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CWI.py
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from dotenv import load_dotenv
load_dotenv() ## load all the environment variables from .env
import streamlit as st
import os
from PIL import Image
import google.generativeai as genai
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
## Load Gemini pro vision model
model=genai.GenerativeModel('gemini-pro-vision')
def get_gemini_response(input,image,user_prompt):
response=model.generate_content([input,image[0],user_prompt])
return response.text
def input_image_details(uploaded_file):
if uploaded_file is not None:
# Read the file into bytes
bytes_data = uploaded_file.getvalue()
image_parts = [
{
"mime_type": uploaded_file.type, # Get the mime type of the uploaded file
"data": bytes_data
}
]
return image_parts
else:
raise FileNotFoundError("No file uploaded")
##initialize our streamlit app
st.set_page_config(page_title="Chat with Inage")
st.header("Chat With Image ")
input=st.text_input("Input Prompt: ",key="input")
uploaded_file = st.file_uploader("Choose an image of the invoice...", type=["jpg", "jpeg", "png"])
if uploaded_file is not None:
image=Image.open(uploaded_file)
st.image(image, caption="Uploaded Image.", use_column_width=True)
submit=st.button("Tell me about the image")
input_prompt="""
You are an expert in understanding images with multiple languages. We will upload a a image
and you will have to answer any questions based on the uploaded image
"""
## if submit button is clicked
if submit:
image_data=input_image_details(uploaded_file)
response=get_gemini_response(input_prompt,image_data,input)
st.subheader("The Rresponse is")
st.write(response)