import streamlit as st
import os
import google.generativeai as genai
from PIL import Image

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

## Function to load Google Gemini Pro Vision API And get response

def get_gemini_repsonse(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, image into numbers
        bytes_data = uploaded_file.getvalue()

        image_parts = [                     #In dic format
            {
                "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="Nutrition and Calories Manager App")

st.header("Nutrition and Calories Manager App")
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("CHECK")

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 item with calories intake
               is below format
               1. Item 1 -no of calories
               2. Item 2 -no of calories
               ----
               ----
               Total Calories
Also mention about the important nutrients like Protein , Carbohydrates and Fats  in each item
        Put the  output in a tabular format with each item in a separate row and details in columns
"""

## If submit button is clicked

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