sourceprompt

来源推广

将您的代码库转换为提示，您可以将其输入LLM。

简而言之：它在指定的目录 / git repostiory中扫描所有文本文件，并将其内容（以及他们的路径）放入结构化的标记文档中。

默认情况下，它提供了预定义的提示，可以使用-r省略或使用-p选项替换。

安装

从发行版中下载二进制或使用以下方式安装：

go install github.com/rostrovsky/sourceprompt@latest

忽略文件 /路径

• 文件/目录以开始.
• 二进制文件

标志

• -i, --include - 应包括的路径的正则态度模式。
• -e, --exclude - 应排除的路径的正则态度模式。
• -o, --output - 输出文件路径。如果未指定，则将输出打印到stdout 。
• -p, --prompt prompt-提示文件路径或URL。允许指定将放置在输出开始时的自定义提示。如果未指定，将使用默认提示。
• -r, --raw从输出中删除提示。
• -v, --verbose启用时打印调试信息。

例子

输出到Stdout

 # output to stdout
sourceprompt /path/to/dir
sourceprompt /path/to/dir -v # debug
sourceprompt https://github.com/some/repo

# use remote git repo for codebase and remote prompt
sourceprompt https://github.com/some/repo -p https://raw.githubusercontent.com/another/repo/prompt.md -o out.md

# output to stdout without default prompt
sourceprompt /path/to/dir -r

# output to file
sourceprompt /path/to/dir -o out.md

# output to file with custom prompt
sourceprompt /path/to/dir -o out.md -p my_prompt.txt

# include only src/ files
sourceprompt /path/to/dir -o out.md -i ' ^src '

# include only C source files
sourceprompt /path/to/dir -o out.md -i ' .c$ ' -i ' .h$ '

# exclude markdown files
sourceprompt /path/to/dir -o out.md -e ' .md$ '

# exclude multiple types
sourceprompt /path/to/dir -o out.md -e ' .md$ ' -e ' .txt$ ' -e ' LICENSE ' 

默认提示

 You will be provided with a markdown text (under the "---" separator) containing the contents of a codebase. Each code snippet will be enclosed in code fences, along with the corresponding file name. Your task is to analyze the codebase and gain a comprehensive understanding of its structure, functionality, and key features.

Please follow these steps:

1. Read through the entire codebase carefully, paying attention to the file names and the code within each code fence.
2. Identify the main components, modules, or classes of the codebase and their responsibilities. Summarize the purpose and functionality of each significant component.
3. Analyze the relationships and dependencies between different parts of the codebase. Identify any important interactions, data flow, or control flow between the components.
4. Extract the most important features and functionalities implemented in the codebase. Highlight any critical algorithms, data structures, or design patterns used.
5. Consider the overall architecture and design of the codebase. Identify any architectural patterns or principles followed, such as MVC, MVVM, or microservices.
6. Evaluate the code quality, readability, and maintainability. Note any areas that could be improved or any potential issues or vulnerabilities.
7. Provide a summary of your analysis, including the key insights, strengths, and weaknesses of the codebase. Offer suggestions for improvements or optimizations, if applicable.
8. Based on your understanding of the codebase, provide guidance on how AI agents can effectively operate across the entire codebase. Identify the entry points, important functions, or APIs that the agents should focus on for interaction and manipulation.
9. Discuss any specific considerations or challenges that AI agents may face when working with this codebase, such as dependencies, external libraries, or platform-specific requirements.
10. Conclude your analysis by providing a high-level overview of the codebase's functionality, architecture, and potential use cases. Highlight any notable features or aspects that make this codebase unique or valuable.

Your analysis should be thorough, insightful, and aimed at enabling AI agents to effectively understand and operate within the given codebase. Provide clear explanations and examples to support your findings and recommendations.

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