mirror of
https://github.com/MervinPraison/PraisonAI.git
synced 2026-11-08 01:08:39 -10:00
Mervin Praison
6a96a17fdf
## Fixes 1. ChatWidget.compose() now yields empty generator instead of None 2. Added 7 missing slash commands: /tokens, /plan, /map, /undo, /diff, /commit, /tools ## Commands Added - /tokens - Show token usage breakdown - /plan - Show/create task plans - /map - Show repository map - /undo - Undo last change - /diff - Show diff of changes - /commit - Commit changes - /tools - Show available tools 31 tests passing
72 lines
2.0 KiB
Python
72 lines
2.0 KiB
Python
"""
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Basic Profiling Example for PraisonAI
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This example demonstrates how to use the unified profiler programmatically
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to measure agent performance.
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Run with:
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python basic_profiling.py
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"""
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import os
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# Ensure API key is set
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if not os.environ.get("OPENAI_API_KEY"):
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print("Please set OPENAI_API_KEY environment variable")
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exit(1)
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from praisonai.cli.execution import (
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ExecutionRequest,
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Profiler,
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ProfilerConfig,
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)
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def main():
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"""Run a profiled query and display results."""
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# Configure profiler (Layer 1 = basic profiling with function stats)
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config = ProfilerConfig(
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layer=1, # 0=minimal, 1=basic, 2=deep
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limit=15, # Show top 15 functions
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show_callers=False, # Set True for caller info (layer 2)
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show_callees=False, # Set True for callee info (layer 2)
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)
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# Create execution request
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request = ExecutionRequest(
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prompt="What is 2+2?",
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agent_name="ProfiledAgent",
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)
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# Run profiled query
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print("🔬 Running profiled query...")
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profiler = Profiler(config)
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result, report = profiler.profile_sync(request)
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# Print formatted report
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print("\n" + report.to_text())
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# Access timing data programmatically
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print("\n📊 Timing Summary:")
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print(f" Imports: {report.timing.imports_ms:>10.2f} ms")
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print(f" Agent Init: {report.timing.agent_init_ms:>10.2f} ms")
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print(f" Execution: {report.timing.execution_ms:>10.2f} ms")
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print(f" Total: {report.timing.total_ms:>10.2f} ms")
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# Show top 5 functions
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if report.functions:
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print("\n🔥 Top 5 Functions by Cumulative Time:")
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for i, func in enumerate(report.functions[:5], 1):
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print(f" {i}. {func.name}: {func.cumulative_time_ms:.2f}ms")
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# Show response
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print(f"\n💬 Response: {result.output}")
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# Export to JSON
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print("\n📄 JSON Export available via: report.to_json()")
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if __name__ == "__main__":
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main()
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