Haystack: open-source AI orchestration framework for Python
An open-source AI orchestration framework for building LLM applications in Python, available via pip.
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Core facts
Read by a script from the official API, not rewritten by a model.
- Repository
- https://github.com/deepset-ai/haystack
- License
- Apache-2.0
- Languages
- Python
- Maintainer
- deepset-ai
- Homepage
- https://haystack.deepset.ai
- Verified
What it is
Haystack is an open-source AI orchestration framework for building LLM applications in Python. It designs modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. The project says it builds RAG systems, multimodal applications, semantic search, question answering, and autonomous agents in a transparent architecture. It defines pipelines and agent workflows where retrieval, memory, tools, and generation are transparent and traceable.
Main features
Agents can extend behavior with lifecycle hooks for guardrails and custom logic, and they track step count, token usage, and tool calls out of the box for monitoring and cost control.
It designs flexible systems with explicit control over how information is retrieved, ranked, filtered, combined, structured, and routed before it reaches the model.
One pipeline runs synchronously or asynchronously and streams token by token, and an agent can run concurrent tool calls.
Built-in components cover retrieval, indexing, tool calling, memory, and evaluation, or you can create your own, and you can add loops, branches, and conditional logic to precisely control how context moves through pipelines and agent workflows.
It integrates with OpenAI, Mistral, Anthropic, Cohere, Hugging Face, Google, Azure OpenAI, AWS Bedrock, local models, and many others, and models or infrastructure components can be swapped without rewriting the system.
Custom components can be built and shared through a consistent interface, which lets the community and third parties extend Haystack and contribute to an open ecosystem.
Getting started
The simplest way to get Haystack is via pip.
Nightly pre-releases can be installed to try the newest features.
Haystack supports multiple installation methods, including Docker images.
pip install haystack-aipip install --pre haystack-aiWho it is for
Hayhooks wraps pipelines and agents with custom logic and exposes them through HTTP endpoints or MCP. Hayhooks also supports OpenAI-compatible chat completion endpoints. The Haystack Enterprise Platform helps build, test, deploy and operate Haystack pipelines with built-in observability, collaboration, governance, and access controls.
The platform is available as a managed cloud service or as a self-hosted solution. Haystack collects anonymous usage statistics of pipeline components. The Haystack docs describe telemetry and how to opt out.
Contributors do not need to be Haystack experts to provide meaningful improvements. Contributors can contribute to the main Haystack project. Contributors can also contribute an integration.
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Sources
This page is written from the official sources below. Open them to check the original text.
- GitHub READMEhttps://github.com/deepset-ai/haystackFetched
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