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# import required libraries | |
from dotenv import load_dotenv | |
load_dotenv() # to load all the env variables | |
import streamlit as st | |
import os | |
import google.generativeai as genai | |
from PIL import Image | |
import time | |
#-------------------------------------------# | |
genai.configure(api_key= os.getenv("GOOGLE_API_KEY")) | |
# creating function to load gemini pro model | |
model = genai.GenerativeModel("gemini-pro-vision") | |
model1 = genai.GenerativeModel("gemini-pro") | |
def get_response(input,image): | |
start_time = time.time() | |
if input != '' and image is not None: | |
response = model.generate_content([input,image]) | |
elif image == None: | |
response = model1.generate_content(input) | |
else: | |
response = model.generate_content(image) | |
#response = response.parts | |
#for part in response: | |
#return (part.text) | |
end_time = time.time() | |
response_time = end_time - start_time | |
return response.text,response_time | |
# To set up streamlit | |
st.set_page_config(page_title="Content Generation LLM Model using Gemini") | |
st.header("Content Generation LLM Model ") | |
input = st.text_input("Input Prompt", key="input") | |
uploaded_file = st.file_uploader("Input Image", type=["jpg", "jpeg", "png"]) | |
image=None | |
if uploaded_file is not None: | |
image = Image.open(uploaded_file) | |
st.image(image, caption="Uploaded Image.", use_column_width=True) | |
submit = st.button("Generate") | |
## when submit button is clicked, | |
if submit: | |
response_text,response_time = get_response(input,image) | |
st.subheader("The Generated Content:") | |
st.write(response_text) | |
st.write("Response Time :" ,response_time) | |