Using Gemini's Code Execution Tool for Math and Data Analysis

Enhancing LLM Capabilities with Tools

• 💡 Large language models (LLMs) excel at predicting text but struggle with precise numerical computation.
• 🛠️ Connecting LLMs to tools extends their abilities, making them more effective for tasks requiring math, data analysis, and code-based reasoning.

Code Execution for Mathematical Accuracy

• 🚀 The Code Execution tool allows Gemini to generate and run Python code, significantly improving accuracy for mathematical problems.
• 🎯 When asked to calculate the sum of the first 60 prime numbers, Gemini without the tool provided an incorrect answer (8,368).
• ✅ With the Code Execution tool enabled, Gemini correctly calculated the sum as 7,699 by generating and executing Python code.
• 🧩 This generated code, which includes a prime number checking function, provides transparency into how the answer was derived.

Practical Data Analysis with CSV Genius

• 📊 A practical example demonstrates using the Code Execution tool with a CSV file for data analysis.
• 📈 The "CSV Genius" app, built with Google AI Studio, can answer questions about uploaded data, such as identifying the most sold fruit by quantity.
• 🥭 In a demonstration, Gemini correctly identified mangoes as the most sold fruit (63 units) from a tropical fruit stand dataset.
• 🔍 The tool also provides the generated Python code used for the analysis, showing how the data was loaded, filtered, and processed to arrive at the answer.

How Code Execution Works with Gemini API

• ⚙️ The Gemini API, specifically using models like Gemini 2.5 Flash, can be configured to use the Code Execution tool.
• ⚡ When the tool is passed, Gemini can call out to execute the Python code it generates on the API backend, returning the results to the user.