class ScientificAgent:
    def __init__(self, domain, llm_model):
        self.domain = domain
        self.llm = llm_model
        self.memory = PersistentMemory()
        self.tools = ToolRegistry()
        
    def generate_hypotheses(self, research_goal):
        """Generate multiple research hypotheses"""
        context = self.memory.retrieve_relevant_knowledge(research_goal)
        literature = self.tools.literature_search(research_goal)
        
        prompt = f"""
        Research Goal: {research_goal}
        Context: {context}
        Recent Literature: {literature}
        
        Generate 5 novel, testable hypotheses addressing this research goal.
        For each hypothesis, provide:
        1. Scientific rationale
        2. Experimental approach
        3. Expected outcomes
        4. Potential limitations
        """
        
        hypotheses = self.llm.generate(prompt)
        return self.rank_hypotheses(hypotheses)
    
    def design_experiment(self, hypothesis):
        """Create detailed experimental protocol"""
        tools_needed = self.identify_required_tools(hypothesis)
        protocol = self.generate_protocol(hypothesis, tools_needed)
        return self.optimize_protocol(protocol)
    
    def execute_workflow(self, research_goal):
        """Complete autonomous research workflow"""
        hypotheses = self.generate_hypotheses(research_goal)
        
        for hypothesis in hypotheses[:3]:  # Test top 3
            experiment = self.design_experiment(hypothesis)
            results = self.execute_experiment(experiment)
            analysis = self.analyze_results(results, hypothesis)
            self.memory.store_findings(hypothesis, experiment, results, analysis)
            
        return self.synthesize_conclusions()


# Usage example
agent = ScientificAgent(domain="materials_science", llm_model="gpt-4")
results = agent.execute_workflow("Develop high-efficiency solar cell materials")