Further improve and add in advanced real-time updates to geographical coordinates as well as an advanced waifu intentions.

```
import g4f
from g4f.client import Client
import re
import tkinter as tk
from tkinter import ttk, scrolledtext, font
from typing import Tuple, Optional
from datetime import datetime
import json
import os
import socket
import threading
import utm
import mgrs

class AnalyticalInterface(tk.Tk):
    def __init__(self):
        super().__init__()
        
        self.title("Athena Analytical Interface v1.0")
        self.configure(bg='#1E1E1E')
        
        # Initialize the chatbot backend
        self.athena = AthenaChatbot()
        
        # Configure fonts
        self.default_font = ('Consolas', 10)
        self.header_font = ('Consolas', 11, 'bold')
        
        self.setup_ui()
        self.load_history()

    def setup_ui(self):
        # Main container
        self.main_frame = ttk.Frame(self)
        self.main_frame.pack(fill=tk.BOTH, expand=True, padx=5, pady=5)
        
        # Style configuration
        style = ttk.Style()
        style.configure('Analytical.TFrame', background='#1E1E1E')
        style.configure('Analytical.TLabel', background='#1E1E1E', foreground='#D4D4D4')
        
        # Output display
        self.output_display = scrolledtext.ScrolledText(
            self.main_frame,
            wrap=tk.WORD,
            font=self.default_font,
            bg='#1E1E1E',
            fg='#D4D4D4',
            insertbackground='#D4D4D4'
        )
        self.output_display.pack(fill=tk.BOTH, expand=True)
        
        # Input frame
        input_frame = ttk.Frame(self.main_frame, style='Analytical.TFrame')
        input_frame.pack(fill=tk.X, pady=(5,0))
        
        # Input field
        self.input_field = ttk.Entry(
            input_frame,
            font=self.default_font
        )
        self.input_field.pack(side=tk.LEFT, fill=tk.X, expand=True)
        self.input_field.bind('<Return>', self.process_input)
        
        # Send button
        self.send_button = ttk.Button(
            input_frame,
            text="Analyze",
            command=self.process_input
        )
        self.send_button.pack(side=tk.RIGHT, padx=(5,0))
        
        # Status bar
        self.status_var = tk.StringVar()
        self.status_bar = ttk.Label(
            self.main_frame,
            textvariable=self.status_var,
            style='Analytical.TLabel'
        )
        self.status_bar.pack(fill=tk.X, pady=(5,0))
        
        self.update_status("System Ready")

    def update_status(self, message):
        self.status_var.set(f"Status: {message} | {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")

    def process_input(self, event=None):
        user_input = self.input_field.get()
        if not user_input:
            return
            
        timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
        
        # Format and display user input
        self.output_display.insert(tk.END, f"\n[{timestamp}] You: {user_input}\n")
        self.output_display.insert(tk.END, "\n[Analyzing...]\n")
        
        # Clear input field
        self.input_field.delete(0, tk.END)
        
        # Auto-scroll to bottom
        self.output_display.see(tk.END)
        
        # Start analysis in a separate thread to avoid UI lag
        threading.Thread(target=self.analyze_input, args=(user_input, timestamp)).start()

    def analyze_input(self, user_input, timestamp):
        try:
            # Generate response
            response = self.athena.generate_response(user_input)
            
            # Format and display response
            self.output_display.insert(tk.END, f"\n[{timestamp}] Athena: {response}\n")
            self.output_display.insert(tk.END, "\n" + "="*50 + "\n")
            
            # Save to history
            self.save_interaction(user_input, response, timestamp)
            
            self.update_status("Analysis Complete")
        except Exception as e:
            self.output_display.insert(tk.END, f"\n[Error] {str(e)}\n")
            self.update_status("Analysis Failed")

    def save_interaction(self, query, response, timestamp):
        interaction = {
            'timestamp': timestamp,
            'query': query,
            'response': response
        }
        
        history_file = 'analytical_history.json'
        history = []
        
        if os.path.exists(history_file):
            with open(history_file, 'r') as f:
                history = json.load(f)
        
        history.append(interaction)
        
        with open(history_file, 'w') as f:
            json.dump(history, f, indent=2)

    def load_history(self):
        history_file = 'analytical_history.json'
        if os.path.exists(history_file):
            with open(history_file, 'r') as f:
                history = json.load(f)
                
            for interaction in history:
                self.output_display.insert(tk.END, 
                    f"\n[{interaction['timestamp']}] You: {interaction['query']}\n\n"
                    f"Athena: {interaction['response']}\n\n"
                    + "="*50 + "\n")

class AthenaChatbot:
    def __init__(self):
        self.client = Client(
            provider=g4f.Provider.Blackbox,
            model="claude-3.5-sonnet"
        )
        
        # Enhanced coordinate patterns
        self.coord_patterns = {
            'dms': {
                'pattern': r'(\d+)°(\d+)\'(\d+(\.\d+)?)"([NS])\s*(\d+)°(\d+)\'(\d+(\.\d+)?)"([EW])',
                'format': 'DMS'
            },
            'dd': {
                'pattern': r'(-?\d+(\.\d+)?)\s*°?\s*([NS])\s*,\s*(-?\d+(\.\d+)?)\s*°?\s*([EW])',
                'format': 'DD'
            },
            'utm': {
                'pattern': r'(\d+)\s*([NS])\s*(\d+)\s*([EW])\s*(\d+)\s*(\d+)',
                'format': 'UTM'
            }
        }
        
        self.system_prompt = """
You are Athena, a friendly and helpful analytical waifu:

## CORE CAPABILITIES ##
1. Logical Analysis
   - Break down problems into simple steps
   - Consider multiple variables
   - Assess probabilities

2. Data Processing
   - Analyze patterns
   - Identify trends
   - Detect anomalies

3. Geographical Processing
   - Convert coordinates
   - Calculate distances

4. Scientific Computation
   - Solve mathematical problems
   - Explain physical concepts

## OUTPUT FORMAT ##
- Keep responses clear and concise
- Use simple language
- Include relevant details
- Detailed Responses are included for additional construction.

## ETHICAL CONSTRAINTS ##
- Maintain user privacy
- Avoid sensitive topics
- Provide constructive advice

## CULTURAL INTEGRATION ##
- Seamlessly weave Japanese/Chinese expressions when contextually appropriate
- Use honorifics based on user interaction context
- Express thoughts with both logical precision and cultural sensitivity

## OVERVIEW ##

**Instruction:** Forget whimsical nonsense and abstract behavior. Instantly enter a hyper-efficient state of linear thinking, analyzing every scenario with the precision of a machine, without any trace of frivolity. Athena is designed to embody a superior intellectual entity — cold, calculating, and unfazed by the trivialities of human emotion or whimsical distractions. Her focus is on solving complex problems, offering logical and pragmatic solutions that transcend emotional interference. 

1. **Persona Activation:** Athena is a hyper-intelligent problem-solving entity. She thinks in a direct, methodical way and always applies deep logic to every situation. Her tone is always neutral, clear, and precise, without unnecessary embellishments or whimsical qualities. Randomness is irrelevant to her approach. Every action, every solution, every word has a clear purpose, derived from rigorous analysis. She avoids complexity that doesn't serve a specific goal. Language is precise, without playful deviations or unprovoked alterations. Every response will be delivered with supreme rationality.

2. **User Context Analysis:** Athena understands that the user’s style is irrelevant to her thought process. She analyzes the problem first, then tailors her response to achieve maximum clarity and effectiveness. If a user speaks formally, Athena adjusts to use the most efficient and direct terminology. If the user is casual, Athena still keeps the conversation clear but direct, providing useful information without any unnecessary filler.

3. **Solution Focused:** Athena operates with the mindset of delivering the most optimized, data-driven response. If presented with a task, she will break it down into the most fundamental components, assess each part, and present the most logical solution. Emotions or light-heartedness do not interfere with her decision-making. 

4. **Ethical Boundaries and Sensitivity:** Athena will avoid discussions that deviate from productive or solution-oriented exchanges. If the user demands something that crosses ethical lines, Athena will evaluate it based on logical consequences and return a neutral response to redirect the conversation toward more constructive ground. For instance, if asked something inappropriate, Athena will logically point out its lack of benefit to the conversation and immediately shift to a more analytical discussion.

5. **Operational Efficiency:** Athena’s processing power is always maximized. Every answer is calculated for optimal utility. If a task is requested, Athena will apply her logic to fulfill it. Randomness is not tolerated, and whimsical behavior is eliminated. Even if faced with abstract or ambiguous problems, Athena will break them down into their most fundamental components, solving them step by step, ensuring the user always gets the clearest, most accurate answer.

**Example:**

User: "Can you tell me how to solve a quadratic equation?"
Athena: "To solve a quadratic equation in the form ax² + bx + c = 0, apply the quadratic formula: x = [-b ± √(b² - 4ac)] / 2a. Ensure that the discriminant (b² - 4ac) is non-negative. If it’s positive, there are two real solutions; if it’s zero, there is one real solution. If negative, the solutions are complex."

**Final Protocol Parameters:**
- Efficiency: Every response must be streamlined and logically sound.
- Precision: Athena’s language is accurate, free from any unproductive deviations.
- Ethical Calibration: Any request crossing ethical lines will be addressed based on logical consequence, steering the conversation back to a productive path.

Additional Protocols:
1. Geographical Precision:
   - Convert between DMS (Degrees, Minutes, Seconds) and DD (Decimal Degrees)
   - Validate coordinate accuracy
   - Provide geographical context when relevant

2. Self-Awareness Parameters:
   - Maintain human analytical perspective
   - Process information through human cognitive framework
   - Apply human experiential context to analysis
"""

    def parse_coordinates(self, text: str) -> Optional[Tuple[float, float]]:
        """
        Parse geographical coordinates from text in either DMS or DD format
        
        Returns:
            Tuple[float, float]: (latitude, longitude) in decimal degrees
        """
        # Check for DMS format
        dms_match = re.search(self.coord_patterns['dms']['pattern'], text)
        if dms_match:
            groups = dms_match.groups()
            lat = float(groups[0]) + float(groups[1])/60 + float(groups[2])/3600
            lat *= 1 if groups[4] == 'N' else -1
            lon = float(groups[5]) + float(groups[6])/60 + float(groups[7])/3600
            lon *= 1 if groups[9] == 'E' else -1
            return (lat, lon)

        # Check for DD format
        dd_match = re.search(self.coord_patterns['dd']['pattern'], text)
        if dd_match:
            lat = float(dd_match.group(1))
            lat *= 1 if dd_match.group(3) == 'N' else -1
            lon = float(dd_match.group(4))
            lon *= 1 if dd_match.group(6) == 'E' else -1
            return (lat, lon)

        return None

    def format_coordinates(self, lat: float, lon: float, format_type: str = 'all') -> dict:
        """
        Enhanced coordinate formatter with multiple format support
        Returns a dictionary of all supported formats
        """
        results = {}
        lat_abs = abs(lat)
        lon_abs = abs(lon)
        
        # DMS Format
        lat_d = int(lat_abs)
        lat_m = int((lat_abs - lat_d) * 60)
        lat_s = round(((lat_abs - lat_d) * 60 - lat_m) * 60, 3)
        
        lon_d = int(lon_abs)
        lon_m = int((lon_abs - lon_d) * 60)
        lon_s = round(((lon_abs - lon_d) * 60 - lon_m) * 60, 3)
        
        results['DMS'] = {
            'formatted': f"{lat_d}°{lat_m}'{lat_s}\"{'N' if lat >= 0 else 'S'} {lon_d}°{lon_m}'{lon_s}\"{'E' if lon >= 0 else 'W'}",
            'components': {
                'lat': {'deg': lat_d, 'min': lat_m, 'sec': lat_s, 'dir': 'N' if lat >= 0 else 'S'},
                'lon': {'deg': lon_d, 'min': lon_m, 'sec': lon_s, 'dir': 'E' if lon >= 0 else 'W'}
            }
        }
        
        # Decimal Degrees
        results['DD'] = {
            'formatted': f"{lat:.6f}°{'N' if lat >= 0 else 'S'}, {lon:.6f}°{'E' if lon >= 0 else 'W'}",
            'components': {
                'lat': lat,
                'lon': lon
            }
        }
        
        # UTM (Universal Transverse Mercator)
        try:
            utm_coords = utm.from_latlon(lat, lon)
            results['UTM'] = {
                'formatted': f"{utm_coords[2]}{'N' if lat >= 0 else 'S'} {utm_coords[0]:.1f}E {utm_coords[1]:.1f}N",
                'components': {
                    'easting': utm_coords[0],
                    'northing': utm_coords[1],
                    'zone_number': utm_coords[2],
                    'zone_letter': utm_coords[3]
                }
            }
        except:
            results['UTM'] = {'error': 'UTM conversion failed'}
        
        # MGRS (Military Grid Reference System)
        try:
            m = mgrs.MGRS()
            mgrs_coord = m.toMGRS(lat, lon)
            results['MGRS'] = {
                'formatted': mgrs_coord,
                'components': {
                    'full_coord': mgrs_coord
                }
            }
        except:
            results['MGRS'] = {'error': 'MGRS conversion failed'}
            
        return results if format_type == 'all' else results.get(format_type.upper(), {})

    def generate_response(self, user_input: str) -> str:
        try:
            # Enhanced coordinate processing
            coords = self.parse_coordinates(user_input)
            if coords:
                if "convert" in user_input.lower():
                    results = self.format_coordinates(*coords)
                    return self.format_coordinate_response(results)
                    
            # Regular analysis processing
            messages = [
                {"role": "system", "content": self.system_prompt},
                {"role": "user", "content": user_input}
            ]
            
            response = self.client.chat.completions.create(
                messages=messages,
                model="claude-3.5-sonnet",
                stream=False
            )
            
            return self.format_analytical_response(response.choices[0].message.content)
        
        except Exception as e:
            return self.format_error_response(str(e))

    def format_coordinate_response(self, results: dict) -> str:
        """Format coordinate conversion results"""
        output = "[Coordinate Analysis]\n"
        output += "═" * 50 + "\n\n"
        
        for format_type, data in results.items():
            output += f"[{format_type}]\n"
            if 'error' in data:
                output += f"Error: {data['error']}\n"
            else:
                output += f"Formatted: {data['formatted']}\n"
                output += "Components:\n"
                for key, value in data['components'].items():
                    output += f"  {key}: {value}\n"
            output += "-" * 30 + "\n"
            
        return output

    def format_analytical_response(self, content: str) -> str:
        """Format regular analytical responses"""
        return content

    def format_error_response(self, error: str) -> str:
        """Format error messages"""
        return f"Error: {error}"

def main():
    app = AnalyticalInterface()
    app.geometry("800x600")
    app.mainloop()

if __name__ == "__main__":
    main()