To get the most out of this book
To benefit from the value this book offers, it is essential to have a foundational understanding of Python. Additionally, possessing some basic knowledge of machine learning is recommended.
Download the example code files
The code bundle for the book is hosted on GitHub at https://github.com/benman1/generative_ai_with_langchain. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!
Download the color images
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://packt.link/gbp/9781835083468.
Conventions used
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. For example: “Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system.”
A block of code is set as follows:
from langchain.chains import LLMCheckerChain
from langchain.llms import OpenAI
llm = OpenAI(temperature=0.7)
text = "What type of mammal lays the biggest eggs?"
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
from pandasai.llm.openai import OpenAI
llm = OpenAI(api_token="YOUR_API_TOKEN")
pandas_ai = PandasAI(llm)
Any command-line input or output is written as follows:
pip install -r requirements.txt
Bold: Indicates a new term, an important word, or words that you see on the screen. For instance, words in menus or dialog boxes appear in the text like this. For example: “Select System info from the Administration panel.”
Warnings or important notes appear like this.
Tips and tricks appear like this.
