| def text_to_speech(input_text): | |
| """Generates a TTS audio file from the input text.""" | |
| # Split the text into manageable chunks | |
| chunks = textwrap.wrap(input_text, 1000) # Wrap at 1000 characters | |
| audio_file_paths = [] | |
| for i, chunk in enumerate(chunks): | |
| tts = gTTS(text=chunk, lang="en") | |
| audio_file_path = f"temp_audio_play_{i}.mp3" | |
| tts.save(audio_file_path) | |
| audio_file_paths.append(audio_file_path) | |
| return audio_file_paths # Return a list of file paths | |
| def autoplay_audio(file_paths: list): | |
| """Automatically plays audio from the provided file paths.""" | |
| for file_path in file_paths: | |
| with open(file_path, "rb") as f: | |
| data = f.read() | |
| b64 = base64.b64encode(data).decode("utf-8") | |
| md = f""" | |
| <audio autoplay> | |
| <source src="data:audio/mp3;base64,{b64}" type="audio/mp3"> | |
| </audio> | |
| """ | |
| st.markdown(md, unsafe_allow_html=True) | |