brainy/docs/troubleshooting.md
David Snelling da7d2ed29d feat: migrate embeddings to Candle WASM + remove semantic type inference
Major architectural changes:

1. EMBEDDINGS ENGINE (ONNX → Candle WASM):
   - Replace ONNX Runtime with Rust Candle compiled to WASM
   - Embedded model in WASM binary (no external downloads)
   - Quantized Q8 precision with <50MB memory footprint
   - Zero-download, offline-first operation
   - Same embedding quality (all-MiniLM-L6-v2)

2. REMOVE SEMANTIC TYPE INFERENCE:
   - Delete embeddedKeywordEmbeddings.ts (14MB of pre-computed embeddings)
   - Remove typeAwareQueryPlanner.ts and semanticTypeInference.ts
   - Remove VerbExactMatchSignal (uses keyword embeddings)
   - Update SmartRelationshipExtractor to 3 signals (55%/30%/15% weights)

API CHANGES (requires v7.0.0):
- Removed: inferTypes(), inferNouns(), inferVerbs(), inferIntent()
- Removed: getSemanticTypeInference(), SemanticTypeInference class
- Removed: TypeInference, SemanticTypeInferenceOptions types

Users can still use natural language queries in find() - they just
need to specify type explicitly for type-optimized searches.

PACKAGE SIZE IMPACT:
- Compressed: 90.1 MB → 86.2 MB (-4.3%)
- Uncompressed: 114.4 MB → 100.3 MB (-12%)
- ~448K lines of code removed

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-06 12:52:34 -08:00

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# 🚨 Troubleshooting Guide
Common issues and solutions for Brainy.
## 🤖 Model Loading Issues
### "Failed to initialize Candle Embedding Engine"
**Symptoms**: Error during `brain.init()` with WASM loading failure.
**Causes & Solutions**:
1. **WASM file missing**
```bash
# Verify WASM exists (~90MB with embedded model)
ls -lh dist/embeddings/wasm/pkg/candle_embeddings_bg.wasm
# Rebuild if missing
npm run build
```
2. **Memory too low**
```bash
# Ensure at least 256MB available
# For Docker:
docker run -m 512m my-app
```
3. **Corrupted WASM**
```bash
# Rebuild the Candle WASM
npm run build:candle
npm run build
```
### Slow Initialization (>500ms)
**Symptoms**: Long wait times during first `brain.init()`.
**Cause**: WASM parsing takes ~200ms, which is normal for the 90MB file.
**Solutions**:
```typescript
// Initialize once at startup, not per-request
await brain.init() // Do this once
// Reuse for all requests
const results = await brain.find(query)
```
### Container Out of Memory During Model Load
**Symptoms**: OOM errors in Docker/Kubernetes during initialization.
**Solutions**:
```dockerfile
# Increase memory limit
docker run -m 2g my-app
# Pre-download models at build time (recommended)
RUN npm run download-models
# Use quantized models (default, but explicit)
ENV BRAINY_MODEL_DTYPE=q8
```
## 💾 Storage Issues
### Permission Denied Creating Storage Directory
**Symptoms**: EACCES or permission errors when creating storage files.
**Solutions**:
```bash
# Make directory writable
chmod 755 ./brainy-data
# Use custom writable path
const brain = new Brainy({
storage: {
type: 'filesystem',
path: '/tmp/brainy-data'
}
})
```
### "ENOENT: no such file or directory"
**Symptoms**: File not found errors during storage operations.
**Solutions**:
```bash
# Ensure parent directory exists
mkdir -p ./brainy-data
# Check storage configuration
const brain = new Brainy({
storage: {
type: 'filesystem',
path: '/full/path/to/storage' // Use absolute path
}
})
```
## 🧠 Initialization Issues
### Initialization Hangs or Times Out
**Symptoms**: `brain.init()` never resolves.
**Possible Causes & Solutions**:
1. **Model download timeout**
```bash
# Pre-download models
npm run download-models
# Or force local-only
export BRAINY_ALLOW_REMOTE_MODELS=false
```
2. **Network issues**
```typescript
// Set initialization timeout
const brain = new Brainy()
// Use Promise.race for timeout
const initPromise = Promise.race([
brain.init(),
new Promise((_, reject) =>
setTimeout(() => reject(new Error('Init timeout')), 30000)
)
])
```
3. **Resource constraints**
```bash
# Increase memory for Node.js
NODE_OPTIONS="--max-old-space-size=4096" npm start
```
## 🔍 Search Issues
### No Search Results
**Symptoms**: Empty results from valid queries.
**Debugging Steps**:
1. **Check if data exists**
```typescript
const stats = await brain.getStats()
console.log(`Total items: ${stats.nounCount}`)
```
2. **Verify embedding generation**
```typescript
const id = await brain.add("test content", { nounType: 'content' })
const item = await brain.get(id)
console.log('Item:', item) // Should have metadata and vector
```
3. **Test with exact match**
```typescript
const results = await brain.search("test content") // Exact text
console.log('Exact match results:', results)
```
### Poor Search Quality
**Symptoms**: Irrelevant results, low scores.
**Improvements**:
1. **Add more context to queries**
```typescript
// Instead of: "cat"
const results = await brain.search("domestic cat animal pet")
```
2. **Use metadata filtering**
```typescript
const results = await brain.search("animals", {
where: { category: "pets" },
limit: 10
})
```
3. **Check data quality**
```typescript
// Ensure consistent, descriptive content
await brain.add("Domestic cat - small carnivorous mammal", {
nounType: 'content',
category: "animals",
subcategory: "pets"
})
```
## ⚡ Performance Issues
### Slow Search Performance
**Symptoms**: High search latency.
**Optimizations**:
1. **Enable search cache**
```typescript
const brain = new Brainy({
cache: {
search: {
maxSize: 1000,
ttl: 300000 // 5 minutes
}
}
})
```
2. **Use appropriate limits**
```typescript
// Don't fetch more than needed
const results = await brain.search("query", { limit: 10 })
```
3. **Consider metadata filtering first**
```typescript
// Filter by metadata first, then semantic search
const results = await brain.search("query", {
where: { category: "specific" }, // Reduces search space
limit: 10
})
```
### High Memory Usage
**Symptoms**: Increasing memory consumption over time.
**Solutions**:
1. **Cleanup when done**
```typescript
await brain.cleanup() // Releases resources
```
2. **Use streaming for large datasets**
```typescript
// Process in batches instead of loading all at once
for (let i = 0; i < data.length; i += 100) {
const batch = data.slice(i, i + 100)
await Promise.all(batch.map(item => brain.add(item, { nounType: 'content' })))
}
```
3. **Configure memory limits**
```bash
NODE_OPTIONS="--max-old-space-size=2048" npm start
```
## 🧪 Testing Issues
### Tests Fail in CI/CD
**Symptoms**: Tests pass locally but fail in automated environments.
**Solutions**:
1. **Pre-download models in CI**
```yaml
# .github/workflows/test.yml
- name: Download Models
run: npm run download-models
- name: Test with Local Models
env:
BRAINY_ALLOW_REMOTE_MODELS: false
run: npm test
```
2. **Use temporary filesystem storage in tests**
```typescript
// In test setup
const brain = new Brainy({
storage: { type: 'filesystem', path: '/tmp/brainy-test' }
})
```
3. **Increase timeout for CI**
```typescript
// In test files
describe('Brainy tests', () => {
it('should work', async () => {
// Test code
}, { timeout: 30000 }) // 30 second timeout
})
```
## 📋 Environment-Specific Issues
### Browser CORS Errors
**Symptoms**: Model loading fails in browser due to CORS.
**Solutions**:
```javascript
// Brainy handles CORS automatically via CDN
// No action needed - models load from CORS-enabled mirrors
// If using custom model URLs, ensure CORS headers:
// Access-Control-Allow-Origin: *
```
### Serverless Cold Start Timeouts
**Symptoms**: Lambda/Vercel functions timeout during initialization.
**Solutions**:
```dockerfile
# Pre-bundle models in deployment
RUN npm run download-models
# Set environment variables
ENV BRAINY_ALLOW_REMOTE_MODELS=false
ENV BRAINY_MODELS_PATH=./models
```
### Node.js Module Resolution Issues
**Symptoms**: "Cannot find module" errors.
**Solutions**:
```json
// package.json
{
"type": "module",
"exports": {
".": {
"import": "./dist/index.js",
"require": "./dist/index.js"
}
}
}
```
## 🆘 Getting Help
### Debug Logging
Enable verbose logging to see what's happening:
```typescript
const brain = new Brainy({
logging: { verbose: true }
})
```
### Health Check
Verify your Brainy setup:
```typescript
// Basic health check
try {
const brain = new Brainy()
await brain.init()
const id = await brain.add("health check", { nounType: 'content' })
const results = await brain.search("health")
console.log('✅ Brainy is working correctly')
console.log(`Added item: ${id}`)
console.log(`Search results: ${results.length}`)
} catch (error) {
console.error('❌ Brainy health check failed:', error)
}
```
### Environment Info
Collect environment information:
```bash
# Node.js version
node --version
# Memory limits
node -e "console.log(process.memoryUsage())"
# Platform info
node -e "console.log(process.platform, process.arch)"
# Verify WASM file exists (model embedded inside)
ls -la dist/embeddings/wasm/pkg/candle_embeddings_bg.wasm
```
### Report Issues
When reporting issues, include:
1. **Environment**: Node.js version, OS, memory
2. **Configuration**: Brainy options, environment variables
3. **Error logs**: Full error messages and stack traces
4. **Reproduction**: Minimal code example that demonstrates the issue
**Where to report**:
- [GitHub Issues](https://github.com/your-repo/brainy/issues)
- Include "troubleshooting" label
- Use the issue template
---
**Still having issues?** Check the [Model Loading Guide](guides/model-loading.md) or [open an issue](https://github.com/your-repo/brainy/issues).