1
LangChain
The most widely used framework for building LLM apps in Python and JS.
Pros
- +Huge integration catalog
- +Active community
- +LangGraph for stateful flows
Cons
- -API churn
- -Abstraction overhead
Best LLM Frameworks
LLM frameworks give you the plumbing for prompts, retrieval, tool use, and chains so you do not rewrite the same wiring in every project. Heavy abstractions can hide what is happening, so weigh ergonomics against control before you commit.
2
LlamaIndex
RAG-first framework with strong document loaders and indexes.
Pros
- +Best-in-class RAG primitives
- +Great for knowledge bases
- +Solid docs
Cons
- -Less general than LangChain
- -Naming churn
3
Haystack
deepset's production pipeline framework for search and RAG.
Pros
- +Pipeline-first design
- +Production-grade tooling
- +Open source
Cons
- -Steeper learning curve
- -Smaller community
4
Semantic Kernel
Microsoft's SDK for plugging LLMs into C#, Python, and Java apps.
Pros
- +First-class C# support
- +Enterprise-friendly
- +Plugin model
Cons
- -MS-flavored
- -Less momentum than LangChain
Related Terms
Concepts you will run into when working with llm frameworks.
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