haystack
Open-source AI orchestration framework for building production-ready LLM applications with modular pipelines and RAG.
haystack overview
Haystack by deepset is an open-source framework for building production-ready LLM applications. It provides modular pipeline architecture for retrieval-augmented generation, semantic search, question answering, and agent workflows — with built-in support for dozens of model providers, vector databases, and document stores.
Rag
haystack surfaces rag as a core capability in its published project metadata and source links.
This gives readers a starting point for evaluating whether the project fits their workflow before visiting the source repository or docs.Memory
haystack surfaces memory as a core capability in its published project metadata and source links.
This gives readers a starting point for evaluating whether the project fits their workflow before visiting the source repository or docs.When to use haystack
Personal memory
Use it as a candidate for personal memory when the project facts, license, and official links match your deployment requirements.
How it compares
Compare it with nearby memory systems by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need.
Questions
What is Haystack best used for?
Haystack excels at RAG pipelines, semantic search, document QA, and any LLM workflow that requires controlled retrieval and generation steps.
Does Haystack support vector databases?
Yes, Haystack integrates with over a dozen vector databases including Pinecone, Weaviate, Qdrant, and Milvus.
Is Haystack open source?
Yes, Haystack is open source under the Apache-2.0 license with 25K+ GitHub stars.
Can I use Haystack with any LLM provider?
Yes, Haystack supports dozens of model providers through its generator and embedder components, including OpenAI, Cohere, and local models.