promptfoo vs quivr

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

quivrfree

Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore:

Metrics

promptfooquivr
Stars18.9k39.1k
Star velocity /mo1.7k67.5
Commits (90d)
Releases (6m)100
Overall score0.79575930447976830.4264472901157703

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
  • +多LLM支持:兼容 OpenAI、Anthropic、Mistral 等主流模型,也支持本地模型部署,提供灵活的模型选择
  • +开箱即用:5行代码即可创建 RAG 系统,内置文档解析和向量化处理,大幅降低实现门槛
  • +高度可定制:支持自定义解析器、添加工具集成、互联网搜索等功能,适应不同业务需求

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
  • -固化架构:「Opinionated」设计虽然简化使用,但可能限制高度定制化需求的实现灵活性
  • -依赖外部服务:需要配置第三方 LLM API 密钥,增加了部署和维护的复杂性

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
  • 企业知识库构建:将内部文档、手册、FAQ 等资料构建成可查询的智能问答系统
  • 文档分析工具:为研究人员或内容创作者提供快速的文档检索和内容总结功能
  • AI助手集成:在现有应用中快速添加基于文档的 AI 问答功能,提升用户体验