from dotenv import load_dotenv
load_dotenv()

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 = genai.GenerativeModel('gemini-pro-vision')

def get_gemini_response(input,image,prompt):
    response = model.generate_content([input,image[0],prompt])
    return response.text

def input_image(uploaded_file):
    if uploaded_file is not None:
        bytes_data = uploaded_file.getvalue()

        image_parts = [
            {
                "mime_type":uploaded_file.type,
                "data":bytes_data
            }
        ]
        return image_parts
    else:
        raise FileNotFoundError("No file uploaded")
    


# Streamlit
st.set_page_config(page_title="Extractor",page_icon=":100:")
st.header("Quick Info")
st.subheader("Extract information from images")
input = st.text_input("Input prompt :",key="input")
uploaded_file = st.file_uploader("Choose an image ...",type=["jpg","jpeg","png"])
image = ""
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. We will upload an image
and you will have to answer any question based on the uploaded image
"""

if submit:
    image_data = input_image(uploaded_file)
    response = get_gemini_response(input,image_data,input_prompt)
    st.subheader("The response :")
    st.write(response)