You’ve seen how to build an AI chatbot with ChatGPT API and give it a personality. But what if you want to make it smarter with your own data? Maybe you have a book, financial data, or a huge database that you want to search easily. Don’t worry, we’ve got you covered. In this article, we’ll show you how to train an AI chatbot with your custom knowledge base using LangChain and ChatGPT API. You’ll use OpenAI’s Large Language Model (LLM) and some awesome libraries like LangChain and GPT Index to create your own AI chatbot. Sounds cool, right? Let’s get started!

How to integrate ChatGPT API, LangChain, and GPT Index to design a creative assistant that can generate poems, stories, code, or lyrics based on your input and preferences.

You want to teach your AI chatbot with your own data? No problem! We have got you covered with this awesome article. It has all the steps you need to set up tools and software, train the AI model, and test it out. Trust us, it’s super easy and fun. Just follow the instructions from top to down and don’t skip anything. You’ll be amazed by what you can do with your own data!

How to ensure responsible AI practices and avoid bias in your ChatGPT model

Hey there, you awesome human! Do you want to train an AI chatbot with your own data? Well, you’ve come to the right place! I’m going to show you how to do it in a snap. But before we start, let me tell you some important points that will make your life easier.

• You can use any platform you want: Windows, macOS, Linux, or ChromeOS. I’m using Windows 11 because I’m cool like that, but you can follow along with any other platform. They’re all pretty much the same.
• You don’t need to be a nerd or a coder to train an AI chatbot. I’ll explain everything in simple words that even a monkey can understand. If you read my previous article on ChatGPT bot, you’re already ahead of the game.
• You need a decent computer with a good CPU and GPU if you want to train an AI chatbot with a lot of data. If you have a crappy computer like a Chromebook, you can still try it out with a small amount of data (like 100 pages of a book). But don’t expect miracles. You get what you pay for.
• If you want to get the most out of this tool, you should use English as your data set language. However, this tool also supports other popular languages such as French, Spanish, German, and more. So feel free to try it with your native language and see how it works for you.

Create the Software Environment for an AI Chatbot Training

Hey there, fellow Python lover! Are you ready to unleash the power of OpenAI and GPT Index on your PDF files? Well, buckle up, because we’re going to show you how to set up everything from scratch in this article. No prior knowledge required! All you need is Python and Pip installed on your computer, along with a few awesome libraries that will make your life easier. What are these libraries, you ask? Well, let me introduce you to:

• OpenAI: The ultimate AI platform that lets you access GPT-3 and other cool stuff.
• GPT Index: The handy tool that lets you index and query your PDF files using natural language.
• Gradio: The simple way to create beautiful web interfaces for your Python scripts.
• PyPDF2: The library that lets you manipulate PDF files like a boss.

Sounds amazing, right? Trust me, it is. And don’t worry about the installation process. It’s as easy as pie. (Mmm… pie.) Just follow our step-by-step guide and you’ll be ready to rock in no time. So what are you waiting for? Let’s get started!

1.Python

If you want to start coding in Python, the first step is to install Pip on your computer. Pip is a package manager that lets you download and use Python libraries with ease. To install Pip, you need to go to this link and choose the setup file that matches your operating system. Whether you use Windows, Mac or Linux, there is a file for you. Follow the instructions on the screen and you will have Pip ready in no time.

You’re almost there! Now you need to run the setup file and make sure you enable the checkbox for “Add Python.exe to PATH.” This is a crucial step that will save you a lot of hassle later on. Then, just click on “Install Now” and follow the simple steps to install Python on your computer.

You can verify the Python installation on your computer by using the Terminal. If you have Windows, you can open Windows Terminal or Command Prompt. Then, type python –version and press Enter. The Terminal will show you the Python version you have. For Linux and macOS users, you may need to type python3 –version instead.

2.Pip

Here is a possible paragraph that meets your criteria:

You can install thousands of Python libraries with Pip, the package manager for Python. Pip comes with Python when you install it on your system. To use the latest version of Pip, you need to upgrade it first. Follow these steps to upgrade Pip and install OpenAI, gpt_index, gradio, and PyPDF2 libraries:

1. Open your preferred Terminal on your computer. You can use Windows Terminal or Command Prompt on Windows. On Linux and macOS, you may have to use python3 and pip3 instead of python and pip.

python -m pip install -U pip

2.

You can verify the installation of Pip by running this command:

pip –version

This command shows you the version number of Pip. If you see any errors, you may have problems with your PATH settings. To fix them, follow our guide on how to install Pip on Windows.

OpenAI, GPT Index, PyPDF2, and Gradio Libraries

To train an AI chatbot with a custom knowledge base, you need to install some essential libraries first. You will use Python and Pip as your programming tools. Follow these steps to install the libraries:

• Run this command in the Terminal to install OpenAI. This library will help you create and train an AI chatbot using a large language model (LLM). You will also import the LangChain framework from OpenAI. If you use Linux or macOS, you may need to use pip3 instead of pip.

pip install openai

• Install GPT Index or LlamaIndex next. This library will connect your LLM to your external data source, which is your knowledge base.

pip install gpt_index

• If you want to use PDF files as your data source, install PyPDF2. This library will parse PDF files for you.

pip install PyPDF2

• Lastly, install Gradio. This library will create a simple user interface (UI) for you to interact with your trained AI chatbot.

pip install gradio

Code Editor (Notepad++)

A code editor is essential for editing some of the code. If you use Windows, download and install Notepad++ (Download) from the link below. It is a simple and user-friendly program. You can also choose VS Code for any platform. It is a powerful IDE that offers many features. For macOS and Linux users, Sublime Text (Download) is another option. It is a fast and elegant code editor.

ChromeOS users can download Caret app (Download) to edit the code. It is an excellent app that works well with Chromebooks. You are almost done with setting up the software environment. The next step is to get the OpenAI API key.

Receive a Free OpenAI API Key

To create a free account on OpenAI platform, go to platform.openai.com/signup. If you already have an OpenAI account, just log in.

To get your OpenAI API key for free, follow these steps:

• Click on your profile in the top-right corner.
• Select “View API keys” from the drop-down menu.
• Click on “Create new secret key” and copy the API key. You can’t copy or view the entire API key later on. So save it to a Notepad file right away.
• Don’t share or display the API key in public. It’s a private key for your account only. You can delete API keys and create up to five private keys.

Develop an AI Chatbot using a customised knowledge base.

To train the AI chatbot, we need to set up the software environment and get the API key from OpenAI. We will use the “text-davinci-003” model for text completion because it works much better than the latest “gpt-3.5-turbo” model. However, you can change the model to Turbo if you want to reduce the cost. Now, let’s follow these instructions to start training our chatbot.

1. To create a new folder called docs, follow these steps: 1. Go to an accessible location like the Desktop. You can also choose another location that suits you better. 2. Right-click on an empty space and select New > Folder. 3. Type docs as the folder name and press Enter.
2. To train the AI, put the documents you want to use inside the “docs” folder. You can use text or PDF files, even scanned ones. You can also import large Excel tables as CSV or PDF files and add them to the “docs” folder. SQL database files work too, as this Langchain AI tweet shows. I haven’t tested other file formats, but you can try them yourself. For this article, I used one of my e-book articles in PDF format.

Start preparing the Code

1.To create a Gradio interface for PDF files, you need to paste some code into a code editor. You can use Notepad++ or any other editor of your choice. The code below is based on armrrs’s work on Google Colab, but I have modified it to make it compatible with PDF files.

from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
import gradio as gr
import sys
import os

os.environ["OPENAI_API_KEY"] = 'Your API Key'

def construct_index(directory_path):
    max_input_size = 4096
    num_outputs = 512
    max_chunk_overlap = 20
    chunk_size_limit = 600

    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)

    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.7, model_name="text-davinci-003", max_tokens=num_outputs))

    documents = SimpleDirectoryReader(directory_path).load_data()

    index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)

    index.save_to_disk('index.json')

    return index

def chatbot(input_text):
    index = GPTSimpleVectorIndex.load_from_disk('index.json')
    response = index.query(input_text, response_mode="compact")
    return response.response

iface = gr.Interface(fn=chatbot,
                     inputs=gr.inputs.Textbox(lines=7, label="Enter your text"),
                     outputs="text",
                     title="Custom-trained AI Chatbot")

index = construct_index("docs")
iface.launch(share=True)

2.Next, select “Save As…” from the drop-down menu by clicking on “File” in the top menu.

3.To save your file as AIChatbot.py, follow these steps. First, type AIChatbot.py in the file name box. Next, select “All types” from the “Save as type” drop-down menu. Finally, choose the location where you created the “docs” folder (for example, Onedrive\ Desktop) and click Save. You can use a different name for your file if you want, but make sure it ends with .py.

4.As seen in the screenshot below, confirm that the “docs” folder and “AIChatbot.py” are in the same location. There won’t be a “AIChatbot.py” file inside the “docs” folder.

5.Return to the code in Notepad++ once more. The generated API key from OpenAI’s website should be substituted here for Your API Key and Save (ctrl+s) it.

Build an AI ChatGPT Bot Using a Custom Knowledge Base

1. To move to the Desktop in the Terminal, run this command: cd Onedrive\Desktop. This is where you should have the “docs” folder and the “AIChatbot.py” file. If you saved them somewhere else, use the Terminal to go there instead.

Run the command listed below now. Users of Linux and macOS might need to use Python 3.

python AIChatbot.py

2. The OpenAI LLM model will analyze and index the document. The file size and your computer’s capability affect the processing time. A 40MB document takes around 10 seconds to process. The Terminal may not show any output while processing the data. An “index.json” file will appear on the Desktop when it’s done.

3. You will receive a few warnings after the LLM has finished processing the data, but you can safely disregard them. Finally, a local URL can be found at the bottom. Copy it.

4.You can create your own ChatGPT-powered AI chatbot with a custom-trained document. Just copy of the document and paste it into the web browser. Your AI chatbot is ready to go. Ask it what the document is about to start chatting.

5.You can create a custom-trained AI chatbot with your own dataset using ChatGPT. You just need to provide the data you want the AI to learn from, and then you can ask further questions. The ChatGPT bot will answer based on the data you provided. This way, you can train and create an AI chatbot for any kind of information you want. The possibilities are endless.

6.Share your public URL with friends and family. They can access it for 72 hours. Keep your computer on during this time. Your server instance runs on your computer.

7.To stop the chatbot, you need to press “Ctrl + C” in the Terminal window. This command will interrupt its training process. If it does not work the first time, try pressing “Ctrl + C” again.

8.You can restart the AI chatbot server easily. Just go back to the Desktop location and run this command:

python AIChatbot.py

9.The server will use the same local URL as before. But remember, the public URL will change every time you restart the server.

10.To train the AI chatbot with new data, you need to replace the files in the “docs” folder. Delete the old files and add new ones. Make sure the files have information on the same subject for a coherent response. The AI chatbot will learn from the new data and improve its skills.

11.You can create a new “index.json” file by running the code again in the Terminal. This will automatically replace the old “index.json” file.

python AIChatbot.py

Related post 10 Ways Of Using ChatGPT For SEO, Example,Tips And Prompts

Conclusion:

You can train an AI chatbot with a custom knowledge base using this code. It works flawlessly on medical books, articles, data tables, and reports from old archives. Create your own AI chatbot with OpenAI’s Large Language Model and ChatGPY today. You can also check out our linked article for the best ChatGPT alternatives. And if you want to use ChatGPT on your Apple Watch, follow our in-depth tutorial. Let us know in the comment section below if you have any issues. We are happy to help you out.