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import streamlit as st
import hmac
import os
from helpers import text_to_speech, autoplay_audio, speech_to_text, get_api_key
from generate_answer import base_model_chatbot, with_pdf_chatbot
from audio_recorder_streamlit import audio_recorder
from streamlit_float import *
from PIL import Image
# Display image/logo in the "Course Query Assistant" section (optional)
voice = Image.open("8090687.png") # Ensure the file is in the correct directory
st.image(voice, width=150) # Adjust the size as per preference
def main(answer_mode: str):
# Float feature initialization
float_init()
# Prompt for API key
api_key = get_api_key()
if not api_key:
st.error("You must provide a valid OpenAI API Key to proceed.")
st.stop()
def initialize_session_state():
if "messages" not in st.session_state:
st.session_state.messages = [
{"role": "assistant", "content": "Hi! How may I assist you today? (Please Speak Clearly)"}
]
initialize_session_state()
st.title("OpenAI Conversational Chatbot 🤖")
# Create footer container for the microphone
footer_container = st.container()
with footer_container:
audio_bytes = audio_recorder()
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.write(message["content"])
if audio_bytes:
# Write the audio bytes to a file
with st.spinner("Transcribing..."):
webm_file_path = "temp_audio.mp3"
with open(webm_file_path, "wb") as f:
f.write(audio_bytes)
transcript = speech_to_text(webm_file_path)
if transcript:
st.session_state.messages.append({"role": "user", "content": transcript})
with st.chat_message("user"):
st.write(transcript)
os.remove(webm_file_path)
if st.session_state.messages[-1]["role"] != "assistant":
with st.chat_message("assistant"):
with st.spinner("Thinking🤔..."):
if answer_mode == 'base_model':
final_response = base_model_chatbot(st.session_state.messages)
elif answer_mode == 'pdf_chat':
final_response = with_pdf_chatbot(st.session_state.messages)
# Add final check for punctuation and completeness
if not final_response.strip()[-1] in ".!?":
final_response += " This is the end of the response. Let me know if you need anything else."
with st.spinner("Generating audio response..."):
audio_file = text_to_speech(final_response)
autoplay_audio(audio_file)
st.write(final_response)
st.session_state.messages.append({"role": "assistant", "content": final_response})
os.remove(audio_file)
# Float the footer container and provide CSS to target it with
footer_container.float("bottom: 0rem;")
if __name__ == "__main__":
main(answer_mode='base_model') # Or: answer_mode='pdf_chat' |