Frequently Asked Questions
The Codegen AI agent leverages modern large language models (LLMs) for code understanding and generation. This means it can generally handle tasks involving any programming language, configuration format (like JSON, YAML), documentation (like Markdown), or other text-based files that current LLMs are proficient with. If you have specific needs or find limitations with a particular language or format, please let us know!
The Codegen agent uses large language models to understand and modify code. While powerful, its understanding isn’t based on formal static analysis and may not always be perfectly exact or catch all edge cases like a traditional compiler or linter might. It aims for practical correctness based on the provided context and instructions.
Yes! Codegen’s agent is designed to work effectively on large, real-world codebases. You can provide context and specific instructions to help it navigate complex projects.
For enterprise use cases and support, please reach out to team@codegen.com
Yes. The Codegen SDK is a standard Python package (pip install codegen).
You can import and use it in your Python scripts, CI/CD pipelines, or any
other development tool that can execute Python code.
Start by trying out the Codegen agent and SDK, joining our Slack community, and reporting any issues or feedback on GitHub. We welcome contributions to documentation, examples, and SDK improvements.
The best places to get help are: 1. Our community Slack channel 2. GitHub issues for bug reports or SDK feature requests 3. Reach out to us on Twitter