Is the ChatGPT Code Interpreter Available for Free?

Is the ChatGPT Code Interpreter Free?

When it comes to high-functionality tools like the ChatGPT Code Interpreter, users frequently ponder over costs associated with them. After a significant buzz, OpenAI has incorporated a feature called Code Interpreter into ChatGPT, exclusively for its paying users. Unfortunately, it doesn’t come cheap—it costs $20 monthly. However, not everyone finds this pricing affordable, leading to the question: Is there a way to use the ChatGPT Code Interpreter for free? The answer is yes! Let’s delve deeper into how you can tap into the power of the Code Interpreter without spending a dime.

Understanding the Code Interpreter’s Release and Cost

Recently, OpenAI rolled out the Code Interpreter feature within ChatGPT, making it available to all paying users. Now, with every update, the tools we use become more powerful. The Code Interpreter lets users engage in data analysis, visualize datasets, and perform complex calculations, which can be invaluable for developers and data scientists. However, the $20 per month subscription isn’t affordable for everyone, especially students or those just starting in tech. But fret not! If you’re looking to leverage the Code Interpreter without breaking the bank, you’re in luck.

Enter Shroominic, a developer who has created an open-source implementation of the ChatGPT Code Interpreter. This means you can analyze datasets and visualize data in a manner quite similar to OpenAI’s own version, but for free! It’s an exciting opportunity, especially for those on a budget. So let’s get started on how you can use this ingenious solution!

Things to Keep in Mind Before You Dive In

Before we dive into this tutorial, there are a few important aspects to consider:

Open Source Project: We will be using a free and open-source Code Interpreter API project available on GitHub. This project employs CodeBoxes, OpenAI’s API, LangChain Agents, and multiple Python packages. It mimics the functionality you would expect from ChatGPT’s Code Interpreter.
Size Limitations: It works well for smaller datasets, and the best part—it’s free to use! But beware; when it comes to larger datasets, you might encounter OpenAI’s rate limit for free users, which may prevent successful operation. If you plan to analyze large amounts of data, it’s advisable to add a payment method to your OpenAI account.
API Compatibility: If you’re lucky enough to have access to the GPT-4 API, the project will perform smoothly. However, fear not if you’re on the GPT-3.5-turbo model; I have customized the code for compatibility.

Step 1: Set Up the Code Interpreter API

The very first step in this adventure is to set up your Code Interpreter API. Here’s how you do it:

Ensure you have Python and Pip installed on your computer. If you need assistance, check out our linked tutorial. Don’t forget to check the box to add python.exe to your PATH while installing—it’ll save you headache later!
Once you’ve got Python and Pip installed, fire up your Terminal and run these commands to test if everything is in order:

python –version
pip –version

Now it’s time to install the Code Interpreter API. Type the below command in the Terminal:

pip install « codeinterpreterapi[all] »

Congrats! You’ve reached the stage where you need to acquire your API key from OpenAI’s website. Just click on “Create new secret key” and copy that golden string of characters.

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Step 2: Run the ChatGPT Code Interpreter for Free

With the API installed and your key ready, it’s finally time to run the Code Interpreter API without spending a single cent! Let’s get cracking:

Open your favorite code editor—whether it’s Sublime Text or Notepad++—and let’s put in some code.
Copy and paste the code below into the code editor. This code is derived from the GitHub page of the Code Interpreter API, but I’ve tweaked it slightly to avoid potential snafus:

import os os.environ[« OPENAI_API_KEY »] = « PASTE THE OPENAI API KEY HERE » from codeinterpreterapi import CodeInterpreterSession async def main(): # create a session session = CodeInterpreterSession(model= »gpt-3.5-turbo ») await session.astart() # generate a response based on user input response = await session.generate_response( « Plot the Apple stock price chart from 2007 to 2023 June » ) # output the response (text + image) print(« AI: « , response.content) for file in response.files: file.show_image() # terminate the session await session.astop() if __name__ == « __main__ »: import asyncio # run the async function asyncio.run(main())

The highlighted area is where the magic happens—make sure to paste your OpenAI API key (the one we got earlier) in the second line.
If you have access to the GPT-4 API, feel free to change the model to « gpt-4 » in line nine. The query you want to create can be entered in line fourteen.
Now save the file as “chart.py” on your Desktop. Ensure you’ve got .py at the end of the filename, or else it’ll be as useful as a chocolate teapot!
Open up the Terminal again and enter the below commands sequentially. The first will direct you to the Desktop location and the second will run your “chart.py” file using Python:

cd Desktop python chart.py

Give it a few moments, and voilà! The Code Interpreter API will generate the required chart for you. It operates in the background using various services, including LangChain Agents and Matplotlib for graph plotting.
If you want to witness everything happening behind the scenes, add os.environ[« VERBOSE »] = « True » to the code.
After this initial setup, changing the query in the code is as easy as pie. You can run the “chart.py” file multiple times with different queries.

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Step 3: Perform Data Analysis Using the Code Interpreter API

Now, let’s take a look at how to perform actual data analysis using the Code Interpreter API:

The first step is to create a folder named “analysis” on your Desktop where you can collect and organize your datasets.
Now, move your chosen dataset to the “analysis” folder. For example, let’s consider a file titled “globaltemperature.csv.” It can be in CSV, XLS, or XLSX format—just ensure that it’s relevant to your analysis tasks.
Next, open your code editor again and copy-paste the following code:

import os os.environ[« OPENAI_API_KEY »] = « PASTE THE OPENAI API KEY HERE » from codeinterpreterapi import CodeInterpreterSession, File async def main(): # context manager for auto start/stop of the session async with CodeInterpreterSession(model= »gpt-3.5-turbo ») as session: # define the user request user_request = « Analyze this dataset and plot global temperature from the year 1950 to 2016. Consider the GCAG system. » files = [ File.from_path(« globaltemperature.csv »), ] # generate the response response = await session.generate_response(user_request, files=files) # output to the user print(« AI: « , response.content) for file in response.files: file.show_image() if __name__ == « __main__ »: import asyncio asyncio.run(main())

Once again, paste your OpenAI API key in the designated line.
Make sure to replace “globaltemperature.csv” with the name of your dataset. You can also tweak the model and user query, depending on your analysis needs.
Now save this file as “data.py” inside the “analysis” folder on your Desktop.
Return to the Terminal, and let’s execute the file like this:

cd Desktop/analysis python data.py

Within moments (usually), you’ll receive a chart based on your local dataset—an incredible achievement!

Conclusion: The Freedom of Open Source

And there you have it! With the steps above, you can effectively utilize the ChatGPT Code Interpreter API for free. More than just a way to save money, this open-source project symbolizes a larger movement toward democratizing technology. By utilizing these resources, we not only free ourselves from financial constraints but also empower fellow tech enthusiasts to explore data analysis and visualization without any barriers.

Who knows? You may end up crafting data visualizations that could change how we perceive global warming or revolutionize the way industries analyze their data. So gear up, learn, experiment, and have fun with your newfound skills!

Should you encounter troubles or errors during setup, don’t hesitate to reach out on forums or communities—they can be treasure troves of guidance. Welcome to the world of code interpretation without the code-pocalypse of fees!