AI Agents Overview

async def agentic_process(
    case_id: str, 
    user_id: str,
    patient_name: str,
    patient_age: int,
    patient_gender: str,
    case_summary: Optional[str] = None,
    lab_files: Optional[List[Dict[str, Any]]] = None,
    radiology_files: Optional[List[Dict[str, Any]]] = None
):

class MedicalAnalysisState(TypedDict):
    # Input data
    case_input: CaseInput
    
    # Processed documents
    processed_lab_docs: List[LabDocument]
    processed_radiology_docs: List[RadiologyDocument]
    
    # Analysis results
    case_summary: Optional[CaseSummary]
    soap_note: Optional[SOAPNote]
    primary_diagnosis: Optional[Diagnosis]
    
    # Final output
    medical_insights: Optional[MedicalInsights]
    
    # Processing metadata
    processing_errors: List[str]
    processing_stage: str
    confidence_scores: Dict[str, float]

if lab_files:
    for lab_file in lab_files:
        # Process each lab file
        result = await process_pdf_async(temp_file_path)
        
if radiology_files:
    # Process all radiology files for the case
    result = await vision_agent(case_id)

confidence_scores = [
    state["case_summary"].confidence_score,
    state["soap_note"].confidence_score,
    state["primary_diagnosis"].confidence_score
]
overall_confidence = sum(confidence_scores) / len(confidence_scores)