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>
2026-01-21 13:29:03 -06:00
parent 3c2022375a
commit 3ad4d5b35d
4 changed files with 75 additions and 2 deletions
@@ -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);
+});