Haystack: Build Enterprise-Grade AI Apps in Hours, Not Months
Production-ready AI orchestration framework for startup founders building complex LLM applications, conversational systems, and semantic search without deep machine learning expertise.
25,438 stars2,822 forksMDXUpdated 6/2/2026100% free · open source
What it does
Helps you build complex AI applications with modular, production-ready pipelines that handle everything from data retrieval to language generation without requiring deep ML engineering skills.
When to use it
•Creating enterprise search systems with semantic document retrieval
•Building conversational AI agents with context-aware memory and routing
•Developing RAG (Retrieval-Augmented Generation) applications with custom knowledge bases
Quick start
1Install via pip: pip install haystack-ai
2Set up a document store (like Elasticsearch or FAISS) to manage your knowledge base
3Create a retrieval pipeline that connects your documents to an LLM for intelligent querying
4Configure and test your pipeline with sample documents and queries
Ready-to-paste prompt
from haystack import Pipeline
pipeline = Pipeline()
pipeline.add_node(retriever, name='retriever', inputs=['Query'])
pipeline.add_node(reader, name='reader', inputs=['retriever'])
result = pipeline.run(query='What are the key benefits of AI for startups?')
Topics
agent
agents
ai
gemini
generative-ai
gpt-4
information-retrieval
large-language-models
llm
machine-learning
nlp
orchestration
python
pytorch
question-answering
rag
retrieval-augmented-generation
semantic-search
summarization
transformers
What's inside — free to inspect
No purchase needed
Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.
14
top-level files
11
folders
97.4M
repo size
Apache-2.0
license
Key files
.pre-commit-config.yaml
AGENTS.md
README.md
File tree
.github/
docker/
docs-website/
e2e/
examples/
haystack/
images/
pydoc/
releasenotes/
scripts/
test/
.gitignore
.pre-commit-config.yaml
AGENTS.md
CITATION.cff
CLAUDE.md
code_of_conduct.txt
CONTRIBUTING.md
LICENSE
license-header.txt
licenserc.toml
pyproject.toml
README.md
SECURITY.md
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Details
Creator
deepset-ai
Language
MDX
Category
automation
Published
11/14/2019
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