multimodal_system.py

try:
    import tensorflow as tf

    TF_AVAILABLE = True
except ImportError:
    TF_AVAILABLE = False

import cv2  # OpenCV for image processing
import numpy as np


class IntegratedMultimodalSystem:
    def __init__(self):
        # Initialize NLP model, image processing model, etc.
        if TF_AVAILABLE:
            # self.nlp_model = tf.keras.models.load_model('nlp_model_path')  # Placeholder
            self.nlp_model = None  # Placeholder for now
        else:
            self.nlp_model = None
        # Other initialization

    def process_input(self, input_data):
        # Determine the type of input (text, image, etc.)
        if self.is_text(input_data):
            return self.process_text(input_data)
        elif self.is_image(input_data):
            return self.process_image(input_data)
        # Additional input types
        return "Unknown input type"

    def process_text(self, text):
        # Process text using NLP model
        # Placeholder implementation
        nlp_result = f"NLP processed: {text}"
        return nlp_result

    def process_image(self, image):
        # Process image (could be an emoji or other symbolic image)
        # Placeholder: assume image is a path
        try:
            processed_image = cv2.imread(image)
            if processed_image is not None:
                # Image analysis logic placeholder
                image_analysis_result = (
                    f"Image processed: shape {processed_image.shape}"
                )
            else:
                image_analysis_result = "Failed to load image"
        except Exception as e:
            image_analysis_result = f"Error processing image: {e}"
        return image_analysis_result

    def is_text(self, input_data):
        # Logic to determine if input_data is text
        return isinstance(input_data, str) and not input_data.endswith(
            (".jpg", ".png", ".jpeg")
        )

    def is_image(self, input_data):
        # Logic to determine if input_data is an image
        return isinstance(input_data, str) and input_data.endswith(
            (".jpg", ".png", ".jpeg")
        )


# Spiritual Quantum Circuit Functions (Placeholders)
def spiritual_quantum_circuit(spiritual_parameters):
    num_qubits = len(spiritual_parameters)  # Determine qubits based on parameters
    # Placeholder for quantum circuit
    qc_placeholder = f"Quantum Circuit with {num_qubits} qubits"
    return qc_placeholder


def advanced_quantum_decision_making(spiritual_parameters, problem_data):
    qc = spiritual_quantum_circuit(spiritual_parameters)
    # Additional custom operations based on problem_data
    # Placeholder
    decision = f"Decision from {qc} with data {problem_data}"
    return decision


def interpret_quantum_state(statevector, problem_data):
    # Interpretation logic here
    # Placeholder
    decision = f"Interpreted decision from statevector of length {len(statevector)}"
    return decision


if __name__ == "__main__":
    system = IntegratedMultimodalSystem()
    text_result = system.process_input("Hello world")
    print(text_result)
    # image_result = system.process_input("emoji.png")  # Would need actual image
    # print(image_result)