LangChain has emerged as a robust framework for constructing functions that leverage massive language fashions (LLMs). Whether or not youāre engaged on chatbots š¤, serps š, or AI-driven assistants š§ , LangChain offers important instruments to streamline improvement. On this weblog, we are going to discover three core ideas of LangChain: Chains, Brokers, and Retrieval Methods, that are essential for constructing environment friendly AI functions.
Chains are sequences of steps the place the output of 1 element serves because the enter for the subsequent. In LangChain, chains allow builders to construct structured workflows involving LLMs, exterior APIs, and databases.
- š Easy Chains: A primary sequential move the place every step processes the enter and passes it to the subsequent.
- š Sequential Chains: A number of chains linked collectively to create a extra complicated workflow.
- š LlamaIndex Chains: Combine LLMs with structured information sources.
- š Customized Chains: Builders can outline their very own logic for chaining totally different features.
