Haystack
LLM framework — RAG, question answering, semantic search
📋 Overview
Haystack is an open-source LLM framework from deepset that provides RAG, question answering, and semantic search — with a pipeline-based architecture. Unlike LangChain (which is chain-based), Haystack uses a pipeline architecture where components are connected in a directed graph. It provides a comprehensive solution for modern AI workflows.
✨ Key Features
- •20K+ GitHub stars — pipeline-based LLM framework
- •RAG, question answering, semantic search
- •Pipeline architecture
- •Component swapping
- •Apache 2.0 licensed
- •Active community and development
🎯 The Problem It Solves
Building RAG applications requires connecting multiple components (retrievers, readers, generators). Haystack provides a pipeline architecture for this.
🔧 How It Works
Haystack defines pipelines where components (retrievers, readers, generators) are connected in a directed graph. Data flows through the pipeline — question goes in, answer comes out. Components can be swapped easily.
🚀 Installation & Quick Start
Installation
See websiteQuick Start
- See documentation
✅ Pros
- •Best pipeline architecture
- •Component swapping
- •Apache 2.0 licensed
- •Active community
- •Comprehensive documentation
- •Production-ready
❌ Cons
- •Smaller community than LangChain
- •Pipeline concept learning curve
- •Documentation sparse
💬 Practitioner Verdict
“Haystack is the best pipeline-based LLM framework — the architecture is genuinely differentiated. The trade-off: smaller community than LangChain, the pipeline concept has a learning curve, and the documentation is sparse. For teams that need a pipeline-based RAG framework, Haystack is the default.”
Self-Hosted (Free)
Open source, MIT/Apache licensed. Run it yourself.
⭐ Star & Clone on GitHubFree forever. Your infrastructure, your data.
📊 Specifications
- Language
- Python
- License
- Apache-2.0
- Platform
- Linux, macOS, Windows
- Supported Models
- REST API, CLI
💰 Pricing Reality
100% free Apache 2.0. No paid tier.