Haystack Documentation
by deepset
A production-minded framework for building composable RAG and LLM search pipelines.
Overview
Haystack is an open-source framework aimed at production LLM applications, especially search and RAG. Its documentation teaches the pipeline/component model — how to wire retrievers, rankers, prompt builders, and generators into robust, branching pipelines — plus integrations with vector stores and models. It's a strong, well-engineered alternative to LangChain/LlamaIndex when you value explicit, composable pipelines.
At a Glance
- Topic
- Frameworks
- Level
- Intermediate
- Format
- Documentation
- Cost
- Free
- Duration
- Self-paced
- Provider
- deepset
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓The Haystack pipeline and component model
- ✓Building RAG and question-answering systems
- ✓Retrievers, rankers, and generators
- ✓Production-oriented, branching pipelines
Highlights
- •Production and search focused
- •Explicit, composable pipeline design
Who It’s For
Best For
- ✓Teams building production search/RAG pipelines
Prerequisites
- •Intermediate Python
FAQ
What is Haystack Documentation?
Official docs for Haystack, deepset's open-source framework for building pipelines for RAG, question answering, and semantic search.
Is Haystack Documentation free?
Haystack Documentation is free to access.
What level is Haystack Documentation for?
Haystack Documentation is aimed at a intermediate audience. Recommended background: Intermediate Python.
How long does Haystack Documentation take?
Expect roughly Self-paced. Most learners work through it at their own pace.
What will I learn from Haystack Documentation?
You'll learn: The Haystack pipeline and component model; Building RAG and question-answering systems; Retrievers, rankers, and generators; Production-oriented, branching pipelines.