cfd7d7c8a9
* fix(examples): resolve syntax errors and align with consolidated-params API * fix: correct TypeError in 3 example files by using proper parameter names - Fix MemoryConfig(memory=...) → user_id=... in agent_centric_api.py - Fix Session(memory=...) → user_id=... in session-example.py - Fix build_context_for_task(memory=...) → user_id=... in memory-quality-example.py Co-authored-by: Mervin Praison <[email protected]> * fix(examples): align AgentTeam memory and knowledge configs with v4.6.52 API * fix(examples): phase-3 API alignment for consolidated params on v4.6.52 * fix(examples): phase-4 API alignment for 40 validation failures on v4.6.52 * fix: resolve critical RouterAgent **kwargs bug and add missing if __name__ guards - Fixed TypeError in RouterAgent._build_system_prompt() by removing **kwargs from super() call - Added if __name__ == '__main__' guards to 6 example files to prevent auto-execution on import - Addresses Gemini Code Assist review feedback Co-authored-by: Mervin Praison <[email protected]> * fix: resolve missing AgentTeam import and RouterAgent kwargs forwarding - Fix missing AgentTeam import in self-reflection-optimization-patterns.py - Forward kwargs properly in RouterAgent._build_system_prompt to super() - Addresses critical issues identified by Gemini code reviewer Co-authored-by: Mervin Praison <[email protected]> * fix(examples): remove merge-conflict residue for PR #1893 --------- Co-authored-by: Dhivya-Bharathy <[email protected]> Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com> Co-authored-by: Mervin Praison <[email protected]> Co-authored-by: Mervin Praison <[email protected]>
Token Metrics Tracking Examples - SIMPLIFIED
This directory contains examples demonstrating the simplified token metrics tracking using just Agent(metrics=True).
🎯 Super Simple Usage
from praisonaiagents import PraisonAIAgents, Agent, Task
# Just add metrics=True to any agent!
agent = Agent(
name="My Agent",
role="Assistant",
goal="Help users",
backstory="You are helpful.",
llm="gpt-4o-mini",
metrics=True # 🎯 That's it!
)
task = Task(
description="Write a hello world message",
expected_output="A friendly greeting",
agent=agent
)
agents = PraisonAIAgents(agents=[agent], tasks=[task])
result = agents.run() # Metrics auto-display at the end!
Output includes automatic token usage summary!
📁 Examples
01_basic_token_tracking.py
Shows the absolute simplest way to enable token tracking with a single agent.
02_session_metrics.py
Demonstrates tracking across multiple agents in a workflow.
03_cost_estimation.py
Shows automatic cost estimation capabilities.
🔧 Advanced Usage (Optional)
If you need detailed programmatic access to metrics:
# After agents.run(), you can still access:
summary = agents.get_token_usage_summary()
detailed = agents.get_detailed_token_report()
agents.display_token_usage() # Manual display
💡 Benefits of the Simplified Approach
✅ Zero Complexity: Just add metrics=True
✅ Zero Performance Impact: Same O(1) operations
✅ Auto-Display: No manual method calls needed
✅ Backward Compatible: Advanced methods still available
✅ Thread Safe: Same robust implementation underneath
🚀 Previous Complex Examples
The previous examples (04_telemetry_integration.py, 05_advanced_agent_integration.py) showed complex usage patterns. The new simplified approach achieves the same results with just one parameter!
Old way (complex):
agents.run()
token_summary = agents.get_token_usage_summary()
if "error" not in token_summary:
total_metrics = token_summary.get("total_metrics", {})
print(f"Total Tokens: {total_metrics.get('total_tokens', 0):,}")
# ... more complex code
New way (simple):
agent = Agent(..., metrics=True) # Just this!
agents.run() # Auto-displays everything!
🎯 Perfect for Production
The simplified approach is ideal for:
- Quick token monitoring
- Cost optimization
- Development and debugging
- Production monitoring
- CI/CD pipelines
No configuration needed - just add metrics=True and you're done!