Haystack: Open-Source AI Framework for Production Ready Agents, RAG (opens in new tab)

People who name projects, please think very carefully if you want to use "Haystack" as the name of anything. There are literally thousands upon thousands of both overlapping and completely different products, projects, bands, initiatives, efforts, and so on with that name and all the possible variants you can think of (Haystax, Heystack, Heystax, Hay Stak, and so on).

And no, you probably won't be the first project with that name in whatever market/vertical/milieu that you are working in.

I found half a dozen different "Haystack" products and companies working in AI in 10 seconds of googling.

Please make it stop.

> Haystack collects anonymous usage statistics of pipeline components. We receive an event every time these components are initialized. This way, we know which components are most relevant to our community.

For an EU based company, this stands out.

its good that there is a competition in framework space, but does anyone have holistic view or opinions about their differences and where they shine?

For example,

* there is LangChain and LangGraph - used a lot, but framework bloat is hated as well

* mastra - for typescript projects

* pydantic, agno, strands, openai agents sdk, claude agents sdk, and so on and on and on

RAG and agents are increasingly critical abstractions for production LLM systems. Having production-grade open-source implementations available helps teams move beyond prototypes into real deployments without vendor constraints.

I've experience using it with clients on several small to large projects. It's has advantages and disadvantages, as every framework.

Clients choose it because it's EU-based company.

I remember haystack being completely unusable for extractive QA 2 years ago. I wonder if it's the same package.

RubyLLM is where its at.

deepset? more like deadseek.

no, thanks, never going to use that.