LangChain, LlamaIndex, Semantic Kernel, and Haystack all help you to construct retrieval-augmented generation and other AI-enabled apps using your favorite large language models.
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Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more reliable system, one that is much less likely to go off the rails and “hallucinate,” which is a relatively nice way of describing LLMs that bullshit you. Connect RAG systems to software that can take actions, even indirect actions like sending emails, and you may have something useful: Agents. These connections, however, don’t spring into being fully grown from their father’s forehead. You need a framework that ties the components together and orchestrates them.
What are LLM application frameworks?
LLM application frameworks are basically plumbing, or, if you like fancier and more specific words, orchestration providers. In a RAG application, for example, LLM application …