import streamlit as st
import cv2
import os
from app import *
import pprint

# Create a folder to save captured images
if not os.path.exists("captured_images"):
    os.makedirs("captured_images")

background_style = """
    <style>
        [data-testid="stAppViewContainer"] {
            background-image: url('https://i.ibb.co/HpYr6qg/Untitled-design-2.png'); 
            background-size: cover;
            background-repeat: no-repeat;
            background-attachment: fixed;
        }
    </style>
"""
st.markdown(background_style, unsafe_allow_html=True)

# Initialize the session state
session_state = st.session_state
if 'ingredientsList' not in session_state:
    session_state['ingredientsList'] = ["apple", "orange", "orange"]
# xyz = ["apple", "yerba mate", "orange", "orange"]

def main():
    # Create two columns
    col1, col2 = st.columns([1, 5])

    # In the first column, display the title
    with col1:
        logo = st.image("https://d112y698adiu2z.cloudfront.net/photos/production/software_thumbnail_photos/002/589/585/datas/medium.png", width=150)

        

    # In the second column, display the logo image
    with col2:
        st.title('RecipeBud')

    st.sidebar.header('Ingredients & Nutrition')
    # List of items
    #items = ['Item 1', 'Item 2', 'Item 3']

    #list to of Ingredients camptured
    #ingredientsList =["apple", "orange", "mango"] #list()
   
    # Create a VideoCapture object to access the webcam
    cap = cv2.VideoCapture(0)

    # Set the video frame width and height (optional)
    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 800)
    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 400)

    # Check if the webcam is opened correctly
    if not cap.isOpened():
        st.error("Error: Unable to access the webcam.")
        return

    # Display a placeholder for the video stream
    video_placeholder = st.empty()

    # Apply custom CSS for the button
    st.markdown(
        """
        <style>
            .stButton>button {
                background-color: #4CAF50; /* Green */
                color: white;
                border: none;
                border-radius: 5px;
            }
        </style>
        """,
        unsafe_allow_html=True
    )

    # Button to capture image
    if st.button("Capture Image"):
        image_path = capture_image()
        classification = classifyImage(image_path)
        #session_state['ingredientsList'].append(classification)

    # Button to indicate done
    #done_button = st.sidebar.button('Done')

    # Display the captured ingredients
    # st.write("Captured Ingredients:", session_state['ingredientsList'])

    button_clicked = st.sidebar.button('Done')
    
    # Display recipes if "Done" is clicked
    while not button_clicked:
    # Read a frame from the webcam
        ret, frame = cap.read()

        if not ret:
            st.error("Error: Unable to read frame from the webcam.")
            break

        # Display the frame in the Streamlit app
        video_placeholder.image(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB), channels="RGB", use_column_width=True)
    if button_clicked:
        nutrition_values = analyze_nutrition(nutrients(session_state['ingredientsList']))
        cap.release()
        if session_state['ingredientsList']:
            session_state['ingredientsList'].pop()
        #st.write("Updated Ingredients List:", session_state['ingredientsList'])

        # displayRecipes(session_state['ingredientsList'])
        # Define content for each item
        content = {}
        for ingredient in nutrition_values:
            # content[ingredient] = askGPT(f"Give me your estimate the calories, grams of protein, grams of sugar, grams of fat, and grams of carbohydrates per 100g of {ingredient} as a list")
            content[ingredient] = nutrition_values[ingredient]

        # Display expanders for each item
        # for ingredient in session_state['ingredientsList']:
        #     with st.sidebar.expander(ingredient):
        #         st.write(content[ingredient])
        # displayRecipes(session_state['ingredientsList'])
        
        for ingredient in content:
            with st.sidebar.expander(ingredient):
                ingred = str(content[ingredient])
                st.write(ingred[1:len(ingred)-1].replace("'", "").replace(',', '\n\n'))
        displayRecipes(session_state['ingredientsList'])



def displayRecipes(ingredientsList):
    items = []
    #now we are gonna send the ingredient list to ask gpt
    prompt = f"I have following Ingredients :{','.join(ingredientsList)}. What can I make with these \
            Ingredients? Give me A list of detailed recipes with measurements containing these ingredients with Nutrition Facts (calories, grams of sugar, grams of protein, grams of fats, grams of carbohydrates) per serving based on the widely accepted nutritional value of each of these ingredients. Rank the list from \
            highest nutritional value to lowest. Give me results in \
            following format and do not deviate from this format:\
            ['Recipe Title', 'Calories per serving']."
    #prompt = f"You are going to act as a nutritional expert who has a lot of knowledge about food. I have the following ingredients: {','.join(ingredientsList)}. What can I make with these ingredients? Give me a list of names of recipes, maximum five."
    LLMResult = askGPT(prompt)
    lystOfRecipes = LLMResult.split('\n\n')
    # print(lystOfRecipes)
    count = 0
    for recipe in range(1,len(lystOfRecipes)-1):
        count += 1
        items.append({"title": lystOfRecipes[recipe].split(":")[0], "content": ""})
        if count == 4:
            break
    # Display the items with =expanding boxes
    for item in items:
        #for side bar's item
        #with st.sidebar.expander(item):
            #st.write("man-holding-banana.jpeg")
        #main page items
        with st.expander(item["title"]):
            st.write(askGPT(f"Give me a detailed recipe for a dish called {item['title']} containing all of the following ingredients: {','.join(ingredientsList)}. Make sure your response is easy to follow and comprehensive."))
    

def capture_image():
    # Create a VideoCapture object to access the webcam
    cap = cv2.VideoCapture(0)

    # Set the video frame width and height (optional)
    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 800)
    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 400)

    # Check if the webcam is opened correctly
    if not cap.isOpened():
        st.error("Error: Unable to access the webcam.")
        return

    # Read a frame from the webcam
    ret, frame = cap.read()

    if not ret:
        st.error("Error: Unable to read frame from the webcam.")
        return

    # Save the frame as an image
    image_path = f"captured_images/captured_image_{len(os.listdir('captured_images')) + 1}.jpg"
    cv2.imwrite(image_path, cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
    st.success(f"Image captured and saved as {image_path}")

    # Release the VideoCapture and close the OpenCV window
    cap.release()
    
    return image_path


def nutrients(ingredients):
    formatted_list = []
    for ingredient in ingredients:
        formatted_list.append(ingredient + " per 100 grams")
    return formatted_list


if __name__ == '__main__':
    main()