A simple utility to explain given source code file using LLM
(eat your own dog food)
$ explain-code.sh explain-code.shGenerated output
# Explanation of the Provided UNIX-Shell File
The provided UNIX-shell script is a utility designed for the purpose of exploring and
understanding unknown code files based on their file types. Below is a detailed breakdown
of its functionality, key algorithms, and design patterns.
## Key Features of the Script
### 1. Shebang and Comments
• The script begins with a shebang ( #!/bin/sh ), indicating that it should be executed
in the Bourne shell.
• Comments are included at the top to describe the utility's purpose and dependencies.
### 2. Dependencies
• LLM API Access: The script requires access to a Language Model (LLM) API.
• ChatGPT Client: It uses a specific chat client to communicate with the API.
• Glow: This is a Markdown beautifier utilized for generating readable output.
### 3. Environment Variable for Markdown Highlighter
• The script sets a variable MARKDOWN_HIGHLIGHER to the path of the glow utility for
beautifying Markdown output.
• If glow is not found, it falls back to using the tr command, which simply transforms
text to lowercase, making it less visually appealing.
### 4. File Existence Check
• The script checks if a filename is provided and if the file exists.
• If not present, it displays a usage message and exits.
### 5. Language Detection
• The script extracts the base name of the provided file and checks its extension to determine
the programming language. Supported languages include Python, Java, JavaScript, C, C++, C#,
UNIX-shell, and SQL.
### 6. Generating Code Explanation
• The core functionality involves passing the content of the specified file to a ChatGPT model via
an API call.
• It constructs a request prompt asking for an explanation, identification of key algorithms, and
design patterns in the file, formatted in Markdown.
### 7. Output
• Finally, the output from the API call is piped into the Markdown highlighter for improved
readability before being displayed to the user.
## Key Algorithms
1. File Manipulation Algorithm:
• Uses basename to extract the filename for determining the language and obtaining the
filename only without the path.
2. Language Identification Algorithm:
• Utilizes a case statement to map file extensions to their corresponding programming languages.
3. Error Handling Algorithm:
• Implements basic validation to ensure a filename is provided and that the file exists,
with appropriate user feedback.
4. Communication with API:
• Constructs and sends a request to the OpenAI API to obtain explanations based on the
file’s content.
## Design Patterns
1. Command Pattern:
• The script can be considered an example of the Command pattern where the action of executing
the script can be seen as invoking a command that performs a specific business logic.
2. Strategy Pattern:
• The selection of a Markdown highlighter, either glow or tr , can be viewed as an application
of the Strategy
pattern enabling the script to choose between different implementations based on availability.
3. Facade Pattern:
• The script serves as a facade for the complexity of interacting with the OpenAI API,
abstracting away details and providing a simple interface for code exploration.
4. Template Method Pattern:
• The overall flow of the script can be classified as a Template Method where the higher-level
steps (file reading, language detection, API interaction) are fixed, while specific details
(language-specific details) can vary based on input.
## Summary
The provided UNIX-shell script serves as a simple but effective utility for code exploration.
By analyzing the file type and querying a language model, it helps users understand the purpose,
algorithms, and design patterns present in the code. Through effective error handling, a modular
approach to language detection, and a clean API interaction, the script exemplifies good design
practices in shell scripting. This work is licensed under Apache 2.0 license.