Promptfoo vs RAGAS
Compare Promptfoo and RAGAS on deployment, pricing, model support, and more.
Promptfoo
- Tagline
- Open-source LLM testing and red-teaming — test prompts, evaluate outputs, catch regressions
- Description
- Promptfoo is an open-source CLI and library for testing, evaluating, and red-teaming LLM applications. Write test cases in YAML or JavaScript, run them against multiple models (GPT-4, Claude, Llama) simultaneously, and compare results in a local web UI. Supports automated red-teaming to find jailbreaks, prompt injections, and safety failures. 4,000+ GitHub stars.
- Category
- LLM Frameworks
- Pricing
- Free
- Metric
- 25,016 GitHub stars (source)
- Link
- Visit
RAGAS
- Tagline
- RAG evaluation framework — measure faithfulness, relevance, and recall of RAG pipelines
- Description
- RAGAS (Retrieval Augmented Generation Assessment) is an open-source framework for evaluating RAG pipelines. It measures key quality dimensions — faithfulness (is the answer grounded in the retrieved context?), answer relevancy (does the answer address the question?), context recall (did retrieval find all needed information?), and context precision. Integrates with LangChain, LlamaIndex, and any RAG system.
- Category
- LLM Frameworks
- Pricing
- Free
- Metric
- 15,705 GitHub stars (source)
- Link
- Visit
| Attribute | Promptfoo | RAGAS |
|---|---|---|
| Tagline | Open-source LLM testing and red-teaming — test prompts, evaluate outputs, catch regressions | RAG evaluation framework — measure faithfulness, relevance, and recall of RAG pipelines |
| Category | LLM Frameworks | LLM Frameworks |
| Pricing | Free | Free |
| Description | Promptfoo is an open-source CLI and library for testing, evaluating, and red-teaming LLM applications. Write test cases in YAML or JavaScript, run them against multiple models (GPT-4, Claude, Llama) simultaneously, and compare results in a local web UI. Supports automated red-teaming to find jailbreaks, prompt injections, and safety failures. 4,000+ GitHub stars. | RAGAS (Retrieval Augmented Generation Assessment) is an open-source framework for evaluating RAG pipelines. It measures key quality dimensions — faithfulness (is the answer grounded in the retrieved context?), answer relevancy (does the answer address the question?), context recall (did retrieval find all needed information?), and context precision. Integrates with LangChain, LlamaIndex, and any RAG system. |
| Metric | 25,016 GitHub stars (source) | 15,705 GitHub stars (source) |
| Link | Visit | Visit |