Building production AI applications requires more than just an API key. LLM frameworks
provide the scaffolding for retrieval-augmented generation (RAG), tool use, memory management,
agent orchestration, prompt chaining, and deployment — so you can focus on building your
application rather than reinventing the infrastructure.
This guide covers the best open-source LLM frameworks and libraries for
building AI applications in Python — from the dominant frameworks like LangChain and LlamaIndex
to emerging challengers like DSPy and Haystack. Includes GitHub stars, language support,
primary use cases, and honest assessments of where each framework shines.
Loading tools…
Frequently Asked Questions
LangChain is the most popular LLM framework with the most tutorials, examples,
and community support — the best starting point for beginners. It abstracts the complexity of
chaining LLM calls, connecting to vector stores, and building retrieval-augmented generation
(RAG) systems. LlamaIndex is the second best choice, especially for RAG.
LangChain is a general-purpose LLM application framework for building agents,
chains, and complex workflows. LlamaIndex (formerly GPT Index) specialises
in data ingestion and retrieval — it excels at connecting LLMs to your own data sources for
RAG applications. Many developers use both together, with LlamaIndex handling data and
LangChain handling orchestration.
Yes — LangChain, LlamaIndex, Haystack,
DSPy, and most LLM frameworks are open-source and free. You only pay for the
underlying LLM API calls (OpenAI, Anthropic, etc.). Many frameworks also have optional paid
cloud products for production deployments with observability and managed hosting.
DSPy (Declarative Self-improving Python) from Stanford is a framework for
optimising LLM pipelines — instead of manually writing prompts, you define what your program
should do and DSPy automatically optimises the prompts and few-shot examples for you.
Use it when you care deeply about prompt quality and want to tune your pipeline systematically
rather than through trial and error.
LangGraph (part of the LangChain ecosystem) is the best framework for building
stateful, multi-step AI agents with complex control flows and human-in-the-loop capabilities.
CrewAI is the best for multi-agent collaboration workflows. See our
Best AI Agent Frameworks guide for a full comparison.