scai/dist/utils/buildContextualPrompt.js

> AI-powered CLI tool for commit messages **and** pull request reviews — using local models.

// File: src/utils/buildContextualPrompt.ts
import chalk from 'chalk';
import path from 'path';
function estimateTokenCount(text) {
    return Math.round(text.length / 4); // simple heuristic approximation
}
export function buildContextualPrompt({ baseInstruction, code, summary, functions, relatedFiles, projectFileTree, }) {
    const parts = [baseInstruction];
    if (summary) {
        parts.push(`📄 File Summary:\n${summary}`);
    }
    if (functions?.length) {
        const formattedFunctions = functions
            .map(fn => `• ${fn.name}:\n${fn.content}`)
            .join('\n\n');
        parts.push(`🔧 Functions:\n${formattedFunctions}`);
    }
    else {
        console.log(chalk.yellow(` ⚠️ No functions found in top rated file.`));
    }
    if (relatedFiles?.length) {
        const formattedRelatedFiles = relatedFiles
            .map(f => {
            const relatedFunctions = f.functions
                .map(fn => `  • ${fn.name}:\n    ${fn.content}`)
                .join('\n\n');
            return `• ${f.path}: ${f.summary}\n${relatedFunctions}`;
        })
            .join('\n\n');
        parts.push(`📚 Related Files:\n${formattedRelatedFiles}`);
    }
    if (projectFileTree) {
        parts.push(`📁 Project File Structure:\n\`\`\`\n${projectFileTree.trim()}\n\`\`\``);
    }
    parts.push(`\n--- CODE START ---\n${code}\n--- CODE END ---`);
    const prompt = parts.join('\n\n');
    const tokenEstimate = estimateTokenCount(prompt);
    // 🔵 Colorized diagnostic output
    // 🔵 Colorized diagnostic output
    const header = chalk.bgBlue.white.bold(' [SCAI] Prompt Overview ');
    const labelColor = chalk.cyan;
    const contentColor = chalk.gray;
    console.log('\n' + header);
    console.log(labelColor('🔢 Token Estimate:'), contentColor(`${tokenEstimate.toLocaleString()} tokens`));
    // 📄 Summary
    if (summary) {
        console.log(labelColor('📄 Summary:'), contentColor(`${estimateTokenCount(summary).toLocaleString()} tokens`));
    }
    // 🔧 Functions
    if (functions?.length) {
        const fnCount = functions.length;
        const fnTokens = functions.reduce((sum, f) => sum + estimateTokenCount(f.content), 0);
        console.log(labelColor(`🔧 Functions (${fnCount}):`), contentColor(`${fnTokens.toLocaleString()} tokens`));
    }
    // 📚 Related Files
    if (relatedFiles?.length) {
        const relCount = relatedFiles.length;
        const relTokens = relatedFiles.reduce((sum, f) => sum + estimateTokenCount(f.summary), 0);
        console.log(labelColor(`📚 Related Files (${relCount}):`), contentColor(`${relTokens.toLocaleString()} tokens`));
        // Optional: Show top 3 file names
        const fileList = relatedFiles.slice(0, 3).map(f => `- ${path.basename(f.path)}`).join('\n');
        if (fileList)
            console.log(contentColor(fileList + (relCount > 3 ? `\n  ...+${relCount - 3} more` : '')));
    }
    // 📁 File Tree
    if (projectFileTree) {
        console.log(labelColor('📁 File Tree:'), contentColor(`${estimateTokenCount(projectFileTree).toLocaleString()} tokens`));
    }
    // 📦 Code Section
    console.log(labelColor('📦 Code:'), contentColor(`${estimateTokenCount(prompt).toLocaleString()} tokens`));
    // 📌 Key
    console.log(labelColor('🔍 Key:'), contentColor('[buildContextualPrompt]\n'));
    return prompt;
}