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Understanding OpenAI's Code Interpreter

Updated: Feb 5

Code interpreter logo


In the world of artificial intelligence, ChatGPT has emerged as a groundbreaking Generative model. However, as with any innovative technology, there are certain challenges to address. One of the most notable issues with ChatGPT is its tendency to "hallucinate" when dealing with numerical calculations.


Hallucination example

ChatGPT might yield an answer of 68.9, while the correct result should have been 139.94. This discrepancy could be efficiently addressed if the AI had the capability to generate and execute Python code seamlessly. Fortunately, the Code Interpreter comes to the rescue by harnessing the power of Python's execution environment. Rather than relying solely on AI-generated responses, the Code Interpreter employs the provided code and executes it in Python, thus ensuring more precise and reliable outcomes. Additionally, this tool proves invaluable when it comes to reading from files, as it leverages Python libraries for seamless file handling. It not only handles uploads and downloads but also boasts a working Python interpreter within a sandboxed, firewalled execution environment, equipped with ample disk space.

The advantages of the Code Interpreter are not limited to numerical calculations alone. Its utility extends to various general tasks, including summarizing extensive PDF files, tackling mathematical problems, conducting data analysis, and visualizing data. Moreover, it also extends to computer vision, demonstrating exceptional abilities in image editing.

Data analysis

The ChatGPT Code Interpreter stands out as an exceptional tool, capable of executing code to facilitate a wide range of data analysis tasks, including preprocessing, data cleaning, and deriving valuable insights. This unique capability grants non-technical users unprecedented accessibility to data analysis, as they can effortlessly interact using natural language. To demonstrate this, let's delve into an example utilizing the Bigmart sales data.

Prompt: Please perform a detailed exploratory data analysis and provide different visualization charts

Data Preprocessing: The Code Interpreter initiates the process by loading the data and conducting essential preprocessing steps. It adeptly identifies missing data, and remarkably, it endeavors to generate descriptions for the headers independently, streamlining the data analysis process.

Data preprocessing example

Descriptive Statistics: Moving forward, the Code Interpreter presents a comprehensive summary of the data through descriptive statistics. It provides essential metrics, such as the average and the range of establishment years for numerical columns, as well as the unique categories for categorical values, enabling users to gain valuable insights at a glance.

Descriptive statistics example

Insightful Data Visualization: It further enriches the data analysis experience by creating visually appealing graphs. It expertly plots distributions for both numerical and categorical variables, offering valuable insights into the underlying patterns. While we display only the numerical plot here, the Interpreter's capabilities extend to both types of variables.

Data visualization example

Correlation Analysis: Understanding the relationships between different variables is crucial for gaining deeper insights into the data. Here, the Code Interpreter excels by unearthing correlations between variables, highlighting positive and negative associations. This critical information aids users in understanding the intricate connections within the dataset.

Correlation example

In summary, the ChatGPT Code Interpreter exhibits an extraordinary capacity for Exploratory Data Analysis (EDA), extracting valuable insights from complex datasets effortlessly. Its ability to generate meaningful visualizations, analyze correlations, and present detailed statistics in a user-friendly manner proves invaluable to users seeking to make data-driven decisions.

Computer vision

With access to a Python environment, the Code Interpreter's capabilities extend seamlessly into the realm of computer vision tasks, encompassing a wide range of applications such as face detection, object detection, object tracking, and Optical Character Recognition (OCR). In this section, we shall explore a fundamental computer vision task - converting a colored image to black and white.

Prompt: Convert the Image to black and whiter

Computer vision example b2w

CV example output

As you can see it utilized relevant library to convert the image to black and white.

Through its proficiency in leveraging relevant libraries, the Code Interpreter deftly accomplishes the image conversion process, successfully transforming the colored image into a black and white representation.

In conclusion, the ChatGPT Code Interpreter efficiently addresses numerical discrepancies through Python integration, ensuring precise outcomes. Its versatile capabilities extend to data analysis and computer vision tasks, empowering users with seamless AI-driven solutions. As this innovative synergy evolves, the Interpreter continues to redefine the AI landscape, making intelligent assistance more accessible and efficient.

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