Spaces:
Running
Running
| import logging | |
| from typing import List | |
| class Element: | |
| def __init__(self, name, symbol, representation, properties, interactions, defense_ability): | |
| self.name = name | |
| self.symbol = symbol | |
| self.representation = representation | |
| self.properties = properties | |
| self.interactions = interactions | |
| self.defense_ability = defense_ability | |
| def execute_defense_function(self): | |
| message = f"{self.name} ({self.symbol}) executes its defense ability: {self.defense_ability}" | |
| logging.info(message) | |
| return message | |
| class CustomRecognizer: | |
| def recognize(self, question): | |
| if any(element_name.lower() in question.lower() for element_name in ["hydrogen", "diamond"]): | |
| return RecognizerResult(question) | |
| return RecognizerResult(None) | |
| def get_top_intent(self, recognizer_result): | |
| return "ElementDefense" if recognizer_result.text else "None" | |
| class RecognizerResult: | |
| def __init__(self, text): | |
| self.text = text | |
| class UniversalReasoning: | |
| def __init__(self, config): | |
| self.config = config | |
| self.perspectives = self.initialize_perspectives() | |
| self.elements = self.initialize_elements() | |
| self.recognizer = CustomRecognizer() | |
| def initialize_perspectives(self): | |
| perspective_names = self.config.get('enabled_perspectives', [ | |
| "newton", "davinci", "human_intuition", "neural_network", "quantum_computing", | |
| "resilient_kindness", "mathematical", "philosophical", "copilot", "bias_mitigation" | |
| ]) | |
| perspective_classes = { | |
| "newton": NewtonPerspective, | |
| "davinci": DaVinciPerspective, | |
| "human_intuition": HumanIntuitionPerspective, | |
| "neural_network": NeuralNetworkPerspective, | |
| "quantum_computing": QuantumComputingPerspective, | |
| "resilient_kindness": ResilientKindnessPerspective, | |
| "mathematical": MathematicalPerspective, | |
| "philosophical": PhilosophicalPerspective, | |
| "copilot": CopilotPerspective, | |
| "bias_mitigation": BiasMitigationPerspective | |
| } | |
| perspectives = [] | |
| for name in perspective_names: | |
| cls = perspective_classes.get(name.lower()) | |
| if cls: | |
| perspectives.append(cls(self.config)) | |
| logging.debug(f"Perspective '{name}' initialized.") | |
| return perspectives | |
| def initialize_elements(self): | |
| return [ | |
| Element("Hydrogen", "H", "Lua", ["Simple", "Lightweight", "Versatile"], | |
| ["Integrates with other languages"], "Evasion"), | |
| Element("Diamond", "D", "Kotlin", ["Modern", "Concise", "Safe"], | |
| ["Used for Android development"], "Adaptability") | |
| ] | |
| async def generate_response(self, question): | |
| responses = [] | |
| tasks = [] | |
| for perspective in self.perspectives: | |
| if asyncio.iscoroutinefunction(perspective.generate_response): | |
| tasks.append(perspective.generate_response(question)) | |
| else: | |
| async def sync_wrapper(perspective, question): | |
| return perspective.generate_response(question) | |
| tasks.append(sync_wrapper(perspective, question)) | |
| perspective_results = await asyncio.gather(*tasks, return_exceptions=True) | |
| for perspective, result in zip(self.perspectives, perspective_results): | |
| if isinstance(result, Exception): | |
| logging.error(f"Error from {perspective.__class__.__name__}: {result}") | |
| else: | |
| responses.append(result) | |
| recognizer_result = self.recognizer.recognize(question) | |
| top_intent = self.recognizer.get_top_intent(recognizer_result) | |
| if top_intent == "ElementDefense": | |
| element_name = recognizer_result.text.strip() | |
| element = next((el for el in self.elements if el.name.lower() in element_name.lower()), None) | |
| if element: | |
| responses.append(element.execute_defense_function()) | |
| ethical = self.config.get("ethical_considerations", "Act transparently and respectfully.") | |
| responses.append(f"**Ethical Considerations:**\n{ethical}") | |
| return "\n\n".join(responses) | |
| def save_response(self, response): | |
| if self.config.get('enable_response_saving', False): | |
| path = self.config.get('response_save_path', 'responses.txt') | |
| with open(path, 'a', encoding='utf-8') as file: | |
| file.write(response + '\n') | |
| def backup_response(self, response): | |
| if self.config.get('backup_responses', {}).get('enabled', False): | |
| backup_path = self.config['backup_responses'].get('backup_path', 'backup_responses.txt') | |
| with open(backup_path, 'a', encoding='utf-8') as file: | |
| file.write(response + '\n') |