import streamlit as st
import os
import pathlib
import textwrap
from PIL import Image


import google.generativeai as genai


os.getenv("GOOGLE_API_KEY")
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))

## Function to load OpenAI model and get respones

def get_gemini_response(input,image,prompt):
    model = genai.GenerativeModel('gemini-pro-vision')
    response = model.generate_content([input,image[0],prompt])
    return response.text
    

def input_image_setup(uploaded_file):
    # Check if a file has been uploaded
    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="Image description APP")

st.header("Image description Application 🤖💬")
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 nutritionist where you need to see the food items from the image
               and calculate the total calories, also provide the details of every food items with calories intake
               is below format

               1. Item 1 - no of calories
               2. Item 2 - no of calories
               ----
               ----
               """

## If ask button is clicked

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