Download embedding model to ~/.codegraph/models on install

The nomic-ai model is now downloaded during npm install via a postinstall
script and stored globally in ~/.codegraph/models (shared across projects)
instead of per-project in .codegraph/models.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Colby McHenry
2026-01-21 13:29:03 -06:00
co-authored by Claude Opus 4.5
parent 3c2022375a
commit 3ad4d5b35d
4 changed files with 75 additions and 2 deletions
+2
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@@ -9,10 +9,12 @@
},
"files": [
"dist",
"scripts",
"README.md"
],
"scripts": {
"build": "tsc && npm run copy-assets",
"postinstall": "node scripts/postinstall.js",
"copy-assets": "cp -r src/extraction/queries dist/extraction/ && cp src/db/schema.sql dist/db/",
"dev": "tsc --watch",
"cli": "npm run build && node dist/bin/codegraph.js",
+68
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@@ -0,0 +1,68 @@
#!/usr/bin/env node
/**
* Postinstall script - downloads the embedding model to ~/.codegraph/models
* This runs after `npm install` or `npx @colbymchenry/codegraph`
*/
const { existsSync, mkdirSync } = require('fs');
const { join } = require('path');
const { homedir } = require('os');
const CODEGRAPH_DIR = join(homedir(), '.codegraph');
const MODELS_DIR = join(CODEGRAPH_DIR, 'models');
const MODEL_ID = 'nomic-ai/nomic-embed-text-v1.5';
async function downloadModel() {
// Ensure directories exist
if (!existsSync(CODEGRAPH_DIR)) {
mkdirSync(CODEGRAPH_DIR, { recursive: true });
}
if (!existsSync(MODELS_DIR)) {
mkdirSync(MODELS_DIR, { recursive: true });
}
// Check if model is already cached
const modelCachePath = join(MODELS_DIR, MODEL_ID.replace('/', '/'));
if (existsSync(modelCachePath)) {
console.log('Embedding model already downloaded.');
return;
}
console.log('Downloading embedding model (~130MB)...');
console.log('This is a one-time download for semantic code search.\n');
try {
// Dynamic import for @xenova/transformers (ESM-only package)
const { pipeline, env } = await import('@xenova/transformers');
// Configure cache directory
env.cacheDir = MODELS_DIR;
// Download with progress
await pipeline('feature-extraction', MODEL_ID, {
progress_callback: (progress) => {
if (progress.status === 'progress' && progress.file && progress.progress !== undefined) {
const fileName = progress.file.split('/').pop();
const percent = Math.round(progress.progress);
process.stdout.write(`\rDownloading ${fileName}... ${percent}% `);
} else if (progress.status === 'done') {
process.stdout.write('\n');
}
},
});
console.log('\nEmbedding model ready!');
} catch (error) {
// Don't fail the install if model download fails
// User can still use codegraph without semantic search
console.log('\nNote: Could not download embedding model.');
console.log('Semantic search will download it on first use.');
if (process.env.DEBUG) {
console.error(error);
}
}
}
downloadModel().catch(() => {
// Silent exit - don't break npm install
process.exit(0);
});
-1
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@@ -760,7 +760,6 @@ export class CodeGraph {
if (!this.vectorManager) {
this.vectorManager = createVectorManager(this.db.getDb(), this.queries, {
embedder: {
cacheDir: path.join(this.projectRoot, '.codegraph', 'models'),
showProgress: true,
},
});
+5 -1
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@@ -7,6 +7,10 @@
import * as path from 'path';
import * as fs from 'fs';
import { homedir } from 'os';
// Global model cache directory (shared across all projects)
const GLOBAL_MODELS_DIR = path.join(homedir(), '.codegraph', 'models');
// Dynamic import for @xenova/transformers (ESM-only package)
// We use dynamic import to support CommonJS builds
@@ -89,7 +93,7 @@ export class TextEmbedder {
constructor(options: EmbedderOptions = {}) {
this.modelId = options.modelId || DEFAULT_MODEL;
this.cacheDir = options.cacheDir || '.codegraph/models';
this.cacheDir = options.cacheDir || GLOBAL_MODELS_DIR;
this.showProgress = options.showProgress ?? false;
}