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