Remove the sympy and further improve with more advanced AGI capabilities with number discovery stuff.

```
import g4f
import random
import math
import sympy
from typing import List, Dict, Any, Optional

class AdvancedNumberDiscoveryAGI:
    def __init__(self, model='claude-3.5-sonnet'):
        self.model = model
        self.discovered_numbers: Dict[str, List[Any]] = {
            'custom_notation': [],
            'variable_based': [],
            'parametric': [],
            'symbolic': []
        }
        self.mathematical_notation_systems = [
            'Scientific Notation',
            'Engineering Notation',
            'Logarithmic Notation',
            'Symbolic Algebra',
            'Parametric Equations'
        ]

    def _generate_client(self):
        return g4f.client.Client(provider=g4f.Provider.Blackbox)

    def generate_advanced_prompt(self, query: str) -> str:
        return f"""
        Advanced Numerical Notation and Generation Challenge:

        User Query: {query}

        Detailed Requirements:
        1. Generate a number with precise mathematical notation
        2. Develop a custom notation system for the number
        3. Create a variable-based representation
        4. Provide a symbolic and parametric interpretation
        5. Demonstrate computational and theoretical significance

        Constraints:
        - Use advanced notation techniques
        - Incorporate user-specified constraints
        - Explore multi-dimensional number representations
        - Provide a computational method for number generation

        Notation Guidelines:
        - Explain the notation system
        - Show variable dependencies
        - Demonstrate computational derivation
        """

    def discover_number(self, query: str) -> Dict[str, Any]:
        client = self._generate_client()
        
        prompt = self.generate_advanced_prompt(query)
        
        try:
            response = client.chat.completions.create(
                model=self.model,
                messages=[
                    {"role": "system", "content": "You are an advanced mathematical notation and number generation assistant."},
                    {"role": "user", "content": prompt}
                ]
            )
            
            result = response.choices[0].message.content
            return self._parse_advanced_discovery(query, result)
        
        except Exception as e:
            print(f"Discovery error: {e}")
            return self._generate_symbolic_number(query)

    def _parse_advanced_discovery(self, query: str, result: str) -> Dict[str, Any]:
        try:
            # Advanced parsing with symbolic computation
            symbolic_representation = self._extract_symbolic_notation(result)
            parametric_form = self._generate_parametric_representation(symbolic_representation)
            
            return {
                'query': query,
                'symbolic_notation': symbolic_representation,
                'parametric_form': parametric_form,
                'computational_method': self._derive_computational_method(result),
                'notation_system': self._identify_notation_system(result)
            }
        except Exception as e:
            print(f"Parsing error: {e}")
            return self._generate_symbolic_number(query)

    def _extract_symbolic_notation(self, text: str) -> str:
        # Advanced symbolic notation extraction
        try:
            # Use sympy for symbolic manipulation
            x, y, z = sympy.symbols('x y z')
            
            # Try to extract a symbolic expression
            symbolic_expressions = [
                r'\b[a-zA-Z]\s*=\s*[^\n]+',  # Variable assignment
                r'f\([a-zA-Z]\)\s*=\s*[^\n]+',  # Function definition
                r'[a-zA-Z]\s*:\s*[^\n]+'  # Mapping notation
            ]
            
            for pattern in symbolic_expressions:
                import re
                match = re.search(pattern, text)
                if match:
                    return match.group(0)
            
            # Fallback: generate a generic symbolic representation
            return f"f(x) = {random.uniform(0.1, 10)} * x^{random.uniform(1, 3)}"
        
        except Exception:
            return f"f(x) = {random.uniform(0.1, 10)} * x^{random.uniform(1, 3)}"

    def _generate_parametric_representation(self, symbolic_notation: str) -> Dict[str, Any]:
        # Generate a parametric representation with multiple variables
        try:
            x, t = sympy.symbols('x t')
            
            # Parse the symbolic notation
            base_func = sympy.sympify(symbolic_notation.split('=')[-1].strip())
            
            # Create parametric representations
            parametric_forms = {
                'linear': f"x(t) = {base_func} * t",
                'quadratic': f"x(t) = {base_func} * t^2",
                'exponential': f"x(t) = exp({base_func} * t)"
            }
            
            return parametric_forms
        except Exception:
            return {
                'linear': f"x(t) = {random.uniform(0.1, 10)} * t",
                'quadratic': f"x(t) = {random.uniform(0.1, 10)} * t^2"
            }

    def _derive_computational_method(self, text: str) -> str:
        # Extract or generate a computational method
        computational_keywords = [
            'algorithm', 'method', 'compute', 'calculate', 'derive'
        ]
        
        sentences = text.split('.')
        for sentence in sentences:
            if any(keyword in sentence.lower() for keyword in computational_keywords):
                return sentence.strip()
        
        return f"Computational method: Iterative generation with randomization and {random.choice(['exponential', 'logarithmic', 'polynomial'])} scaling"

    def _identify_notation_system(self, text: str) -> str:
        # Machine learning-inspired notation system identification
        notation_scores = {
            system: sum(text.lower().count(term.lower()) for term in system.split()) 
            for system in self.mathematical_notation_systems
        }
        return max(notation_scores, key=notation_scores.get)

    def _generate_symbolic_number(self, query: str) -> Dict[str, Any]:
        # Advanced symbolic number generation
        x, y = sympy.symbols('x y')
        
        # Generate various symbolic representations
        symbolic_generators = [
            lambda: sympy.simplify(x**2 + y),
            lambda: sympy.simplify(sympy.exp(x) * y),
            lambda: sympy.simplify(sympy.log(x + 1) * y)
        ]
        
        generator = random.choice(symbolic_generators)
        symbolic_expr = generator()
        
        return {
            'query': query,
            'symbolic_notation': str(symbolic_expr),
            'parametric_form': {
                'linear': f"x(t) = {symbolic_expr} * t",
                'quadratic': f"x(t) = {symbolic_expr} * t^2"
            },
            'computational_method': "Symbolic generation with randomized function composition",
            'notation_system': random.choice(self.mathematical_notation_systems)
        }

    def visualize_discovery(self, discovery: Dict[str, Any]) -> None:
        print("\n🔢 Advanced Number Discovery Report 🔢")
        print(f"Original Query: {discovery.get('query', 'N/A')}")
        print(f"Symbolic Notation: {discovery.get('symbolic_notation', 'N/A')}")
        print("\nParametric Forms:")
        for key, value in discovery.get('parametric_form', {}).items():
            print(f"  {key.capitalize()}: {value}")
        print(f"\nNotation System: {discovery.get('notation_system', 'N/A')}")
        print(f"Computational Method: {discovery.get('computational_method', 'N/A')}")

def main():
    agi = AdvancedNumberDiscoveryAGI()
    
    while True:
        query = input("What kind of number would you like to discover? (or 'exit'): ")
        
        if query.lower() == 'exit':
            break
        
        discovery = agi.discover_number(query)
        agi.visualize_discovery(discovery)

if __name__ == "__main__":
    main()