Experience this AI-Powered library that generates your complete Code Base!

Ranjith kumar

11 months ago

How to build an entire project using AI in minutes? Use this open-source library named gpt-engineer 🤖

How does GPT engineer work?

gpt-engineer is very easy to use. You give instructions on what you want to build. AI analyzes it, asks you for a few more questions for clarification, and then generates a codebase. You can also incrementally build it and improve it by giving more prompts.

Here’s a demo where we build a snake game using gpt-engineer:

https://github.com/AntonOsika/gpt-engineer/assets/4467025/6e362e45-4a94-4b0d-973d-393a31d92d9b

Core features

One prompt generates a codebase
Asks clarifying questions
Generates technical spec
Writes all necessary code
Easy to add your own reasoning steps, modify, and experiment
Open source
Lets you finish a coding project in minutes.

Project philosophy

Simple to get value
Flexible and easy to add new own “AI steps”.
Incrementally build towards a user experience of:
1. high-level prompting
2. giving feedback to the AI that it will remember over time
Fast handovers back and forth between AI and human
Simplicity, all computation is “resumable” and persisted to the filesystem

Usage

Choose either stable or development.

For stable release:

pip install gpt-engineer

For development:

git clone git@github.com:AntonOsika/gpt-engineer.git
cd gpt-engineer
make install
source venv/bin/activate

Setup

With an api key that has GPT4 access run:

export OPENAI_API_KEY=[your api key]

Run:

Create an empty folder. If inside the repo, you can run:
- cp -r projects/example/ projects/my-new-project
Fill in the main_prompt file in your new folder
Run: gpt-engineer projects/my-new-project

Results

Check the generated files in projects/my-new-project/workspace

Limitations

Implementing additional chain of thought prompting, e.g. Reflexion, should be able to make it more reliable and not miss requested functionality in the main prompt.

Sharing prompts across the projects

You can specify the “identity” of the AI agent by editing the files in the identity folder.

Editing the identity, and evolving the main_prompt, is currently how you make the agent remember things between projects.

Each step in steps.py will have its communication history with GPT4 stored in the logs folder, and can be rerun with scripts/rerun_edited_message_logs.py.