Wrap-up!

Developing LLM Applications with LangChain

Jonathan Bennion

AI Engineer & LangChain Contributor

LangChain's core components

A selection of the core LangChain components: LLMs, prompts, retrievers, agents, and chains.

Developing LLM Applications with LangChain

Chains and agents

An agent making a decision about which tool to use based on the user's input.

Developing LLM Applications with LangChain

Retrieval Augmented Generation (RAG)

A typical RAG workflow.

Developing LLM Applications with LangChain

LangChain Hub

The LangChain Hub.

Access the LangChain Hub at: https://smith.langchain.com/hub

Developing LLM Applications with LangChain

The README file from the LangChain templates GitHub repository.

Developing LLM Applications with LangChain

The LangChain ecosystem

The LangChain logo

LangSmith: troubleshooting and evaluating applications

LangServe: deploying applications

LangGraph: multi-agent knowledge graphs

Developing LLM Applications with LangChain

Let's practice!

Developing LLM Applications with LangChain

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