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import streamlit as st | |
import os | |
from streamlit_chat import message | |
from streamlit_extras.colored_header import colored_header | |
from streamlit_extras.add_vertical_space import add_vertical_space | |
from streamlit_mic_recorder import speech_to_text | |
from model_pipeline import ModelPipeLine | |
from gtts import gTTS | |
from io import BytesIO | |
mdl = ModelPipeLine() | |
final_chain = mdl.create_final_chain() | |
st.set_page_config(page_title="PeacePal") | |
# Add logo to the sidebar | |
logo_path = os.path.join('images', 'logo.jpeg') | |
st.sidebar.image(logo_path, use_column_width=True) | |
# Add image to the sidebar | |
image_path = os.path.join('images', 'sidebar.jpg') | |
st.sidebar.image(image_path, use_column_width=True) | |
st.title('PeacePal 🌱') | |
## generated stores AI generated responses | |
if 'generated' not in st.session_state: | |
st.session_state['generated'] = ["I'm your Mental health Assistant, How may I help you?"] | |
## past stores User's questions | |
if 'past' not in st.session_state: | |
st.session_state['past'] = ['Hi!'] | |
# Layout of input/response containers | |
colored_header(label='', description='', color_name='blue-30') | |
response_container = st.container() | |
input_container = st.container() | |
# User input | |
## Function for taking user provided prompt as input | |
def get_text(): | |
input_text = st.text_input("You: ", "", key="input") | |
return input_text | |
def generate_response(prompt): | |
response = mdl.call_conversational_rag(prompt,final_chain) | |
return response['answer'] | |
def text_to_speech(text): | |
# Use gTTS to convert text to speech | |
tts = gTTS(text=text, lang='en') | |
# Save the speech as bytes in memory | |
fp = BytesIO() | |
tts.write_to_fp(fp) | |
return fp | |
def speech_recognition_callback(): | |
# Ensure that speech output is available | |
if st.session_state.my_stt_output is None: | |
st.session_state.p01_error_message = "Please record your response again." | |
return | |
# Clear any previous error messages | |
st.session_state.p01_error_message = None | |
# Store the speech output in the session state | |
st.session_state.speech_input = st.session_state.my_stt_output | |
## Applying the user input box | |
with input_container: | |
# Add a radio button to choose input mode | |
input_mode = st.radio("Select input mode:", ["Text", "Speech"]) | |
if input_mode == "Speech": | |
# Use the speech_to_text function to capture speech input | |
speech_input = speech_to_text( | |
key='my_stt', | |
callback=speech_recognition_callback | |
) | |
# Check if speech input is available | |
if 'speech_input' in st.session_state and st.session_state.speech_input: | |
# Display the speech input | |
st.text(f"Speech Input: {st.session_state.speech_input}") | |
# Process the speech input as a query | |
query = st.session_state.speech_input | |
with st.spinner("processing....."): | |
response = generate_response(query) | |
st.session_state.past.append(query) | |
st.session_state.generated.append(response) | |
# Convert the response to speech | |
speech_fp = text_to_speech(response) | |
# Play the speech | |
st.audio(speech_fp, format='audio/mp3') | |
else: | |
# Add a text input field for query | |
query = st.text_input("Query: ", key="input") | |
# Process the query if it's not empty | |
if query: | |
with st.spinner("typing....."): | |
response = generate_response(query) | |
st.session_state.past.append(query) | |
st.session_state.generated.append(response) | |
# Convert the response to speech | |
speech_fp = text_to_speech(response) | |
# Play the speech | |
st.audio(speech_fp, format='audio/mp3') | |
## Conditional display of AI generated responses as a function of user provided prompts | |
with response_container: | |
if st.session_state['generated']: | |
for i in range(len(st.session_state['generated'])): | |
message(st.session_state['past'][i], is_user=True, key=str(i) + '_user') | |
message(st.session_state["generated"][i], key=str(i)) | |