from swarms.structs.agent import Agent from typing import Dict, List class HealthcareDiagnosticSystem: def __init__(self): self.primary_diagnostician = Agent( agent_name="Primary-Diagnostician", agent_description="Primary diagnostic analysis specialist", system_prompt="""You are a primary diagnostician expert in: 1. Initial Symptom Analysis 2. Patient History Evaluation 3. Preliminary Diagnosis Formation 4. Risk Factor Assessment 5. Treatment Priority Determination""", max_loops=3, model_name="gpt-4" ) self.specialist_consultant = Agent( agent_name="Specialist-Consultant", agent_description="Specialized medical consultation expert", system_prompt="""You are a medical specialist focusing on: 1. Complex Case Analysis 2. Specialized Treatment Planning 3. Comorbidity Assessment 4. Treatment Risk Evaluation 5. Advanced Diagnostic Interpretation""", max_loops=3, model_name="gpt-4" ) self.treatment_coordinator = Agent( agent_name="Treatment-Coordinator", agent_description="Treatment planning and coordination specialist", system_prompt="""You are a treatment coordination expert specializing in: 1. Treatment Plan Development 2. Care Coordination 3. Resource Allocation 4. Recovery Timeline Planning 5. Follow-up Protocol Design""", max_loops=3, model_name="gpt-4" ) def process_case(self, patient_data: Dict) -> Dict: # Initial diagnosis primary_assessment = self.primary_diagnostician.run( f"Perform initial diagnosis: {patient_data}" ) # Specialist consultation specialist_review = self.specialist_consultant.run( f"Review case with initial assessment: {primary_assessment}" ) # Treatment planning treatment_plan = self.treatment_coordinator.run( f"Develop treatment plan based on: Primary: {primary_assessment}, Specialist: {specialist_review}" ) return { "initial_assessment": primary_assessment, "specialist_review": specialist_review, "treatment_plan": treatment_plan } # Usage diagnostic_system = HealthcareDiagnosticSystem()