Break the Limits: Send Large Text Blocks to ChatGPT with Ease

❓ Have you ever received a message from ChatGPT about sending too much data and needing to send a shorter text?

Jose Diaz
4 min readMar 18, 2023

Here’s a great alternative to bypass this limitation! 🚀

Overview

ChatGPT PROMPTs Splitter is an open-source tool designed to help you provide big amounts of context data to the prompts you are sending to ChatGPT into smaller chunks, and also according to a method on how to deal with the reception of all of the chunks to ChatGPT (or other language models with character limitations).

The tool ensures that the text is divided into safe chunks of up to 15,000 characters per request as default, although can be customized as needed.

The project includes an easy-to-use web interface for inputting the long prompt, selecting the maximum length of each chunk, and copying the chunks individually to paste them to ChatGPT.

Test it out by yourself!

The code is available in our GitHub repository for you to explore, and you can even contribute if you’re interested.

Github repository: https://github.com/jupediaz/chatgpt-prompt-splitter
Github repository: https://github.com/jupediaz/chatgpt-prompt-splitter

https://github.com/jupediaz/chatgpt-prompt-splitter

We’ve also deployed it serverless on Vercel for an easy, hassle-free test drive. Don’t hesitate to visit the GitHub repo and Vercel deployment to start making the most of the ChatGPT Prompt Splitter today!

https://chatgpt-prompt-splitter.jjdiaz.dev/

How it works

The tool uses a simple algorithm to split the text into smaller chunks. The algorithm is based on the following rules:

1. Divide the prompt into chunks based on the specified maximum length.

2. Add information to the first chunk to instruct the AI on the process of receiving and acknowledging the chunks and to wait for the completion of chunk transmission before processing subsequent requests.

Features

✅ Python 3.9
✅ Web interface for splitting text into smaller chunks
✅ Customizable maximum length for each chunk
✅ Copy chunks individually to send to ChatGPT
✅ Instructions for ChatGPT on how to process the chunks
✅ Tests included
✅ Easy deployment to Vercel included

Usage example

Follow these simple steps to use the ChatGPT Prompt Splitter web application, illustrated with screenshots.

Step 1: Access the application

Open your web browser and navigate to the application URL.

https://chatgpt-prompt-splitter.jjdiaz.dev/

You should see the main screen, displaying the input fields for your long text prompt and maximum chunk length.

Step 2: Input the long prompt

Enter the text you want to split into smaller chunks for use with ChatGPT.

You can also specify custom length for each chunk by entering the number of characters in the *”Max chars length…”* field.

In this example, we are gonna split into chunks of just 25 characters as a basic test.

Step 3: Click “Split”

Click the “Split” button to process the text and divide it into smaller chunks.

Step 4: Copy the chunks

The application will display the text divided into smaller chunks. You can copy each chunk individually by clicking the “Copy” button next to it.

Step 5: Paste the chunks into ChatGPT

Now that you have your chunks copied, you can paste them into ChatGPT or any other language model with character limitations.

That’s it! You’ve successfully split a long PROMPT into smaller, manageable chunks using the ChatGPT Prompt Splitter.

Check it out!

I would love to get your feedback and collaboration on this open-source project to help the community. 🤝

✅ Python 3.9
✅ Web interface for splitting text into smaller chunks
✅ Customizable maximum length for each chunk
✅ Copy chunks individually to send to ChatGPT
✅ Instructions for ChatGPT on how to process the chunks
✅ Tests included
✅ Easy deployment to Vercel included

Let’s make AI conversations more efficient together! 💬

#chatgpt #opensource #ai #python #communitysupport

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Jose Diaz

Head of IT @ IMCW. +15 years experience. Passionate about building scalable and clean code software. Experience leading software development teams.