import streamlit as st
import pandas as pd
import folium
from streamlit_folium import st_folium

# Set the title of the Streamlit app
st.title("Conjunto de datos de IA agentica multimodal a través de Uber 3 | Multimodal Agentic AI via Uber Dataset 3")

# Load and display the Uber dataset
@st.cache_data  # Cache the dataframe to improve performance
def load_data():
    return pd.read_csv('uber-raw-data-may14.csv')

# Load the Uber dataset
df = load_data()

# Display a subset of the dataframe (rows 10 to 20)
st.subheader("Trips per Hour (Rows 10 to 20)")
st.dataframe(df.iloc[10:21])  # Display rows 10 to 20

# Load and display videos
video_files = [f'analisis_video_{i}.mp4' for i in range(1, 14)]  # Generate video filenames

for video_file in video_files:
    try:
        with open(video_file, 'rb') as f:
            video_bytes = f.read()
            st.video(video_bytes)
    except FileNotFoundError:
        st.warning(f"Video file {video_file} not found.")

# Load and display the Folium map
st.subheader("Trips Map")
try:
    # Load the Folium map from the HTML file
    with open('trips_map.html', 'r', encoding='utf-8') as f:
        map_html = f.read()
    
    # Display the map using st_folium
    st.components.v1.html(map_html, width=700, height=500)
except FileNotFoundError:
    st.warning("Folium map file 'trips_map.html' not found.")