Summary

In this chapter, we covered the integration of code assistants with LLMs to assist users with auto-code generation. Then, we explored three commonly used auto-code generation prompting techniques: single-line prompts, multi-line prompts, and chain-of-thought prompts. We introduced each of these prompting techniques for auto-code generation, along with potential use cases, limitations, and required coding experience. Sample code examples were used in JetBrains’ PyCharm IDE with Amazon Q Developer enabled. Additionally, we introduced the chat with code assistant technique in the auto-code generation process, where users interact with the code assistant in a simple question-and-answer style session. Amazon Q Developer was utilized to obtain general recommendations for coding/debugging.

We then discussed some of the common building methods of code generation, such as single-line code completion, full function generation, block completion, line-by-line recommendations...