Custom Prompt

You can customize the prompt used for code completions by providing a customPrompt function in the options parameter of the copilot.complete method. This allows you to tailor how the AI completes your code based on your specific needs.

Usage

copilot.complete({
    options: {
        customPrompt: metadata => ({
            context: 'Your custom codebase context information here',
            instruction: 'Your custom instructions for code completion here',
            fileContent: 'Your representation of file with cursor position',
        }),
    },
});

The context, instruction, and fileContent properties in the customPrompt function are all optional. If you omit any of these properties, the default values for those fields will be used.

Parameters

The customPrompt function receives a completionMetadata object, which contains information about the current editor state and can be used to tailor the prompt.

Completion Metadata

Property	Type	Description
language	string or undefined	The programming language of the code being completed.
cursorPosition	{ lineNumber: number; column: number }	The current cursor position where the completion should begin.
filename	string or undefined	The name of the file being edited. Only available if you have provided the filename option in the registerCompletion function.
technologies	string[] or undefined	An array of technologies used in the project. Only available if you have provided the technologies option in the registerCompletion function.
relatedFiles	object[] or undefined	An array of objects containing the path and content of related files. Only available if you have provided the relatedFiles option in the registerCompletion function.
textAfterCursor	string	The text that appears after the cursor position.
textBeforeCursor	string	The text that appears before the cursor position.

Return Value Structure

The customPrompt function should return a PromptData object (or a partial one) with the following properties:

Property	Type	Description
context	string or undefined	Information about the codebase context, including technologies, filename, language, etc.
instruction	string or undefined	Instructions for how the AI should complete the code after the cursor position.
fileContent	string or undefined	The representation of the file content showing where the cursor is positioned for completion.

Example

Here's an example of a custom prompt for completing React component code:

const customPrompt = ({
    textBeforeCursor,
    textAfterCursor,
    language,
    filename,
    technologies,
}) => ({
    context: `You're working with a ${language} file named ${filename || 'unnamed'} in a project using ${technologies?.join(', ') || 'React'}.`,
    instruction:
        'Complete the code after the cursor position with appropriate React syntax. Ensure the code follows modern React best practices and matches the style of the existing code.',
    fileContent: `${textBeforeCursor}[CURSOR]${textAfterCursor}`,
});

copilot.complete({
    options: {customPrompt},
});

Partial Customization

You can customize just one aspect of the prompt while letting the system handle the rest:

// Only customize the instruction for code completion
copilot.complete({
    options: {
        customPrompt: metadata => ({
            instruction:
                'Complete this code with an efficient algorithm that handles edge cases.',
        }),
    },
});

// Only customize the context based on project information
copilot.complete({
    options: {
        customPrompt: ({language, technologies, filename}) => ({
            context: `This is a ${language} file named ${filename} in a project using ${technologies?.join(', ')}. The code follows a functional programming paradigm with strict typing.`,
        }),
    },
});

By using a custom prompt, you can guide the AI to complete your code in ways that better match your coding style, project requirements, or specific technologies you're working with.

For additional completionMetadata needs, please open an issue.