gpt-engineer
Platform to experiment with the AI Software Engineer. Terminal based. NOTE: Very different from
Science Score: 44.0%
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✓codemeta.json file
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○Scientific vocabulary similarity
Low similarity (16.0%) to scientific vocabulary
Keywords
Repository
Platform to experiment with the AI Software Engineer. Terminal based. NOTE: Very different from
Basic Info
- Host: GitHub
- Owner: lucatosc
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://gptengineer.app
- Size: 16.9 MB
Statistics
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
gpt-engineer
gpt-engineer lets you: - Specify software in natural language - Sit back and watch as an AI writes and executes the code - Ask the AI to implement improvements
Getting Started
Install gpt-engineer
For stable release:
python -m pip install gpt-engineer
For development:
- git clone https://github.com/gpt-engineer-org/gpt-engineer.git
- cd gpt-engineer
- poetry install
- poetry shell to activate the virtual environment
We actively support Python 3.10 - 3.12. The last version to support Python 3.8 - 3.9 was 0.2.6.
Setup API key
Choose one of:
- Export env variable (you can add this to .bashrc so that you don't have to do it each time you start the terminal)
- export OPENAI_API_KEY=[your api key]
- .env file:
- Create a copy of .env.template named .env
- Add your OPENAIAPIKEY in .env
- Custom model:
- See docs, supports local model, azure, etc.
Check the Windows README for Windows usage.
Other ways to run:
- Use Docker (instructions)
- Do everything in your browser:
Create new code (default usage)
- Create an empty folder for your project anywhere on your computer
- Create a file called
prompt(no extension) inside your new folder and fill it with instructions - Run
gpte <project_dir>with a relative path to your folder- For example:
gpte projects/my-new-projectfrom the gpt-engineer directory root with your new folder inprojects/
- For example:
Improve existing code
- Locate a folder with code which you want to improve anywhere on your computer
- Create a file called
prompt(no extension) inside your new folder and fill it with instructions for how you want to improve the code - Run
gpte <project_dir> -iwith a relative path to your folder- For example:
gpte projects/my-old-project -ifrom the gpt-engineer directory root with your folder inprojects/
- For example:
Benchmark custom agents
- gpt-engineer installs the binary 'bench', which gives you a simple interface for benchmarking your own agent implementations against popular public datasets.
- The easiest way to get started with benchmarking is by checking out the template repo, which contains detailed instructions and an agent template.
- Currently supported benchmark:
- [APPS]
- MBPP
By running gpt-engineer, you agree to our terms.
Relation to gptengineer.app (GPT Engineer)
gptengineer.app is a commercial project for the automatic generation of web apps. It features a UI for non-technical users connected to a git-controlled codebase. The gptengineer.app team is actively supporting the open source community.
Features
Pre Prompts
You can specify the "identity" of the AI agent by overriding the preprompts folder with your own version of the preprompts. You can do so via the --use-custom-preprompts argument.
Editing the preprompts is how you make the agent remember things between projects.
Vision
By default, gpt-engineer expects text input via a prompt file. It can also accept image inputs for vision-capable models. This can be useful for adding UX or architecture diagrams as additional context for GPT Engineer. You can do this by specifying an image directory with the —-image_directory flag and setting a vision-capable model in the second CLI argument.
E.g. gpte projects/example-vision gpt-4-vision-preview --prompt_file prompt/text --image_directory prompt/images -i
Open source, local and alternative models
By default, gpt-engineer supports OpenAI Models via the OpenAI API or Azure OpenAI API, as well as Anthropic models.
With a little extra setup, you can also run with open source models like WizardCoder. See the documentation for example instructions.
Mission
The gpt-engineer community mission is to maintain tools that coding agent builders can use and facilitate collaboration in the open source community.
If you are interested in contributing to this, we are interested in having you.
If you want to see our broader ambitions, check out the roadmap, and join [discord] to learn how you can contribute to it.
gpt-engineer is governed by a board of long-term contributors. If you contribute routinely and have an interest in shaping the future of gpt-engineer, you will be considered for the board.
Owner
- Login: lucatosc
- Kind: user
- Repositories: 1
- Profile: https://github.com/lucatosc
Citation (citation.cff)
cff-version: 1.0.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Osika
given-names: Anton
title: gpt-engineer
version: 0.1.0
date-released: 2023-04-23
repository-code: https://github.com/gpt-engineer-org/gpt-engineer
url: https://gpt-engineer.readthedocs.io
GitHub Events
Total
- Watch event: 4
- Issue comment event: 2
- Push event: 3
- Pull request event: 6
- Create event: 2
Last Year
- Watch event: 4
- Issue comment event: 2
- Push event: 3
- Pull request event: 6
- Create event: 2
Issues and Pull Requests
Last synced: 12 months ago
All Time
- Total issues: 0
- Total pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: 3 minutes
- Total issue authors: 0
- Total pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 1.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: 3 minutes
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 1.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
- lucatosc (4)