#1717th of 24 in Agent frameworks and SDKs
haystack
Python framework for building RAG pipelines and agents from modular components
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- Stars
- 26.7k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Python
Missed the latest GitHub check; these facts may be older.
Overview
Haystack is a Python framework for composing LLM applications as pipelines of components covering retrieval, routing, memory, tool calling and generation. One Pipeline runs sync or async and streams tokens, and the Agent class supports lifecycle hooks and concurrent tool calls. It integrates with OpenAI, Anthropic, Mistral, Cohere, Hugging Face, Google, Azure OpenAI, AWS Bedrock and local models.
Who it is for: Python developers building production RAG systems and agents
Strengths
- Pipelines support loops, branches and conditional routing, so context flow is explicit and traceable
- Agent hooks (before_llm, before_tool, on_exit) plus step_count and token_usage tracking
- Model-agnostic: many hosted providers and local models, swappable without rewriting pipelines
- Installs with pip install haystack-ai; Apache-2.0 licensed
Weaknesses
- Collects anonymous component-usage telemetry by default; opt-out is documented separately
- Serving as REST or MCP needs the separate Hayhooks project
- Governance, access controls and managed observability are in the paid Enterprise Platform
- Many integrations live in a separate haystack-core-integrations repo
What it needs
- GPU optional
- Needs Python, LLM provider or local model
- Models: OpenAI, Anthropic, Mistral, Cohere, Hugging Face
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