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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 376 pages
Edition 1st Edition
Languages
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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 (14) 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. Unlock Your Book’s Exclusive Benefits 12. Other Books You May Enjoy
13. Index

Automating software development

In LangChain, we have several integrations for code execution, like LLMMathChain, which executes Python code to solve math questions, and BashChain, which executes Bash terminal commands, which can help with system administration tasks. However, while useful for problem-solving, these don’t address the larger software development process.

This approach of solving problems with code can, however, work quite well, as we’ll see here:

from langchain.llms.openai import OpenAI
from langchain.agents import load_tools, initialize_agent, AgentType
llm = OpenAI()
tools = load_tools(["python_repl"])
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
result = agent("What are the prime numbers until 20?")
print(result)

We can see how the prime number calculations get processed quite well under the hood between OpenAI’s LLM and the Python interpreter:

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