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from transformers import AutoModelForCausalLM, AutoTokenizer
from PIL import Image
import torch
import streamlit as st
from streamlit_extras.stylable_container import stylable_container
import backend
from backend import *
def chat_UI(model, tokenizer, device, uploaded_file):
st.snow()
st.header('Welcome to ***Icicle*** :ice_cube: ')
st.divider()
if uploaded_file is not None:
if uploaded_file.type == "image/gif":
process_input(model, tokenizer, device, uploaded_file, is_gif=True)
else:
process_input(model, tokenizer, device, uploaded_file, is_gif=False)
def process_input(model, tokenizer, device, uploaded_file, is_gif=False):
st.subheader("Uploaded Image:")
st.image(uploaded_file, caption='Uploaded Image', use_column_width=True)
conversation = st.session_state.get("conversation", [])
user_input = st.session_state.get("user_input", "")
# Display the chat input bar
user_input = st.chat_input("Say something")
if user_input:
# Record user input
chat_record("user", user_input)
# Generate answer
if is_gif:
response = process_gif(model, tokenizer, device, uploaded_file, user_input)
else:
response = generate_answer(model, tokenizer, device, uploaded_file, user_input)
# Record AI response
chat_record("ai", response)
# Update conversation history
conversation.append({'speaker': 'ai', 'message': response})
st.session_state["conversation"] = conversation
# Display the AI responses in sequential order
for i, chat in enumerate(conversation):
if chat['speaker'] == 'ai':
st.text_area(f"AI Response {i+1}", value=chat['message'],max_chars=None, key=None)
def side_bar():
with st.sidebar:
logo_image = "logo.png"
with stylable_container(
key='Logo_Image',
css_styles="""
div[data-testid="stImage"] > img {
border-radius:50%;
width:70%;
margin: -4em 0em 0em 2.5em;
}
""",
):
st.image(logo_image)
st.markdown('<p class="info-text">A GenAI Vision Language Model</p>', unsafe_allow_html=True)
st.markdown('<p class="upload-text">Upload an Image and Ask!</p>', unsafe_allow_html=True)
uploaded_file = st.file_uploader("Choose an Image file : ", type=["jpg", "jpeg", "png", "gif"])
return uploaded_file
def local_css(file_name):
with open(file_name) as f:
st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
def footer():
st.markdown('<div class="footer"><p>Developed with ❤ by <a style="display: block; text-align: center;" href="linkedin.com/in/taher-p-821817214" target="_blank">Taher !</a></p></div>',unsafe_allow_html=True)
def main():
local_css("styles.css")
initialize_session_state()
model, tokenizer, device = model_loading()
uploaded_image = side_bar()
chat_UI(model, tokenizer, device, uploaded_image)
footer()
if __name__=='__main__':
main() |