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Generative AI with LangChain

You're reading from   Generative AI with LangChain Build large language model (LLM) apps with Python, ChatGPT, and other LLMs

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781835083468
Length 368 pages
Edition 1st Edition
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Author (1):
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Ben Auffarth Ben Auffarth
Author Profile Icon Ben Auffarth
Ben Auffarth
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Table of Contents (13) Chapters Close

Preface 1. What Is Generative AI? 2. LangChain for LLM Apps FREE CHAPTER 3. Getting Started with LangChain 4. Building Capable Assistants 5. Building a Chatbot Like ChatGPT 6. Developing Software with Generative AI 7. LLMs for Data Science 8. Customizing LLMs and Their Output 9. Generative AI in Production 10. The Future of Generative Models 11. Other Books You May Enjoy
12. Index

Exploring API model integrations

Before properly starting with generative AI, we need to set up access to models such as LLMs or text-to-image models so we can integrate them into our applications. As discussed in Chapter 1, What Is Generative AI?, there are various LLMs by tech giants, like GPT-4 by OpenAI, BERT and PaLM-2 by Google, LLaMA by Meta, and many more.

For LLMs, OpenAI, Hugging Face, Cohere, Anthropic, Azure, Google Cloud Platform’s Vertex AI (PaLM-2), and Jina AI are among the many providers supported in LangChain; however, this list is growing all the time. You can check out the full list of supported integrations for LLMs at https://integrations.langchain.com/llms.

Here’s a screenshot of this page as of the time of writing (October 2023), which includes both cloud providers and interfaces for local models:

Figure 3.1: LLM integrations in LangChain

LangChain implements three different interfaces – we can use chat models, LLMs...

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