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🔬 v0.2.0: Agent Evaluation System Online!

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@webup webup released this 08 Sep 06:14
· 3 commits to main since this release
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v0.2.0
e7c9394

🎉 Major Release: Comprehensive Agent Evaluation Framework

This release introduces a production-grade evaluation system that sets a new standard for ReAct agent testing and benchmarking.

🔬 Dual Evaluation Framework

Graph Trajectory Evaluation

  • LLM-as-Judge methodology with scenario-specific custom rubrics
  • Tests agent reasoning patterns and tool usage decisions across multiple scenarios
  • Automated scoring and ranking systems for objective performance measurement

Multi-turn Chat Simulation

  • Role-persona interaction testing with adversarial scenarios
  • Comprehensive conversational capability assessment
  • Professional user persona testing including polite and challenging user types

🚀 SiliconFlow Integration

  • Complete MaaS Platform Support: Native integration with China's leading open-source model platform
  • Multi-Model Benchmarking: Test across Qwen/Qwen3-8B, GLM-4-9B-0414, GLM-Z1-9B-0414 models
  • Cost-Effective Evaluation: <10B models provide excellent evaluation capabilities at minimal cost
  • Regional API Support: Seamless cn/international endpoint switching

📊 Professional Evaluation Tools

  • LangSmith Integration: Complete evaluation tracking with historical analysis
  • Structured Reporting: Detailed score extraction and performance analytics
  • Trajectory Normalization: JSON serialization-compatible evaluation processing
  • Centralized Configuration: Unified evaluation settings via config.py

📚 Comprehensive Documentation

The evaluation system is fully documented in tests/evaluations/README.md with:

  • Quick Start Guides: Get running with evaluations in minutes
  • Methodology Explanations: Deep dive into LLM-as-Judge approaches
  • Configuration References: Complete setup and customization options
  • Results Analysis: How to interpret and act on evaluation results

🛠 Enhanced Development Experience

New Make Commands:

make evals                  # Run complete evaluation suite
make eval_graph             # Graph trajectory evaluation
make eval_multiturn         # Multi-turn chat evaluation
make eval_graph_qwen        # Test specific SiliconFlow models
make eval_graph_glm         # GLM model evaluation

Environment Setup:

  • New region aliases: cn (China mainland), international (global)
  • Added SILICONFLOW_API_KEY for multi-model evaluation
  • Enhanced model configuration with provider-specific optimizations

🎯 Production-Ready Features

  • Automated CI/CD Integration: Evaluation workflows ready for production pipelines
  • Multi-Provider Testing: Compare performance across OpenAI, Anthropic, Qwen, and SiliconFlow
  • Security Testing: Adversarial user personas for robust agent validation
  • Performance Benchmarking: Quantitative metrics for agent optimization

📈 What's Next

With this evaluation foundation, teams can now:

  • Objectively measure agent performance improvements
  • Compare different model providers and configurations
  • Identify and fix agent reasoning issues before production
  • Build confidence in agent reliability through systematic testing
  • Full Documentation: Updated README.md, and README_CN.md with comprehensive v0.2.0 features
  • Roadmap: v0.2.0 milestone marked complete in ROADMAP.md with detailed achievements
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