promptfoo vs WFGY
Side-by-side comparison of two AI agent tools
promptfooopen-source
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and
WFGYfree
WFGY is an open-source AI Troubleshooting Atlas for RAG, agents, and real-world AI workflows. Includes the 16-problem map, Global Debug Card, and WFGY 3.0. ⭐ Star to help more builders find this repo.
Metrics
| promptfoo | WFGY | |
|---|---|---|
| Stars | 18.9k | 1.7k |
| Star velocity /mo | 1.7k | 67.5 |
| Commits (90d) | — | — |
| Releases (6m) | 10 | 5 |
| Overall score | 0.7957593044797683 | 0.6560348752564751 |
Pros
- +Comprehensive testing suite covering both performance evaluation and security red teaming in a single tool
- +Multi-provider support with easy comparison between OpenAI, Anthropic, Claude, Gemini, Llama and dozens of other models
- +Strong CI/CD integration with automated pull request scanning and code review capabilities for production deployments
- +专门针对AI系统设计的故障排除框架，覆盖RAG、代理和工作流等核心场景
- +开源项目拥有活跃社区支持，GitHub上已获得1684颗星的认可
- +提供结构化的问题图和全局调试卡，将复杂的AI调试过程系统化和标准化
Cons
- -Requires API keys and credits for multiple LLM providers, which can become expensive for extensive testing
- -Command-line focused interface may have a learning curve for teams preferring GUI-based tools
- -Limited to evaluation and testing - does not provide actual LLM application development capabilities
- -专业性较强，需要一定的AI系统基础知识才能充分利用
- -针对性工具，主要适用于AI相关问题，不适合通用软件调试
- -文档和学习资料可能需要时间消化理解
Use Cases
- •Automated testing and evaluation of prompt performance across different models before production deployment
- •Security vulnerability scanning and red teaming of LLM applications to identify potential risks and compliance issues
- •Systematic comparison of model performance and cost-effectiveness to optimize AI application architecture
- •RAG系统性能调优和准确性问题诊断，如检索质量差、答案不准确等问题排查
- •AI代理行为异常调试，包括决策逻辑错误、工具调用失败等问题定位
- •复杂AI工作流故障排除，如多步骤管道中断、数据流问题和集成错误分析