import os
import streamlit as st
import time
import io
import logging
import json
from components.dashboard import Dashboard

# Must be the first Streamlit command
st.set_page_config(
    page_title="Cybersecurity IDS Dashboard",
    page_icon="🛡️",
    layout="wide",
    initial_sidebar_state="expanded",
)

logging.basicConfig(level=logging.ERROR)

def get_api_token():
    """Retrieves the Hugging Face API token from Streamlit secrets."""
    try:
        return st.secrets["HUGGING_FACE_API_TOKEN"]
    except KeyError:
        st.warning(
            "Please add your Hugging Face API token to Streamlit secrets. "
            "See the Streamlit documentation for instructions."
        )
        st.stop()

def load_sample_logs(filepath="sample_logs.json"):
    """Loads sample logs from a JSON file, or returns default logs if file not found."""
    try:
        with open(filepath, "r") as f:
            return json.load(f)
    except FileNotFoundError:
        return [
            "Failed SSH login attempt from IP 192.168.1.10",
            "Multiple port scan detected from IP 10.0.0.5",
            "Suspicious outbound connection to known malicious IP",
            "Brute force attack detected on admin portal",
        ]

def process_log(log, dashboard, placeholder):
    """Processes a single log entry and updates the dashboard."""
    try:
        from PurpleTeamIDS import analyze_security_log
        threat_data = analyze_security_log(log)
        dashboard.threat_analysis.process_new_threat(threat_data)
        placeholder.write(dashboard.threat_analysis.display_threats())
    except ImportError:
        st.error("PurpleTeamIDS module not found. Please install the necessary dependencies.")
        st.stop()
    except Exception as e:
        st.error(f"Error processing log: {e}")
        logging.error(f"Error processing log: {e}")

def main():
    """Main function to render the Cybersecurity IDS Dashboard."""
    st.title("Cybersecurity Intrusion Detection Dashboard")
    st.markdown("Monitor and analyze security logs for potential threats.")

    # Secure API Token Handling
    api_token = get_api_token()

    # Initialize dashboard
    dashboard = Dashboard()

    # Load custom CSS
    css_path = os.getenv("CSS_PATH", "styles/custom.css")
    try:
        with open(css_path) as f:
            st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
    except FileNotFoundError:
        st.error(f"CSS file not found: {css_path}")

    # Render main content
    dashboard.render_main_content()

    # File Upload functionality
    uploaded_file = st.file_uploader("Upload Security Log File", type=["log", "txt"])
    if uploaded_file is not None:
        try:
            stringio = io.StringIO(uploaded_file.getvalue().decode("utf-8"))
            placeholder = st.empty()
            progress_bar = st.progress(0)
            lines = stringio.readlines()
            total_lines = len(lines)
            for i, line in enumerate(lines):
                process_log(line.strip(), dashboard, placeholder)
                progress_bar.progress((i + 1) / total_lines)
                time.sleep(1)
            progress_bar.empty()
        except Exception as e:
            st.error(f"Error processing log file: {e}")
            logging.error(f"Error processing log file: {e}")

    else:
        # Simulate real-time log analysis
        sample_logs = load_sample_logs()
        placeholder = st.empty()
        progress_bar = st.progress(0)
        total_logs = len(sample_logs)
        for i, log in enumerate(sample_logs):
            process_log(log, dashboard, placeholder)
            progress_bar.progress((i + 1) / total_logs)
            time.sleep(1)
        progress_bar.empty()

    st.markdown("---")
    st.markdown("Footer: Example Cybersecurity Application")

if __name__ == "__main__":
    main()