AutoCode: Automated Code Improvement by Metrics Optimization
Project description
autocode
Auto Code Improvement by Technical Metrics Optimization.
Description
Autocode selects the best values for optimized metrics. The value types could be bool, int, float, and choice (including but not limited to code). This project utilizes a Large Language Model and Mixed-Variable Many-Objective Optimization. Based on our research/literature review, this project hypothetically can contribute to the economic performance of companies.
Features
- Many-software Value-level Mixed-variable Many-objective Optimization.
- Value types include bool, int, float, and choice (code).
- Code scoring and variation generators using LLM.
- Software cross-language support.
- Easy software deployment using docker-compose.
- Scalable to infinite cores to speed up processing in parallel.
How to Use
- Install the requirements
pip install autocode-py
- Prepare software to be processed as in the
./example/client
folder. - Prepare deployment as in the
./example/client-compose.yml
file. - Prepare controller as in the
./example/controller.ipynb
file. - Run the process in controller.
- Open dashboard in
http://localhost:{dashboard_port}/
to see the process in real-time. - Wait until the process is finished.
- Analyze and decide the best values.
Demo
- Controller
- Client
- Dashboard
Compatibility
- Python 3.10
- Linux
- Docker
- autocode-go
Project details
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