Haystack vs Ragas

Developers should learn Haystack when building applications that require intelligent document retrieval, such as chatbots, enterprise search engines, or AI assistants that need to answer questions based on specific knowledge bases meets developers should learn and use ragas when building or optimizing rag systems, such as chatbots, question-answering tools, or document-based ai assistants, to ensure reliable and accurate outputs. Here's our take.

Haystack

Nice Pick

Developers should learn Haystack when building applications that require intelligent document retrieval, such as chatbots, enterprise search engines, or AI assistants that need to answer questions based on specific knowledge bases

Pros

• It is particularly useful for implementing RAG systems to reduce hallucinations in LLMs by grounding responses in retrieved documents, making it ideal for domains like customer support, legal research, or technical documentation
• Related to: natural-language-processing, retrieval-augmented-generation

Cons

• Specific tradeoffs depend on your use case

Ragas

Developers should learn and use Ragas when building or optimizing RAG systems, such as chatbots, question-answering tools, or document-based AI assistants, to ensure reliable and accurate outputs

Pros

• It is particularly useful during development, testing, and deployment phases to benchmark performance against industry standards and iterate on improvements based on quantitative feedback
• Related to: retrieval-augmented-generation, python

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. Haystack is a framework while Ragas is a tool. We picked Haystack based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Haystack wins

Based on overall popularity. Haystack is more widely used, but Ragas excels in its own space.