Developing Apps with GPT-4 and ChatGPT, 2nd Edition

Chapter 5. Advancing LLM Capabilities with Frameworks, Plug-Ins, and More

This chapter explores how you can go beyond the use of the OpenAI libraries and API and make the most of existing tools. Frameworks such as LangChain and LlamaIndex have emerged with the boom of the popularity of LLMs, facilitating the development of LLM-powered applications and offering additional features to go from proof of concepts to production. We will also look at what OpenAI provides to expand the capabilities of its models: plug-ins, GPTs, and the Assistants API.

This advanced knowledge will be fundamental in developing sophisticated, cutting-edge applications that rely on LLMs.

The LangChain Framework

LangChain is a framework designed for the development and deployment of LLM-powered applications. It provides a suite of open source libraries and tooling to cover all the phases of the LLM application lifecycle.

It is an extremely popular framework, with more than 80,000 starts on GitHub, despite some criticism regarding its complexity. Frameworks for LLM application development, such as LangChain, provide layers of abstraction to help developers who are focusing on the complex aspects of their application and not on the semantics of the API.

You will find that the code integrating LangChain is much more elegant than the Project 3 example provided in Chapter 3. LangChain offers compatibility with OpenAI as well as with other private or open solutions and provides many additional possibilities, such ...