Haystack
Open-source framework for building production-ready search and RAG (retrieval-augmented generation) applications with LLMs.
- Actively maintained
- Well documented
- Permissive license
Overview
Haystack provides composable building blocks - document retrieval, embedding, ranking, generation - for building LLM-powered search and question-answering pipelines, with connectors to many vector databases, document stores, and model providers. It's designed around explicit, inspectable pipelines rather than a single black-box abstraction.
Haystack is a fit for teams building retrieval-augmented generation or enterprise search applications specifically, a more focused alternative to LangChain's (also in this catalog) broader general-purpose LLM application framework.
Why it's in this catalog
Catalog rating: ★★★☆☆ (3/5)
Established RAG/LLM orchestration framework, meaningful overlap with LangChain/LlamaIndex.
- Mature
- Vendor-backed
- Categories
- AI & Machine Learning
- Languages
- Python
- License
- Apache-2.0
Related Projects
LlamaIndex
MITData framework for connecting large language models to your own data - documents, databases, APIs - for retrieval-augmented applications.
Actively maintained
- AI & Machine Learning
LangChain
MITFramework for developing applications powered by large language models, agents and retrieval-augmented generation.
Actively maintained
- AI & Machine Learning
Semantic Kernel
MITMicrosoft's open-source SDK for integrating large language models into applications, with support for plugins, memory, and planning.
Actively maintained
- AI & Machine Learning
Instructor
MITLibrary for getting reliable, structured data output from LLMs using function-calling APIs and Pydantic models for validation.
Actively maintained
- AI & Machine Learning
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