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import os
import streamlit as st
from streamlit_option_menu import option_menu
from gemini_utility import (load_gemini_pro,
gemini_pro_vision_responce)
from PIL import Image
# To get the working directory
working_directory = os.path.dirname(os.path.abspath(__file__))
# Setting the page config
st.set_page_config(
page_title="Gemini AI",
page_icon="🤖",
layout="centered",
initial_sidebar_state="expanded",
)
with st.sidebar:
selected = option_menu("Gemini AI",
["Chatbot",
"Image Captioning",
],
menu_icon="robot",
icons=['chat-dots-fill', 'image-fill'],
default_index=0)
def translate_role_to_streamlit(user_role):
if user_role == "model":
return "assistant"
else:
return user_role
if selected == "Chatbot":
model = load_gemini_pro()
# Initialize chat session in Streamlit if not present
if "chat_session" not in st.session_state:
st.session_state.chat_session = model.start_chat(history=[])
# Streamlit page title
st.title("Gemini Chatbot 🤖")
# Display the chatbot history
for message in st.session_state.chat_session.history:
with st.chat_message(translate_role_to_streamlit(message.role)):
st.markdown(message.parts[0].text)
# Input field for user's message
user_prompt = st.chat_input("Ask Gemini Pro...")
if user_prompt:
st.chat_message("user").markdown(user_prompt)
gemini_response = st.session_state.chat_session.send_message(user_prompt)
# Display the chatbot response
with st.chat_message("assistant"):
st.markdown(gemini_response.text)
if selected == "Image Captioning":
# Streamlit title
st.title("Gemini Image Caption Generation📸")
upload_image = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
if upload_image and st.button("Generate"):
image = Image.open(upload_image)
col1, col2 = st.columns(2)
with col1:
st.image(image, caption="Uploaded Image", use_column_width=True)
default_prompt = "Write a caption for this image"
# Getting the response from gemini
caption = gemini_pro_vision_responce(default_prompt, image)
with col2:
st.info(caption)
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