haystack-ai
LLM framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data.
Decision gist · record as of 2026-08-14
Yes. Haystack is a mature, actively maintained framework (Apache-2.0, production-stable status, 26210 GitHub stars, OpenSSF Best Practices certified) with low install friction and no known vulnerabilities. It is well-suited for anyone building production LLM applications who needs modular, vendor-agnostic orchestration with explicit control over retrieval and generation.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Some components may require additional dependencies like openai for provider integration.
- Low install friction with a pure-Python wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions. Suitable for proprietary applications.
last release 2026-07-20 (25 days) · last repo commit 2026-08-14 · 26,210 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,059,625 downloads/mo, #4,422 on PyPI
Alternatives
Verify before relying
pip install haystack-ai
from haystack import Pipeline
from haystack.components.retrievers.in_memory import InMemoryBM25Retriever
pipeline = Pipeline()
pipeline.add_component("retriever", InMemoryBM25Retriever())- Whether all runtime dependencies are required for basic usage or only for specific integrations
- Performance characteristics and scalability limits for production deployments
- Specific vector database and model provider integrations available beyond those listed in dependencies
What it is and what it does
Haystack is a framework for composing LLM applications as explicit, transparent pipelines and agent workflows. It provides built-in components for retrieval, indexing, tool calling, memory, and evaluation, while remaining model- and vendor-agnostic—you can integrate with OpenAI, Mistral, Anthropic, Cohere, Hugging Face, Azure OpenAI, AWS Bedrock, or local models and swap them without rewriting your system.
The framework emphasizes modular design and deep customization: you build systems by connecting components into pipelines with explicit control over how context flows through retrieval, ranking, filtering, routing, and generation stages. It supports both traditional RAG systems and autonomous agents with loops, branches, and conditional logic. Core dependencies include pydantic, jinja2, httpx, and openai for provider integration.
Use it for
- Build retrieval-augmented generation systems that combine document retrieval with LLM generation for question answering
- Create semantic search applications that rank and retrieve relevant documents from large collections
- Design autonomous agent workflows with tool calling, memory, and multi-step reasoning loops
- Develop multimodal applications that process and reason over text, images, and structured data
- Prototype and experiment with different LLM providers and retrieval strategies without rewriting application code
- Deploy production-ready LLM pipelines with transparent, auditable control flow and error handling
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Haystack is a mature, actively maintained framework (Apache-2.0, production-stable status, 26210 GitHub stars, OpenSSF Best Practices certified) with low install friction and no known vulnerabilities. It is well-suited for anyone building production LLM applications who needs modular, vendor-agnostic orchestration with explicit control over retrieval and generation.
Install
haystack-ai on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Active maintenance with a recent release and strong community signals: 26210 GitHub stars and over a million monthly downloads. Supports Python 3.10 through 3.14.
Requires Python 3.10 or later. Some components may require additional dependencies like openai for provider integration.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions. Suitable for proprietary applications.
Quickstart
pip install haystack-ai
from haystack import Pipeline
from haystack.components.retrievers.in_memory import InMemoryBM25Retriever
pipeline = Pipeline()
pipeline.add_component("retriever", InMemoryBM25Retriever())Verify before relying
- Whether all runtime dependencies are required for basic usage or only for specific integrations
- Performance characteristics and scalability limits for production deployments
- Specific vector database and model provider integrations available beyond those listed in dependencies
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 18 packagesdocstring-parserfiletypehttpxjinja2jsonschemalazy-importsmarkupsafemore-itertoolsnetworkxnumpyopenaiposthogpydanticpython-dateutilpyyamltenacitytqdmtyping-extensions |
| Maintenance | Actively maintained 25 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,059,625 / month, #4,422 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: Science/ResearchLicense :: Freely DistributableLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: haystack_ai-3.0.0-py3-none-any.whl
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See also farm-haystack · haystack-experimental · openinference-instrumentation-haystack · opentelemetry-instrumentation-haystack · django-haystack · opik · cocoindex · llama-index · deepeval · application-file-scanner