Integrating ChatGPT with Stata: A Modern Approach

Building bridges between statistical analysis tools and AI is crucial for modern data workflows. Today, we'll explore how to seamlessly integrate ChatGPT with Stata using Python, creating a powerful command-line interface that leverages OpenAI's API.

The Stack

• Stata

• Python for API integration

• OpenAI's GPT-3.5 Turbo model

• Stata/Python Integration (SFI) for cross-language communication

Quick Setup

First, ensure you have the OpenAI package installed:

pip install openai

Core Integration

The integration leverages Stata's Python capabilities to create a bridge between Stata's command interface and OpenAI's API. Here's the foundational setup:

import openai
from sfi import Macro

def chatgpt():
    openai.api_key = "YOUR_API_KEY"
    inputtext = Macro.getLocal('InputText')
    outputtext = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": inputtext}]
    )
    return outputtext.choices[0].message.content

Building the Command Interface

The magic happens in the Stata command definition. We're creating a seamless developer experience by wrapping the Python function in a native Stata command:

program chatgpt, rclass
    version 18
    args InputText
    python: chatgpt()
    return local OutputText = `"`OutputText'"'
end

Enhanced Output Handling

To maintain data integrity and formatting, we've implemented direct file output:

def write_output(content):
    with open("chatgpt_output.txt", "w") as f:
        f.write(content)

Usage

The interface is designed for simplicity:

chatgpt "Write a data analysis plan for time series data"

Performance Considerations

• Commands execute near-instantly

• Responses are cached in both memory and file system

• State is maintained between calls

• Native Stata performance isn't impacted

Advanced Features

Local Macro Areas

Access responses programmatically through Stata's return system:

return list
display "`r(OutputText)'"

File System Integration

Responses are automatically written to disk, maintaining formatting:

view "chatgpt_output.txt"

Looking Ahead

This integration opens up possibilities for:

• Automated code generation

• Natural language data analysis

• Interactive documentation

• AI-assisted statistical modeling

The intersection of statistical computing and AI is just beginning. This integration demonstrates how traditional statistical tools can be enhanced with modern AI capabilities, creating more powerful and intuitive workflows for data scientists and researchers.

Get Started

Install the OpenAI Python package

1. Set up your API key

2. Save the implementation in chatgpt.ado

3. Start using AI-powered commands in your Stata workflow

The full implementation is available as a Stata package, ready to enhance your statistical computing environment with the power of GPT-3.5.