Là một kỹ sư backend đã làm việc với nhiều codebase quy mô enterprise (hơn 500k dòng code), tôi hiểu rõ nỗi thốn khi phải tìm một hàm cụ thể giữa hàng ngàn file. Trong bài viết này, tôi sẽ chia sẻ cách tôi xây dựng hệ thống semantic search cho Cursor Workspace sử dụng HolySheep AI — giải pháp giúp tôi tiết kiệm 85%+ chi phí so với các provider thông thường.
Tại Sao Cần Semantic Search Cho Codebase?
Vấn đề tôi gặp phải: codebase của dự án có structure như sau:
/src
/modules
/auth (120 files)
/billing (85 files)
/inventory (200 files)
/notifications (60 files)
/services (150 files)
/utils (90 files)
/types (40 files)Tìm kiếm bằng grep truyền thống không còn đủ khi:
- Tên hàm không mô tả chính xác chức năng
- Cùng một logic được implement ở nhiều nơi với naming khác nhau
- Cần hiểu context của đoạn code thay vì chỉ keyword matching
Kiến Trúc Hệ Thống
Tôi thiết kế hệ thống gồm 3 layer:
┌─────────────────────────────────────────────────────────┐
│ Presentation Layer │
│ (Cursor Extension + VS Code Webview) │
└─────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────┐
│ Service Layer │
│ - SemanticIndexService (indexing, querying) │
│ - CodeChunker (parse, split, embed) │
│ - CacheManager (Redis + in-memory LRU) │
└─────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────┐
│ API Layer │
│ - HolySheep AI (embeddings: text-embedding-3-small) │
│ - Vector Store (Pinecone / Qdrant / in-memory) │
└─────────────────────────────────────────────────────────┘Implementation Chi Tiết
1. Setup Project và Dependencies
// package.json
{
"name": "cursor-semantic-search",
"version": "1.0.0",
"type": "module",
"dependencies": {
"@holysheepai/sdk": "^1.0.0",
"pinecone-client": "^2.0.0",
"lru-cache": "^10.0.0",
"tree-sitter": "^0.20.0"
}
}2. HolySheep AI Client Configuration
// lib/holysheep-client.ts
import { HolySheep } from '@holysheepai/sdk';
class HolySheepClient {
private client: HolySheep;
private cache: Map<string, number[]>;
private cacheHits = 0;
private cacheMisses = 0;
constructor() {
this.client = new HolySheep({
baseURL: 'https://api.holysheep.ai/v1', // ⚠️ BẮT BUỘC
apiKey: process.env.HOLYSHEEP_API_KEY,
});
this.cache = new Map();
// LRU cache 1000 entries, auto-evict sau 1 giờ
setInterval(() => this.cleanExpiredCache(), 3600000);
}
async embed(text: string): Promise<number[]> {
const cacheKey = this.hashText(text);
if (this.cache.has(cacheKey)) {
this.cacheHits++;
return this.cache.get(cacheKey)!;
}
this.cacheMisses++;
const response = await this.client.embeddings.create({
model: 'text-embedding-3-small', // 1536 dimensions, rẻ nhất
input: text,
});
const embedding = response.data[0].embedding;
// Cache với giới hạn 1000 entries
if (this.cache.size >= 1000) {
const firstKey = this.cache.keys().next().value;
this.cache.delete(firstKey);
}
this.cache.set(cacheKey, embedding);
return embedding;
}
async batchEmbed(texts: string[], batchSize = 100): Promise<number[][]> {
const results: number[][] = [];
for (let i = 0; i < texts.length; i += batchSize) {
const batch = texts.slice(i, i + batchSize);
const embeddings = await Promise.all(
batch.map(text => this.embed(text))
);
results.push(...embeddings);
// Rate limit protection: 50ms delay giữa batches
if (i + batchSize < texts.length) {
await this.delay(50);
}
}
return results;
}
getCacheStats() {
const total = this.cacheHits + this.cacheMisses;
return {
hits: this.cacheHits,
misses: this.cacheMisses,
hitRate: total > 0 ? (this.cacheHits / total * 100).toFixed(2) + '%' : '0%',
cacheSize: this.cache.size
};
}
private hashText(text: string): string {
// Dùng simple hash thay vì crypto để tốc độ
let hash = 0;
for (let i = 0; i < text.length; i++) {
const char = text.charCodeAt(i);
hash = ((hash << 5) - hash) + char;
hash = hash & hash;
}
return hash.toString(36);
}
private delay(ms: number): Promise<void> {
return new Promise(resolve => setTimeout(resolve, ms));
}
private cleanExpiredCache(): void {
// Simple cleanup - trong thực tế dùng Map với expiry
if (this.cache.size > 500) {
const keysToDelete = Array.from(this.cache.keys()).slice(0, 200);
keysToDelete.forEach(key => this.cache.delete(key));
}
}
}
export const holysheepClient = new HolySheepClient();3. Code Chunking Strategy
// lib/code-chunker.ts
import * as parser from 'tree-sitter';
import Parser from 'tree-sitter';
interface CodeChunk {
id: string;
content: string;
filePath: string;
startLine: number;
endLine: number;
functionName?: string;
className?: string;
language: string;
chunkType: 'function' | 'class' | 'module' | 'comment';
}
class CodeChunker {
private parsers: Map<string, Parser> = new Map();
constructor() {
this.initParsers();
}
private initParsers(): void {
// Khởi tạo parsers cho các ngôn ngữ phổ biến
const languages = ['typescript', 'javascript', 'python', 'go', 'rust'];
languages.forEach(lang => {
try {
const parser = new Parser();
// parser.setLanguage(require(tree-sitter-${lang}));
this.parsers.set(lang, parser);
} catch (e) {
console.warn(Parser for ${lang} not available);
}
});
}
chunkFile(content: string, filePath: string): CodeChunk[] {
const ext = this.getExtension(filePath);
const chunks: CodeChunk[] = [];
// Strategy 1: Function-level chunking (ưu tiên)
const functionChunks = this.extractFunctions(content, filePath, ext);
chunks.push(...functionChunks);
// Strategy 2: Line-based fallback (cho files không parse được)
if (chunks.length === 0) {
chunks.push(...this.chunkByLines(content, filePath));
}
return chunks.map((chunk, idx) => ({
...chunk,
id: ${filePath}:${chunk.startLine}:${idx}
}));
}
private extractFunctions(
content: string,
filePath: string,
ext: string
): Omit<CodeChunk, 'id'>[] {
const chunks: Omit<CodeChunk, 'id'>[] = [];
// Regex patterns cho các ngôn ngữ phổ biến
const patterns: Record<string, RegExp> = {
typescript: /(?:export\s+)?(?:async\s+)?function\s+(\w+)|(?:const|let|var)\s+(\w+)\s*=\s*(?:async\s*)?\([^)]*\)\s*(?::\s*\w+)?\s*=>/g,
javascript: /(?:export\s+)?(?:async\s+)?function\s+(\w+)|(?:const|let)\s+(\w+)\s*=\s*(?:async\s*)?\([^)]*\)\s*(?::\s*\w+)?\s*=>/g,
python: /^(?:async\s+)?def\s+(\w+)\s*\(/gm,
go: /func\s+(\w+)\s*\(/,
rust: /fn\s+(\w+)\s*</,
};
const pattern = patterns[ext] || patterns.typescript;
let match;
const matches: { name: string; index: number }[] = [];
while ((match = pattern.exec(content)) !== null) {
matches.push({
name: match[1] || match[2] || 'anonymous',
index: match.index
});
}
// Tạo chunks từ các function matches
for (let i = 0; i < matches.length; i++) {
const start = matches[i].index;
const end = i + 1 < matches.length ? matches[i + 1].index : content.length;
const functionContent = content.slice(start, end);
const lines = content.slice(0, start).split('\n');
const startLine = lines.length;
chunks.push({
content: functionContent,
filePath,
startLine,
endLine: startLine + functionContent.split('\n').length,
functionName: matches[i].name,
language: ext,
chunkType: 'function'
});
}
return chunks;
}
private chunkByLines(content: string, filePath: string): Omit<CodeChunk, 'id'>[] {
const lines = content.split('\n');
const chunks: Omit<CodeChunk, 'id'>[] = [];
const chunkSize = 50; // lines per chunk
const overlap = 10;
for (let i = 0; i < lines.length; i += chunkSize - overlap) {
const chunkLines = lines.slice(i, i + chunkSize);
chunks.push({
content: chunkLines.join('\n'),
filePath,
startLine: i + 1,
endLine: Math.min(i + chunkSize, lines.length),
language: this.getExtension(filePath),
chunkType: 'module'
});
}
return chunks;
}
private getExtension(filePath: string): string {
const match = filePath.match(/\.([^.]+)$/);
const ext = match ? match[1].toLowerCase() : 'txt';
// Map extensions
const map: Record<string, string> = {
'ts': 'typescript',
'tsx': 'typescript',
'js': 'javascript',
'jsx': 'javascript',
'py': 'python',
'go': 'go',
'rs': 'rust',
'java': 'java',
};
return map[ext] || ext;
}
}
export const codeChunker = new CodeChunker();4. Semantic Search Service
// services/semantic-search.ts
import { holysheepClient } from '../lib/holysheep-client';
import { codeChunker } from '../lib/code-chunker';
import { Pinecone } from '@pinecone-database/pinecone';
interface SearchResult {
chunk: {
id: string;
content: string;
filePath: string;
startLine: number;
endLine: number;
functionName?: string;
};
score: number;
reasoning?: string;
}
class SemanticSearchService {
private pinecone: Pinecone;
private indexName: string;
private namespace: string;
constructor() {
this.pinecone = new Pinecone({
apiKey: process.env.PINECONE_API_KEY!
});
this.indexName = process.env.PINECONE_INDEX || 'codebase-search';
this.namespace = process.env.CURSOR_WORKSPACE_ID || 'default';
}
async indexWorkspace(rootPath: string): Promise<{
totalChunks: number;
duration: number;
cost: number;
}> {
const startTime = Date.now();
let totalTokens = 0;
// 1. Discovery all code files
const files = await this.discoverFiles(rootPath);
console.log(Found ${files.length} files to index);
// 2. Chunk all files
const allChunks = [];
for (const file of files) {
const content = await this.readFile(file);
const chunks = codeChunker.chunkFile(content, file);
allChunks.push(...chunks);
}
console.log(Created ${allChunks.length} chunks);
// 3. Batch embed với HolySheep AI
const texts = allChunks.map(c => this.createEmbeddingText(c));
const batchSize = 100;
for (let i = 0; i < texts.length; i += batchSize) {
const batch = texts.slice(i, i + batchSize);
await holysheepClient.batchEmbed(batch);
const progress = Math.min(100, ((i + batchSize) / texts.length) * 100);
console.log(Embedding progress: ${progress.toFixed(1)}%);
// Estimate tokens consumed (rough: ~4 chars per token)
totalTokens += batch.reduce((sum, t) => sum + Math.ceil(t.length / 4), 0);
}
// 4. Store in Pinecone
await this.storeChunks(allChunks);
const duration = Date.now() - startTime;
const cost = this.estimateCost(totalTokens);
return {
totalChunks: allChunks.length,
duration,
cost
};
}
async search(
query: string,
options: {
topK?: number;
filter?: Record<string, any>;
includeReasoning?: boolean;
} = {}
): Promise<SearchResult[]> {
const { topK = 10, filter, includeReasoning = false } = options;
// 1. Embed query
const queryEmbedding = await holysheepClient.embed(query);
// 2. Search Pinecone
const index = this.pinecone.Index(this.indexName);
const results = await index.query({
vector: queryEmbedding,
topK,
namespace: this.namespace,
filter,
includeMetadata: true
});
// 3. Rerank với reasoning nếu cần (dùng GPT-4.1 thay vì embedding)
const searchResults: SearchResult[] = results.matches.map(match => ({
chunk: {
id: match.id as string,
content: match.metadata?.content as string,
filePath: match.metadata?.filePath as string,
startLine: match.metadata?.startLine as number,
endLine: match.metadata?.endLine as number,
functionName: match.metadata?.functionName as string | undefined,
},
score: match.score || 0
}));
if (includeReasoning) {
return await this.enhanceWithReasoning(query, searchResults);
}
return searchResults;
}
private async enhanceWithReasoning(
query: string,
results: SearchResult[]
): Promise<SearchResult[]> {
// Dùng DeepSeek V3.2 cho reasoning (rẻ nhất: $0.42/MTok)
const context = results
.slice(0, 5)
.map(r => [${r.chunk.filePath}:${r.chunk.startLine}]\n${r.chunk.content})
.join('\n\n---\n\n');
const prompt = Query: ${query}\n\nSearch Results:\n${context}\n\nExplain why each result is relevant (or not) to the query:;
const response = await fetch('https://api.holysheep.ai/v1/chat/completions', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': Bearer ${process.env.HOLYSHEEP_API_KEY}
},
body: JSON.stringify({
model: 'deepseek-v3.2', // Model rẻ nhất cho reasoning
messages: [{ role: 'user', content: prompt }],
max_tokens: 500
})
});
const data = await response.json();
// Attach reasoning to results
return results.map((r, i) => ({
...r,
reasoning: Result ${i + 1}: ${data.choices?.[0]?.message?.content || 'No reasoning available'}
}));
}
private async storeChunks(chunks: any[]): Promise<void> {
const index = this.pinecone.Index(this.indexName);
// Batch upsert
const batchSize = 100;
for (let i = 0; i < chunks.length; i += batchSize) {
const batch = chunks.slice(i, i + batchSize);
const vectors = await Promise.all(
batch.map(async chunk => ({
id: chunk.id,
values: await holysheepClient.embed(this.createEmbeddingText(chunk)),
metadata: {
content: chunk.content.substring(0, 10000), // Limit metadata size
filePath: chunk.filePath,
startLine: chunk.startLine,
endLine: chunk.endLine,
functionName: chunk.functionName || '',
language: chunk.language,
chunkType: chunk.chunkType
}
}))
);
await index.upsert(vectors, this.namespace);
}
}
private createEmbeddingText(chunk: any): string {
// Tạo text optimized cho embedding
return [${chunk.chunkType}] ${chunk.functionName || chunk.className || 'module'}\n +
File: ${chunk.filePath}\n +
Lines: ${chunk.startLine}-${chunk.endLine}\n +
Code:\n${chunk.content};
}
private async discoverFiles(rootPath: string): Promise<string[]> {
const extensions = ['.ts', '.tsx', '.js', '.jsx', '.py', '.go', '.rs', '.java'];
const files: string[] = [];
// Recursive file discovery
const walkDir = async (dir: string) => {
const entries = await fs.readdir(dir, { withFileTypes: true });
for (const entry of entries) {
const fullPath = path.join(dir, entry.name);
if (entry.isDirectory()) {
// Skip common ignore patterns
if (!['node_modules', '.git', 'dist', 'build', '__pycache__'].includes(entry.name)) {
await walkDir(fullPath);
}
} else if (extensions.some(ext => entry.name.endsWith(ext))) {
files.push(fullPath);
}
}
};
await walkDir(rootPath);
return files;
}
private estimateCost(tokens: number): number {
// HolySheep pricing: text-embedding-3-small $0.002/1K tokens
return (tokens / 1000) * 0.002;
}
}
export const semanticSearch = new SemanticSearchService();Performance Benchmark
Tôi đã test hệ thống với codebase thự