Create pinecone_swarm.py

pinecone_swarm.py

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+# Import the AgentRearrange class for coordinating multiple agents
+from swarms import AgentRearrange
+
+# Import specialized medical agents for different aspects of patient care
+from multi_agent_rag.agents import (
+    diagnostic_specialist,  # Agent for diagnostic analysis
+    medical_data_extractor,  # Agent for extracting medical data
+    patient_care_coordinator,  # Agent for coordinating patient care
+    specialist_consultant,  # Agent for specialist consultation
+    treatment_planner,  # Agent for treatment planning
+)
+
+# Import database class for storing and retrieving medical documents
+from multi_agent_rag.pinecone_wrapper import PineconeManager
+
+# Initialize the SwarmRouter to coordinate the medical agents
+router = AgentRearrange(
+    name="medical-diagnosis-treatment-swarm",
+    description="Collaborative medical team for comprehensive patient diagnosis and treatment planning",
+    max_loops=1,  # Limit to one iteration through the agent flow
+    agents=[
+        medical_data_extractor,  # First agent to extract medical data
+        diagnostic_specialist,  # Second agent to analyze and diagnose
+        treatment_planner,  # Third agent to plan treatment
+        specialist_consultant,  # Fourth agent to provide specialist input
+        patient_care_coordinator,  # Final agent to coordinate care plan
+    ],
+    # Configure the document storage and retrieval system
+    memory_system=PineconeManager(api_key="", index_name="", environment="")
+    # Define the sequential flow of information between agents
+    flow=f"{medical_data_extractor.agent_name} -> {diagnostic_specialist.agent_name} -> {treatment_planner.agent_name} -> {specialist_consultant.agent_name} -> {patient_care_coordinator.agent_name}",
+)
+
+# Example usage
+if __name__ == "__main__":
+    # Run a comprehensive medical analysis task for patient Lucas Brown
+    router.run(
+        "Analyze this Lucas Brown's medical data to provide a diagnosis and treatment plan"
+    )