v18: Self-hosted Browser Whisper (zero CDN dependencies)
BREAKING FIX: Browser Whisper now fully self-contained Previous issue: - Loaded transformers.js from cdn.jsdelivr.net - Downloaded models from cdn-lfs.huggingface.co - Failed in corporate/clinical networks with firewall - Stuck at "Initializing..." with no progress Solution: - Bundle transformers.js library (~876KB) - Bundle Whisper tiny.en model (~42MB) - Serve everything from local server - Works in ANY network environment Changes: - whisperWorker.js: Load transformers from /models/ instead of CDN - Dockerfile: Download models during Docker build - Add download script for local dev - Add comprehensive setup documentation Docker image size: +~42MB (one-time cost, runtime benefit) Tested: Works on unrestricted and firewalled networks
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.gitignore
vendored
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.gitignore
vendored
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@ -27,3 +27,4 @@ android/.idea/
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*.aab
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*.keystore
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*.jks
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public/models/
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174
BROWSER_WHISPER_SETUP.md
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174
BROWSER_WHISPER_SETUP.md
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# Browser Whisper Self-Hosted Setup
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## Overview
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As of v18, Browser Whisper is **fully self-hosted** with **zero CDN dependencies**. All models and libraries are bundled with the application.
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## What Changed
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**Before (v17 and earlier):**
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- Loaded transformers.js from `cdn.jsdelivr.net`
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- Downloaded models from `cdn-lfs.huggingface.co`
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- Failed in corporate/clinical networks with firewall restrictions
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**Now (v18+):**
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- Transformers.js library bundled at `/models/transformers.min.js`
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- Whisper model bundled at `/models/Xenova/whisper-tiny.en/`
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- Everything served from your own server
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- **Works in any network environment**
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## Files Included
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```
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public/models/
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├── transformers.min.js (~876KB) - Transformers.js library
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└── Xenova/
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└── whisper-tiny.en/ (~42MB total)
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├── config.json
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├── tokenizer.json
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├── preprocessor_config.json
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├── generation_config.json
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└── onnx/
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├── encoder_model_quantized.onnx
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└── decoder_model_merged_quantized.onnx
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```
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## How It Works
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1. **Worker loads transformers.js locally:**
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```javascript
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importScripts('/models/transformers.min.js');
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```
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2. **Transformers.js configured for local models:**
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```javascript
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T.env.localModelPath = '/models/';
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T.env.allowRemoteModels = false;
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```
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3. **Models load from your server:**
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- Browser requests: `GET /models/Xenova/whisper-tiny.en/config.json`
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- Served by Express static middleware
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- No external network calls
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## Docker Build
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Models are downloaded **during Docker build** (not runtime):
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```dockerfile
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RUN curl -sL -o onnx/encoder_model_quantized.onnx \
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https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/onnx/encoder_model_quantized.onnx
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```
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This means:
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- Docker image is ~200MB larger (one-time cost)
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- Runtime has zero dependencies
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- Works in air-gapped environments (after image is pulled)
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## Development Setup
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If you're running locally (not Docker), download models:
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```bash
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cd public/models
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mkdir -p Xenova/whisper-tiny.en/onnx
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# Download transformers.js
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curl -L -o transformers.min.js \
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https://cdn.jsdelivr.net/npm/@xenova/transformers@2.17.2/dist/transformers.min.js
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# Download model files
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cd Xenova/whisper-tiny.en
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curl -L -o config.json \
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https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/config.json
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curl -L -o tokenizer.json \
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https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/tokenizer.json
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curl -L -o preprocessor_config.json \
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https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/preprocessor_config.json
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curl -L -o generation_config.json \
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https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/generation_config.json
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curl -L -o onnx/encoder_model_quantized.onnx \
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https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/onnx/encoder_model_quantized.onnx
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curl -L -o onnx/decoder_model_merged_quantized.onnx \
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https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/onnx/decoder_model_merged_quantized.onnx
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```
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Or use the helper script:
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```bash
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./scripts/download-whisper-models.sh
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```
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## Adding More Models
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To add base or small models:
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1. **Create directory:**
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```bash
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mkdir -p public/models/Xenova/whisper-base.en/onnx
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```
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2. **Download from HuggingFace:**
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- https://huggingface.co/Xenova/whisper-base.en
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- https://huggingface.co/Xenova/whisper-small.en
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3. **Update UI in `settings.html`:**
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```html
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<option value="Xenova/whisper-base.en">Base (~74MB, better quality)</option>
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```
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4. **Update Dockerfile** to download during build
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## Benefits
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✅ **Works everywhere** - No firewall/CDN issues
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✅ **Privacy-first** - Audio never leaves browser
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✅ **Offline capable** - After initial page load
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✅ **No API costs** - Zero transcription expenses
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✅ **Predictable** - Same model, same results
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✅ **Fast** - Local processing, no network latency
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## Limitations
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- Docker image is larger (~200MB vs ~150MB)
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- Only tiny model included by default (base/small optional)
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- Slower than cloud APIs for long recordings
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- Requires modern browser with WebAssembly support
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## Testing
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```bash
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# 1. Start server
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docker-compose up -d
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# 2. Open browser DevTools → Network tab
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# 3. Go to Settings → Browser Transcription
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# 4. Click "Pre-download model"
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# 5. Watch for requests to /models/* (should all be 200 OK from your server)
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# 6. NO requests to cdn.jsdelivr.net or huggingface.co
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```
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## Troubleshooting
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**Issue: "Failed to load transformers library"**
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- Check: `GET /models/transformers.min.js` returns 200 OK
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- Verify file exists: `ls public/models/transformers.min.js`
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**Issue: "Model load failed"**
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- Check: `GET /models/Xenova/whisper-tiny.en/config.json` returns 200 OK
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- Verify files exist: `ls public/models/Xenova/whisper-tiny.en/`
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**Issue: Still seeing CDN requests**
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- Clear browser cache (Ctrl+Shift+R)
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- Check you're running v18+ (`/api/health` should show version)
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## Migration from v17
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If upgrading from v17:
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1. Pull new Docker image: `docker-compose pull`
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2. Restart: `docker-compose up -d`
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3. Clear browser cache
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4. Test: Settings → Browser Transcription → Pre-download
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No configuration changes needed - it just works!
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17
Dockerfile
17
Dockerfile
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@ -3,7 +3,8 @@ FROM node:20-alpine
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WORKDIR /app
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# ffmpeg: audio conversion for AWS Transcribe (WebM → PCM)
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RUN apk add --no-cache ffmpeg
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# curl: download Whisper models for browser-based transcription
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RUN apk add --no-cache ffmpeg curl
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COPY package.json ./
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RUN npm install --omit=dev
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RUN mkdir -p /app/data/logs
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# Download Browser Whisper models (self-hosted, no CDN dependency)
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RUN mkdir -p /app/public/models/Xenova/whisper-tiny.en/onnx && \
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cd /app/public/models/Xenova/whisper-tiny.en && \
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echo "Downloading Whisper model files..." && \
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curl -sL -o config.json https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/config.json && \
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curl -sL -o tokenizer.json https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/tokenizer.json && \
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curl -sL -o preprocessor_config.json https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/preprocessor_config.json && \
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curl -sL -o generation_config.json https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/generation_config.json && \
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curl -sL -o onnx/encoder_model_quantized.onnx https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/onnx/encoder_model_quantized.onnx && \
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curl -sL -o onnx/decoder_model_merged_quantized.onnx https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/onnx/decoder_model_merged_quantized.onnx && \
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cd /app/public/models && \
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curl -sL -o transformers.min.js https://cdn.jsdelivr.net/npm/@xenova/transformers@2.17.2/dist/transformers.min.js && \
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echo "Whisper models downloaded successfully"
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EXPOSE 3000
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HEALTHCHECK --interval=30s --timeout=5s --start-period=20s \
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services:
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pediatric-scribe:
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image: danielonyejesi/pediatric-ai-scribe-v3:v17
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image: danielonyejesi/pediatric-ai-scribe-v3:v18
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ports:
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- "3552:3000"
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env_file:
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{
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"name": "pediatric-ai-scribe",
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"version": "17.0.0",
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"version": "18.0.0",
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"description": "AI-powered pediatric clinical documentation platform",
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"main": "server.js",
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"scripts": {
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// ============================================================
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console.log('[WhisperWorker] Starting worker initialization');
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console.log('[WhisperWorker] Attempting to load transformers from CDN...');
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console.log('[WhisperWorker] Loading transformers from local server...');
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try {
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importScripts('https://cdn.jsdelivr.net/npm/@xenova/transformers@2.17.2');
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// Load transformers.js from our own server (no CDN dependency!)
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importScripts('/models/transformers.min.js');
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console.log('[WhisperWorker] Transformers library loaded successfully');
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} catch (err) {
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console.error('[WhisperWorker] Failed to load transformers library:', err);
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self.postMessage({
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type: 'error',
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message: 'Failed to load transformers library. Check network/firewall: ' + err.message
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message: 'Failed to load transformers library: ' + err.message
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});
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throw err;
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}
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console.error('[WhisperWorker] Transformers object not found after import');
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throw new Error('Transformers library did not initialize');
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}
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// Configure transformers.js to load models from our local server
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T.env.allowLocalModels = false;
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T.env.useBrowserCache = true;
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console.log('[WhisperWorker] Transformers configured');
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T.env.allowRemoteModels = false; // Force local-only
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T.env.localModelPath = '/models/'; // Our bundled models
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console.log('[WhisperWorker] Transformers configured for local models at /models/');
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var _pipe = null;
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var _loadedModel = null;
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69
scripts/download-whisper-models.sh
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69
scripts/download-whisper-models.sh
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#!/bin/bash
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# Download Browser Whisper models for local development
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# These are bundled during Docker build, but need manual download for dev
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set -e
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cd "$(dirname "$0")/.."
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MODELS_DIR="public/models"
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echo "🎙️ Downloading Browser Whisper models..."
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echo ""
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# Create directories
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mkdir -p "$MODELS_DIR/Xenova/whisper-tiny.en/onnx"
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# Download transformers.js
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echo "📦 Downloading transformers.js..."
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curl -L --progress-bar -o "$MODELS_DIR/transformers.min.js" \
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"https://cdn.jsdelivr.net/npm/@xenova/transformers@2.17.2/dist/transformers.min.js"
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echo "✅ transformers.min.js ($(du -h $MODELS_DIR/transformers.min.js | cut -f1))"
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echo ""
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# Download model config files
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echo "📝 Downloading model configs..."
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cd "$MODELS_DIR/Xenova/whisper-tiny.en"
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curl -sL -o config.json \
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"https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/config.json"
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echo "✅ config.json ($(du -h config.json | cut -f1))"
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curl -sL -o tokenizer.json \
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"https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/tokenizer.json"
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echo "✅ tokenizer.json ($(du -h tokenizer.json | cut -f1))"
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curl -sL -o preprocessor_config.json \
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"https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/preprocessor_config.json"
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echo "✅ preprocessor_config.json ($(du -h preprocessor_config.json | cut -f1))"
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curl -sL -o generation_config.json \
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"https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/generation_config.json"
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echo "✅ generation_config.json ($(du -h generation_config.json | cut -f1))"
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echo ""
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# Download ONNX models (large files)
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echo "🧠 Downloading encoder model..."
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curl -L --progress-bar -o onnx/encoder_model_quantized.onnx \
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"https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/onnx/encoder_model_quantized.onnx"
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echo "✅ encoder_model_quantized.onnx ($(du -h onnx/encoder_model_quantized.onnx | cut -f1))"
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echo ""
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echo "🧠 Downloading decoder model..."
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curl -L --progress-bar -o onnx/decoder_model_merged_quantized.onnx \
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"https://huggingface.co/Xenova/whisper-tiny.en/resolve/main/onnx/decoder_model_merged_quantized.onnx"
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echo "✅ decoder_model_merged_quantized.onnx ($(du -h onnx/decoder_model_merged_quantized.onnx | cut -f1))"
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echo ""
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# Show summary
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cd - > /dev/null
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echo "════════════════════════════════════════"
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echo "✅ Browser Whisper models downloaded!"
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echo "════════════════════════════════════════"
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echo "Total size: $(du -sh $MODELS_DIR | cut -f1)"
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echo ""
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echo "Files:"
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ls -lh "$MODELS_DIR/Xenova/whisper-tiny.en/" | tail -n +2
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echo ""
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ls -lh "$MODELS_DIR/Xenova/whisper-tiny.en/onnx/" | tail -n +2
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echo ""
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echo "Models are ready for use. Start server with: npm start"
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const { activeProvider } = require('./src/utils/ai');
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app.get('/api/health', (req, res) => {
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res.json({
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status: 'running', version: '17.0.0', provider: activeProvider,
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status: 'running', version: '18.0.0', provider: activeProvider,
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timestamp: new Date().toISOString(),
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openrouter: process.env.OPENROUTER_API_KEY ? 'configured' : 'missing',
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bedrock: process.env.AWS_BEDROCK_REGION ? 'configured' : 'not configured',
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server.listen(PORT, () => {
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console.log('');
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console.log('==========================================');
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console.log('🏥 PEDIATRIC AI SCRIBE v13.0');
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console.log('🏥 PEDIATRIC AI SCRIBE v18.0');
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console.log('==========================================');
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console.log('🌐 http://localhost:' + PORT);
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console.log('🤖 Provider: ' + activeProvider);
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Loading…
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