import streamlit as st
import pandas as pd
import plotly.express as px

# Load the Excel file from a URL
def load_data(url):
    return pd.read_excel(url)

# Function to filter data
def filter_data(df, location_region, priority, month):
    filtered_df = df[(df['Location Region'] == location_region) &
                     (df['Priority'] == priority) &
                     (df['Month'] == month)]
    return filtered_df

# Function to create timeline
def create_timeline(df):
    fig = px.timeline(df, x_start="Actual Date", x_end="Actual Date", y="Name", color="Location Region", title="Conference Timeline")
    fig.update_yaxes(categoryorder="total ascending")
    return fig

# Streamlit app
def main():
    st.title("AI Conferences Timeline")

    # Load data from URL
    url = "https://huggingface.co/datasets/Bexaga/AI-Conference/resolve/main/AI%20conferences%202025.xlsx"
    data = load_data(url)

    # Sidebar for filters
    st.sidebar.header("Filter Options")
    location_regions = data['Location Region'].unique()
    selected_location_region = st.sidebar.selectbox("Select Location Region", location_regions)
    priorities = data['Priority'].unique()
    selected_priority = st.sidebar.selectbox("Select Priority", priorities)
    months = data['Month'].unique()
    selected_month = st.sidebar.selectbox("Select Month", months)

    # Filter data based on user input
    filtered_data = filter_data(data, selected_location_region, selected_priority, selected_month)

    # Display filtered data
    st.subheader("Filtered Conferences")
    st.dataframe(filtered_data[['Category', 'Name', 'Priority', 'Coverage', 'Month', 'Actual Date', 'Date status', 'URL', 'Location Region', 'Location']])

    # Create and display timeline
    st.subheader("Conference Timeline")
    timeline_fig = create_timeline(filtered_data)
    st.plotly_chart(timeline_fig)

if __name__ == "__main__":
    main()