import streamlit as st
import spacy
from transformers import pipeline
from PIL import Image

nlp = spacy.load("./models/en_core_web_sm")

st.title("SpaGAN Demo")
st.write("Enter a text, and the system will highlight the geo-entities within it.")

# Define a color map for different entity types
COLOR_MAP = {
    'FAC': 'red',    # Facilities (e.g., buildings, airports)
    'ORG': 'blue',   # Organizations (e.g., companies, institutions)
    'LOC': 'purple', # Locations (e.g., mountain ranges, water bodies)
    'GPE': 'green'   # Geopolitical Entities (e.g., countries, cities)
}

# Display the color key
st.write("**Color Key:**")
for label, color in COLOR_MAP.items():
    st.markdown(f"- **{label}**: <span style='color:{color}'>{color}</span>", unsafe_allow_html=True)

user_input = st.text_area("Input Text", height=200)

# Process the text when the button is clicked
if st.button("Highlight Geo-Entities"):
    if user_input.strip():
        # Process the text using spaCy
        doc = nlp(user_input)

        # Highlight geo-entities with different colors
        highlighted_text = user_input
        for ent in reversed(doc.ents):
            if ent.label_ in COLOR_MAP:
                color = COLOR_MAP[ent.label_]
                highlighted_text = (
                    highlighted_text[:ent.start_char] +
                    f"<span style='color:{color}; font-weight:bold'>{ent.text}</span>" + 
                    highlighted_text[ent.end_char:]
                )

        # Display the highlighted text with HTML support
        st.markdown(highlighted_text, unsafe_allow_html=True)
    else:
        st.error("Please enter some text.")