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A newer version of the Gradio SDK is available:
4.44.0
title: Code Interpreter
emoji: 🔥
colorFrom: blue
colorTo: pink
sdk: gradio
sdk_version: 3.41.2
app_file: app.py
pinned: false
license: mit
duplicated_from: dongsiqie/Code-Interpreter
Local-Code-Interpreter
A local implementation of OpenAI's ChatGPT Code Interpreter.
Introduction
OpenAI's Code Interpreter plugin for ChatGPT is a revolutionary feature that allows the execution of Python code within the AI model. However, it execute code within an online sandbox and has certain limitations. In this project, we present Local Code Interpreter – which enables code execution on your local device, offering enhanced flexibility, security, and convenience.
Key Advantages
Custom Environment: Execute code in a customized environment of your choice, ensuring you have the right packages and settings.
Seamless Experience: Say goodbye to file size restrictions and internet issues while uploading. With Local Code Interpreter, you're in full control.
GPT-3.5 Availability: While official Code Interpreter is only available for GPT-4 model, the Local Code Interpreter offers the flexibility to switch between both GPT-3.5 and GPT-4 models.
Enhanced Data Security: Keep your data more secure by running code locally, minimizing data transfer over the internet.
Note
Executing AI-generated code without human review on your own device is not safe. You are responsible for taking measures to protect the security of your device and data (such as using a virtural machine) before launching this program. All consequences caused by using this program shall be borne by youself.
Usage
Getting Started
Clone this repository to your local device
git clone https://github.com/MrGreyfun/Local-Code-Interpreter.git
Install the necessary dependencies. The program has been tested on Windows 10 and CentOS Linux 7.8, with Python 3.9.16. Required packages include:
Jupyter Notebook 6.5.4 gradio 3.39.0 openai 0.27.8
Other system or package version may also work.
Configuration
Create a
config.json
file in thesrc
directory, following the examples provided in theconfig_example
directory.Configure your API key in the
config.json
file.
Please Note:
Set the
model_name
Correctly This program relies on the function calling capability of two specific models:gpt-3.5-turbo-0613
gpt-4-0613
Older versions of the models will not work.
For Azure OpenAI service users:
- Set the
model_name
as your deployment name. - Confirm that the deployed model corresponds to the
0613
version.
API Version Settings If you're using Azure OpenAI service, set the
API_VERSION
to2023-07-01-preview
in theconfig.json
file. Note that other API versions do not support the necessary function calls for this program.Alternate API Key Handling If you prefer not to store your API key in the
config.json
file, you can opt for an alternate approach:- Leave the
API_KEY
field inconfig.json
as an empty string:"API_KEY": ""
- Set the environment variable
OPENAI_API_KEY
with your API key before running the program:- On Windows:
set OPENAI_API_KEY=<YOUR-API-KEY>
- On Linux:
export OPENAI_API_KEY=<YOUR-API-KEY>
- Leave the
Getting Started
Navigate to the
src
directory.Run the command:
python web_ui.py
Access the generated link in your browser to start using the Local Code Interpreter.
Example
Imagine uploading a data file and requesting the model to perform linear regression and visualize the data. See how Local Code Interpreter provides a seamless experience: