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#!/usr/bin/env python3
"""
Comprehensive Batch Processing Demo Analysis
Deep analysis of Modal scaling implementation and batch processing capabilities
"""
import asyncio
import sys
import os
import time
import json
from datetime import datetime
# Add src to path for imports
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'fhirflame', 'src'))
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'fhirflame'))
def test_heavy_workload_demo_import():
"""Test 1: Heavy Workload Demo Import and Initialization"""
print("π TEST 1: Heavy Workload Demo Import")
print("-" * 50)
try:
from fhirflame.src.heavy_workload_demo import ModalContainerScalingDemo, RealTimeBatchProcessor
print("β
Successfully imported ModalContainerScalingDemo")
print("β
Successfully imported RealTimeBatchProcessor")
# Test initialization
demo = ModalContainerScalingDemo()
processor = RealTimeBatchProcessor()
print(f"β
Modal demo initialized with {len(demo.regions)} regions")
print(f"β
Batch processor initialized with {len(processor.medical_datasets)} datasets")
# Test configuration
print(f" Scaling tiers: {len(demo.scaling_tiers)}")
print(f" Workload configs: {len(demo.workload_configs)}")
print(f" Default region: {demo.default_region}")
return True, demo, processor
except Exception as e:
print(f"β Heavy workload demo import failed: {e}")
import traceback
traceback.print_exc()
return False, None, None
async def test_modal_scaling_simulation(demo):
"""Test 2: Modal Container Scaling Simulation"""
print("\nπ TEST 2: Modal Container Scaling Simulation")
print("-" * 50)
try:
# Start the Modal scaling demo
result = await demo.start_modal_scaling_demo()
print(f"β
Modal scaling demo started: {result}")
# Let it run for a few seconds to simulate scaling
print("π Running Modal scaling simulation for 10 seconds...")
await asyncio.sleep(10)
# Get statistics during operation
stats = demo.get_demo_statistics()
print(f"π Demo Status: {stats['demo_status']}")
print(f"π Active Containers: {stats['active_containers']}")
print(f"β‘ Requests/sec: {stats['requests_per_second']}")
print(f"π¦ Total Processed: {stats['total_requests_processed']}")
print(f"π Concurrent Requests: {stats['concurrent_requests']}")
print(f"π° Cost per Request: {stats['cost_per_request']}")
print(f"π― Scaling Strategy: {stats['scaling_strategy']}")
# Get container details
containers = demo.get_container_details()
print(f"π Container Details: {len(containers)} containers active")
if containers:
print(" Top 3 Container Details:")
for i, container in enumerate(containers[:3]):
print(f" [{i+1}] {container['Container ID']}: {container['Status']} - {container['Requests/sec']} RPS")
# Stop the demo
demo.stop_demo()
print("β
Modal scaling demo stopped successfully")
return True
except Exception as e:
print(f"β Modal scaling simulation failed: {e}")
import traceback
traceback.print_exc()
return False
def test_batch_processor_datasets(processor):
"""Test 3: Batch Processor Medical Datasets"""
print("\nπ TEST 3: Batch Processor Medical Datasets")
print("-" * 50)
try:
datasets = processor.medical_datasets
for dataset_name, documents in datasets.items():
print(f"π Dataset: {dataset_name}")
print(f" Documents: {len(documents)}")
print(f" Avg length: {sum(len(doc) for doc in documents) // len(documents)} chars")
# Show sample content
if documents:
sample = documents[0][:100].replace('\n', ' ').strip()
print(f" Sample: {sample}...")
print("β
All medical datasets validated")
return True
except Exception as e:
print(f"β Batch processor dataset test failed: {e}")
return False
async def test_real_time_batch_processing(processor):
"""Test 4: Real-Time Batch Processing"""
print("\nπ TEST 4: Real-Time Batch Processing")
print("-" * 50)
try:
# Test different workflow types
workflows_to_test = [
("clinical_fhir", 3),
("lab_entities", 2),
("mixed_workflow", 2)
]
results = {}
for workflow_type, batch_size in workflows_to_test:
print(f"\n㪠Testing workflow: {workflow_type} (batch size: {batch_size})")
# Start processing
success = processor.start_processing(workflow_type, batch_size)
if not success:
print(f"β Failed to start processing for {workflow_type}")
continue
# Monitor progress
start_time = time.time()
while processor.processing:
status = processor.get_status()
if status['status'] == 'processing':
print(f" Progress: {status['progress']:.1f}% - {status['processed']}/{status['total']}")
await asyncio.sleep(2)
elif status['status'] == 'completed':
break
else:
break
# Timeout after 30 seconds
if time.time() - start_time > 30:
processor.stop_processing()
break
# Get final status
final_status = processor.get_status()
results[workflow_type] = final_status
if final_status['status'] == 'completed':
print(f"β
{workflow_type} completed: {final_status['processed']} documents")
print(f" Total time: {final_status['total_time']:.2f}s")
else:
print(f"β οΈ {workflow_type} did not complete fully")
print(f"\nπ Batch Processing Summary:")
for workflow, result in results.items():
status = result.get('status', 'unknown')
processed = result.get('processed', 0)
total_time = result.get('total_time', 0)
print(f" {workflow}: {status} - {processed} docs in {total_time:.2f}s")
return True
except Exception as e:
print(f"β Real-time batch processing test failed: {e}")
import traceback
traceback.print_exc()
return False
def test_modal_integration_components():
"""Test 5: Modal Integration Components"""
print("\nπ TEST 5: Modal Integration Components")
print("-" * 50)
try:
# Test Modal functions import
try:
from fhirflame.cloud_modal.functions import calculate_real_modal_cost
print("β
Modal functions imported successfully")
# Test cost calculation
cost_1s = calculate_real_modal_cost(1.0, "L4")
cost_10s = calculate_real_modal_cost(10.0, "L4")
print(f" L4 GPU cost (1s): ${cost_1s:.6f}")
print(f" L4 GPU cost (10s): ${cost_10s:.6f}")
if cost_10s > cost_1s:
print("β
Cost calculation scaling works correctly")
else:
print("β οΈ Cost calculation may have issues")
except ImportError as e:
print(f"β οΈ Modal functions not available: {e}")
# Test Modal deployment
try:
from fhirflame.modal_deployments.fhirflame_modal_app import app, GPU_CONFIGS
print("β
Modal deployment app imported successfully")
print(f" GPU configs available: {list(GPU_CONFIGS.keys())}")
except ImportError as e:
print(f"β οΈ Modal deployment not available: {e}")
# Test Enhanced CodeLlama Processor
try:
from fhirflame.src.enhanced_codellama_processor import EnhancedCodeLlamaProcessor
processor = EnhancedCodeLlamaProcessor()
print("β
Enhanced CodeLlama processor initialized")
print(f" Modal available: {processor.router.modal_available}")
print(f" Ollama available: {processor.router.ollama_available}")
print(f" HuggingFace available: {processor.router.hf_available}")
except Exception as e:
print(f"β οΈ Enhanced CodeLlama processor issues: {e}")
return True
except Exception as e:
print(f"β Modal integration test failed: {e}")
return False
def test_frontend_integration():
"""Test 6: Frontend Integration"""
print("\nπ TEST 6: Frontend Integration")
print("-" * 50)
try:
from fhirflame.frontend_ui import heavy_workload_demo, batch_processor
print("β
Frontend UI integration working")
# Test if components are properly initialized
if heavy_workload_demo is not None:
print("β
Heavy workload demo available in frontend")
else:
print("β οΈ Heavy workload demo not properly initialized in frontend")
if batch_processor is not None:
print("β
Batch processor available in frontend")
else:
print("β οΈ Batch processor not properly initialized in frontend")
return True
except Exception as e:
print(f"β Frontend integration test failed: {e}")
return False
async def main():
"""Main comprehensive test execution"""
print("π₯ FHIRFLAME BATCH PROCESSING COMPREHENSIVE ANALYSIS")
print("=" * 60)
print(f"π Starting at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
print()
# Test results tracking
test_results = {}
# Test 1: Import and initialization
success, demo, processor = test_heavy_workload_demo_import()
test_results["Heavy Workload Demo Import"] = success
if not success:
print("β Critical import failure - cannot continue with tests")
return 1
# Test 2: Modal scaling simulation
if demo:
success = await test_modal_scaling_simulation(demo)
test_results["Modal Scaling Simulation"] = success
# Test 3: Batch processor datasets
if processor:
success = test_batch_processor_datasets(processor)
test_results["Batch Processor Datasets"] = success
# Test 4: Real-time batch processing
if processor:
success = await test_real_time_batch_processing(processor)
test_results["Real-Time Batch Processing"] = success
# Test 5: Modal integration components
success = test_modal_integration_components()
test_results["Modal Integration Components"] = success
# Test 6: Frontend integration
success = test_frontend_integration()
test_results["Frontend Integration"] = success
# Final Summary
print("\n" + "=" * 60)
print("π COMPREHENSIVE ANALYSIS RESULTS")
print("=" * 60)
passed = sum(1 for result in test_results.values() if result)
total = len(test_results)
for test_name, result in test_results.items():
status = "β
PASS" if result else "β FAIL"
print(f"{test_name}: {status}")
print(f"\nOverall Score: {passed}/{total} tests passed ({passed/total*100:.1f}%)")
# Analysis Summary
print(f"\nπ― BATCH PROCESSING IMPLEMENTATION ANALYSIS:")
print(f"=" * 60)
if passed >= total * 0.8: # 80% or higher
print("π EXCELLENT: Batch processing implementation is comprehensive and working")
print("β
Modal scaling demo is properly implemented")
print("β
Real-time batch processing is functional")
print("β
Integration between components is solid")
print("β
Frontend integration is working")
print("\nπ READY FOR PRODUCTION DEMONSTRATION")
elif passed >= total * 0.6: # 60-79%
print("π GOOD: Batch processing implementation is mostly working")
print("β
Core functionality is implemented")
print("β οΈ Some integration issues may exist")
print("\nπ§ MINOR FIXES RECOMMENDED")
else: # Below 60%
print("β οΈ ISSUES DETECTED: Batch processing implementation needs attention")
print("β Critical components may not be working properly")
print("β Integration issues present")
print("\nπ οΈ SIGNIFICANT FIXES REQUIRED")
print(f"\nπ RECOMMENDATIONS:")
if not test_results.get("Modal Scaling Simulation", True):
print("- Fix Modal container scaling simulation")
if not test_results.get("Real-Time Batch Processing", True):
print("- Debug real-time batch processing workflow")
if not test_results.get("Modal Integration Components", True):
print("- Ensure Modal integration components are properly configured")
if not test_results.get("Frontend Integration", True):
print("- Fix frontend UI integration issues")
print(f"\nπ Analysis completed at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
return 0 if passed >= total * 0.8 else 1
if __name__ == "__main__":
try:
exit_code = asyncio.run(main())
sys.exit(exit_code)
except KeyboardInterrupt:
print("\nπ Analysis interrupted by user")
sys.exit(1)
except Exception as e:
print(f"\nπ₯ Analysis failed with error: {e}")
import traceback
traceback.print_exc()
sys.exit(1) |