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#!/usr/bin/env python3
"""
Multi-Server Performance Comparison Test for Felix Framework.
This script compares performance between single-server and multi-server
configurations to demonstrate true parallel processing benefits.
Requirements:
- Multiple LM Studio servers running on different ports
- Configuration files in config/ directory
Usage:
python examples/test_multi_server_performance.py
"""
import sys
import time
import asyncio
import statistics
from pathlib import Path
from typing import List, Dict, Any, Tuple
# Add src to path for imports
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from blog_writer import FelixBlogWriter
class PerformanceTest:
"""Test framework for comparing single vs multi-server performance."""
def __init__(self, debug_mode: bool = False):
self.debug_mode = debug_mode
self.test_topics = [
"Quantum computing applications",
"Sustainable energy solutions",
"Artificial intelligence ethics",
"Space exploration technology",
"Blockchain and cryptocurrency"
]
async def run_single_test(self, topic: str, config_path: str, test_name: str) -> Dict[str, Any]:
"""
Run a single performance test.
Args:
topic: Blog post topic
config_path: Server configuration path
test_name: Name for this test
Returns:
Test results dictionary
"""
print(f"\n{'='*60}")
print(f"π§ͺ RUNNING TEST: {test_name}")
print(f"Topic: {topic}")
print(f"Config: {config_path}")
print(f"{'='*60}")
# Create writer with specified configuration
writer = FelixBlogWriter(
server_config_path=config_path,
strict_mode=True, # Use strict mode for consistent testing
debug_mode=self.debug_mode
)
# Test connection
if not writer.test_lm_studio_connection():
return {
"error": "Connection failed",
"test_name": test_name,
"topic": topic,
"config": config_path
}
# Create team
writer.create_blog_writing_team(complexity="medium")
# Run test
start_time = time.perf_counter()
results = await writer.run_blog_writing_session_async(
topic=topic,
simulation_time=1.0
)
end_time = time.perf_counter()
total_duration = end_time - start_time
# Extract metrics
stats = results["session_stats"]
test_result = {
"test_name": test_name,
"topic": topic,
"config": config_path,
"success": results["final_output"] is not None,
"total_duration": total_duration,
"simulation_duration": stats["total_duration"],
"total_tokens": stats["total_tokens_used"],
"agents_participated": stats["agents_participated"],
"agents_created": stats["agents_created"],
"messages_processed": stats["total_messages_processed"],
"final_confidence": results["final_output"]["confidence"] if results["final_output"] else 0.0,
"llm_stats": stats.get("llm_client_stats", {}),
"content_length": len(results["final_output"]["content"]) if results["final_output"] else 0
}
# Add server-specific metrics if available
if hasattr(writer.llm_client, 'get_pool_stats'):
test_result["pool_stats"] = writer.llm_client.get_pool_stats()
print(f"β
Test completed: {total_duration:.2f}s, {test_result['total_tokens']} tokens")
return test_result
async def run_comparison_tests(self, num_iterations: int = 3) -> Dict[str, Any]:
"""
Run comprehensive comparison tests.
Args:
num_iterations: Number of test iterations per configuration
Returns:
Comparison results
"""
print(f"π STARTING MULTI-SERVER PERFORMANCE COMPARISON")
print(f"Iterations per config: {num_iterations}")
print(f"Topics: {len(self.test_topics)}")
print(f"Total tests: {len(self.test_topics) * num_iterations * 2}")
all_results = {
"single_server": [],
"multi_server": [],
"test_config": {
"num_iterations": num_iterations,
"topics": self.test_topics,
"debug_mode": self.debug_mode,
"timestamp": time.time()
}
}
# Test each topic with both configurations
for topic in self.test_topics:
print(f"\nπ― Testing topic: {topic}")
for iteration in range(num_iterations):
print(f"\n--- Iteration {iteration + 1}/{num_iterations} ---")
# Test single server
try:
single_result = await self.run_single_test(
topic,
"config/single_server_config.json",
f"Single-Server-{iteration+1}"
)
all_results["single_server"].append(single_result)
except Exception as e:
print(f"β Single server test failed: {e}")
all_results["single_server"].append({
"error": str(e),
"test_name": f"Single-Server-{iteration+1}",
"topic": topic
})
# Brief pause between tests
await asyncio.sleep(2)
# Test multi server
try:
multi_result = await self.run_single_test(
topic,
"config/server_config.json",
f"Multi-Server-{iteration+1}"
)
all_results["multi_server"].append(multi_result)
except Exception as e:
print(f"β Multi server test failed: {e}")
all_results["multi_server"].append({
"error": str(e),
"test_name": f"Multi-Server-{iteration+1}",
"topic": topic
})
# Brief pause between tests
await asyncio.sleep(2)
return all_results
def analyze_results(self, results: Dict[str, Any]) -> Dict[str, Any]:
"""
Analyze and compare test results.
Args:
results: Results from run_comparison_tests
Returns:
Analysis summary
"""
print(f"\n{'='*60}")
print(f"π ANALYZING RESULTS")
print(f"{'='*60}")
# Filter successful tests
single_success = [r for r in results["single_server"] if "error" not in r and r.get("success", False)]
multi_success = [r for r in results["multi_server"] if "error" not in r and r.get("success", False)]
print(f"Successful tests: Single={len(single_success)}, Multi={len(multi_success)}")
if not single_success or not multi_success:
return {"error": "Insufficient successful tests for comparison"}
# Calculate metrics
def calc_stats(test_list: List[Dict], metric: str) -> Dict[str, float]:
values = [t[metric] for t in test_list if metric in t]
if not values:
return {"mean": 0, "median": 0, "min": 0, "max": 0, "std": 0}
return {
"mean": statistics.mean(values),
"median": statistics.median(values),
"min": min(values),
"max": max(values),
"std": statistics.stdev(values) if len(values) > 1 else 0,
"count": len(values)
}
analysis = {
"single_server": {
"duration": calc_stats(single_success, "total_duration"),
"tokens": calc_stats(single_success, "total_tokens"),
"confidence": calc_stats(single_success, "final_confidence"),
"content_length": calc_stats(single_success, "content_length"),
"agents_participated": calc_stats(single_success, "agents_participated")
},
"multi_server": {
"duration": calc_stats(multi_success, "total_duration"),
"tokens": calc_stats(multi_success, "total_tokens"),
"confidence": calc_stats(multi_success, "final_confidence"),
"content_length": calc_stats(multi_success, "content_length"),
"agents_participated": calc_stats(multi_success, "agents_participated")
}
}
# Calculate performance improvements
improvements = {}
for metric in ["duration", "tokens", "confidence", "content_length"]:
single_mean = analysis["single_server"][metric]["mean"]
multi_mean = analysis["multi_server"][metric]["mean"]
if single_mean > 0:
if metric == "duration": # Lower is better
improvement = ((single_mean - multi_mean) / single_mean) * 100
improvements[metric] = improvement
else: # Higher is better
improvement = ((multi_mean - single_mean) / single_mean) * 100
improvements[metric] = improvement
else:
improvements[metric] = 0
analysis["improvements"] = improvements
analysis["summary"] = {
"single_tests": len(single_success),
"multi_tests": len(multi_success),
"speed_improvement": improvements.get("duration", 0),
"token_difference": improvements.get("tokens", 0),
"confidence_improvement": improvements.get("confidence", 0),
"quality_improvement": improvements.get("content_length", 0)
}
return analysis
def display_analysis(self, analysis: Dict[str, Any]):
"""Display analysis results in readable format."""
if "error" in analysis:
print(f"β Analysis Error: {analysis['error']}")
return
print(f"\n{'='*60}")
print(f"π PERFORMANCE COMPARISON RESULTS")
print(f"{'='*60}")
summary = analysis["summary"]
print(f"Tests: {summary['single_tests']} single-server, {summary['multi_tests']} multi-server")
print(f"\nπ SPEED COMPARISON:")
single_duration = analysis["single_server"]["duration"]["mean"]
multi_duration = analysis["multi_server"]["duration"]["mean"]
speed_improvement = summary["speed_improvement"]
print(f" Single-server: {single_duration:.2f}s average")
print(f" Multi-server: {multi_duration:.2f}s average")
if speed_improvement > 0:
print(f" β
Multi-server is {speed_improvement:.1f}% FASTER")
else:
print(f" β Multi-server is {abs(speed_improvement):.1f}% slower")
print(f"\nπͺ TOKEN USAGE:")
single_tokens = analysis["single_server"]["tokens"]["mean"]
multi_tokens = analysis["multi_server"]["tokens"]["mean"]
token_difference = summary["token_difference"]
print(f" Single-server: {single_tokens:.0f} tokens average")
print(f" Multi-server: {multi_tokens:.0f} tokens average")
print(f" Difference: {token_difference:.1f}%")
print(f"\nπ― QUALITY METRICS:")
single_conf = analysis["single_server"]["confidence"]["mean"]
multi_conf = analysis["multi_server"]["confidence"]["mean"]
single_length = analysis["single_server"]["content_length"]["mean"]
multi_length = analysis["multi_server"]["content_length"]["mean"]
print(f" Confidence: {single_conf:.2f} vs {multi_conf:.2f} ({summary['confidence_improvement']:+.1f}%)")
print(f" Content length: {single_length:.0f} vs {multi_length:.0f} chars ({summary['quality_improvement']:+.1f}%)")
print(f"\nπ DETAILED STATISTICS:")
print(f" Single-server duration: {single_duration:.2f}Β±{analysis['single_server']['duration']['std']:.2f}s")
print(f" Multi-server duration: {multi_duration:.2f}Β±{analysis['multi_server']['duration']['std']:.2f}s")
print(f"\nπ VERDICT:")
if speed_improvement > 10:
print("β
MULTI-SERVER PROVIDES SIGNIFICANT PERFORMANCE IMPROVEMENT")
elif speed_improvement > 0:
print("β
Multi-server provides modest performance improvement")
else:
print("β Multi-server shows no performance benefit (check server setup)")
# Server utilization analysis
multi_results = [r for r in analysis if r.get("pool_stats")]
if multi_results:
print(f"\nπ SERVER UTILIZATION:")
# This would show which servers were used most
print(" (Server utilization metrics available in detailed results)")
def save_results(self, results: Dict[str, Any], analysis: Dict[str, Any], filename: str = None):
"""Save test results and analysis to file."""
if filename is None:
timestamp = int(time.time())
filename = f"performance_comparison_{timestamp}.json"
import json
output_data = {
"test_results": results,
"analysis": analysis,
"timestamp": time.time()
}
with open(filename, 'w') as f:
json.dump(output_data, f, indent=2)
print(f"\nπΎ Results saved to: {filename}")
async def main():
"""Main performance test function."""
print("π Felix Framework Multi-Server Performance Test")
print("=" * 60)
# Check if config files exist
single_config = Path("config/single_server_config.json")
multi_config = Path("config/server_config.json")
if not single_config.exists():
print(f"β Single server config not found: {single_config}")
return
if not multi_config.exists():
print(f"β Multi server config not found: {multi_config}")
return
# Run performance tests
test_runner = PerformanceTest(debug_mode=False)
print("β‘ Running performance comparison tests...")
results = await test_runner.run_comparison_tests(num_iterations=2)
print("\nπ Analyzing results...")
analysis = test_runner.analyze_results(results)
# Display results
test_runner.display_analysis(analysis)
# Save results
test_runner.save_results(results, analysis)
print("\nπ Performance comparison complete!")
if __name__ == "__main__":
asyncio.run(main()) |