import streamlit as st
import base64

# Setting page config
st.set_page_config(page_title="Home", page_icon=":house:", layout="wide")

#-------------------------------- Background and custom CSS -------------------------------------#
#impliment background formating
def set_bg_hack(main_bg):
    # set bg name
    main_bg_ext = "jpg"
    st.markdown(
        f"""
         <style>
         .stApp {{
             background: url(data:image/{main_bg_ext};base64,{base64.b64encode(open(main_bg, "rb").read()).decode()});
             background-repeat: no-repeat;
             background-position: right 50% bottom 95% ;
             background-size: cover;
             background-attachment: scroll;
         }}
         </style>
         """,
        unsafe_allow_html=True,
    )

set_bg_hack("images/dark_bg_home.jpg")

# Setting custom css
css = f"""
<style>

[data-testid="stHeader"] {{
background: rgba(0,0,0,0);
}}

</style>
"""
st.markdown(css, unsafe_allow_html=True)

#-------------------------------- Sidebar Modification -------------------------------------#
# Setting logo on sidebar
st.sidebar.image("images/logo.png", caption="About this app")
st.sidebar.markdown("##")
st.sidebar.markdown("##")
st.sidebar.markdown("##")
st.sidebar.markdown("[![GitHub](https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github)](https://github.com/prithush92)")
st.sidebar.markdown("[![LinkedIn](https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin)](https://www.linkedin.com/in/prithush92/)")

# Page title
st.title("Airline Passenger Feedback Portal ✈️")

# Description
st.markdown("""
Welcome to the Airline Passenger Feedback Portal! This app analyzes passenger ratings and reviews and predicts how likely is a passenger to recommend the airline. \n
""")

# Features
st.header("🚩 Features", divider="red")
st.markdown("""
- **Analyze Passenger Ratings**: A Machine Learning model is deployed to predict customer recommendation status based on Ratings.
- **Review Sentiment Analysis**: Customer Reviews are deeply analyzed and sentiment analysis is performed to determine the sentiment of the review.
- **Overall Recommendation Prediction**: Finally using both the Ratings and Review Sentiment, Overall Recommendation Status of the user is predicted.
- **Airline Reviews Dashboard**: For the convenience of Airline Companies, a dashboard is designed to easily visualize Passenger Ratings 
            and Important Keywords in both Positive and Negative Reviews.
""")

# Technologies Used
st.header("🌐 Technologies Used", divider="blue")
st.markdown("""
- **SQLite**: Database management system for storing and retrieving passenger feedback data.
- **Pandas**: Data manipulation and analysis library for handling datasets.
- **NumPy**: Numerical computing library for performing mathematical operations.
- **Matplotlib**: Visualization library for creating insightful plots and charts.
- **WordCloud**: Visualization tool for generating word clouds from textual data.
- **TensorFlow**: Deep learning framework for building and training machine learning models.
""")

# About the Developer
st.header("👨🏻‍💻 About the Developer", divider="green")
st.write("""
This app is developed by **Prithu Sharma**.
""")
st.markdown(
        """
        [![GitHub](https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github)](https://github.com/prithush92)
        [![LinkedIn](https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin)](https://www.linkedin.com/in/prithush92/)
        """
    )

# Footer
st.markdown("---")
st.write("Explore the app and make informed decisions based on passenger feedback!")