refactor: simplify build system and improve model loading flexibility

- Remove Rollup bundling in favor of direct TypeScript compilation
- Move from bundled models to dynamic model loading with configurable paths
- Add Docker deployment examples and documentation
- Implement robust model loader with fallback mechanisms
- Update storage adapters for better cross-environment compatibility
- Add comprehensive tests for model loading and package installation
- Simplify package.json scripts and remove complex build configurations
- Clean up deprecated demo files and old bundling scripts

BREAKING CHANGE: Models are no longer bundled with the package. They are now loaded dynamically from CDN or custom paths.

examples/docker-deployment/README.md

@@ -0,0 +1,235 @@
+# Docker Deployment for Brainy
+
+This guide shows how to deploy Brainy applications with embedded models in Docker containers, avoiding the need to download models at runtime.
+
+## Problem
+
+When deploying Node.js applications to Docker containers, `node_modules` is often ignored in `.dockerignore` to reduce image size. However, this means the `@soulcraft/brainy-models` package (containing pre-trained models) won't be included in the container, forcing runtime model downloads from the internet.
+
+## Solution
+
+Brainy now supports loading models from custom directories using:
+
+1. **Environment variable**: `BRAINY_MODELS_PATH` or `MODELS_PATH`
+2. **Configuration option**: `customModelsPath` in `RobustModelLoader`
+
+## Deployment Strategies
+
+### Strategy 1: Embed Models in Docker Image (Recommended)
+
+This approach copies models from `node_modules` to a custom location during the Docker build process.
+
+```dockerfile
+# Multi-stage build to extract models
+FROM node:24-alpine AS builder
+WORKDIR /app
+COPY package*.json ./
+RUN npm ci --only=production
+COPY . .
+
+# Extract models from node_modules
+RUN mkdir -p /app/models && \
+    if [ -d "./node_modules/@soulcraft/brainy-models" ]; then \
+        cp -r ./node_modules/@soulcraft/brainy-models/models/* /app/models/; \
+    fi
+
+# Production stage
+FROM node:24-alpine AS production
+WORKDIR /app
+COPY package*.json ./
+RUN npm ci --only=production --omit=optional
+COPY . .
+COPY --from=builder /app/models /app/models
+
+# Set environment variable
+ENV BRAINY_MODELS_PATH=/app/models
+
+CMD ["node", "dist/your-app.js"]
+```
+
+### Strategy 2: Mount Models as Volume
+
+Mount pre-downloaded models as a Docker volume:
+
+```yaml
+services:
+  brainy-app:
+    image: your-brainy-app
+    environment:
+      - BRAINY_MODELS_PATH=/models
+    volumes:
+      - ./models:/models:ro
+```
+
+### Strategy 3: Init Container Pattern
+
+Use an init container to download models before starting your application:
+
+```yaml
+services:
+  model-downloader:
+    image: node:24-alpine
+    volumes:
+      - brainy-models:/models
+    command: |
+      sh -c "
+        npm install @soulcraft/brainy-models
+        cp -r node_modules/@soulcraft/brainy-models/models/* /models/
+      "
+
+  brainy-app:
+    image: your-brainy-app
+    environment:
+      - BRAINY_MODELS_PATH=/models
+    volumes:
+      - brainy-models:/models:ro
+    depends_on:
+      - model-downloader
+
+volumes:
+  brainy-models:
+```
+
+## Configuration Options
+
+### Environment Variables
+
+```bash
+# Primary environment variable
+BRAINY_MODELS_PATH=/app/models
+
+# Alternative variable name
+MODELS_PATH=/app/models
+```
+
+### Programmatic Configuration
+
+```javascript
+import { BrainyData, RobustModelLoader } from '@soulcraft/brainy'
+
+// Option 1: Configure via RobustModelLoader
+const loader = new RobustModelLoader({
+  customModelsPath: '/app/models'
+})
+
+// Option 2: Environment variable (automatic)
+// Just set BRAINY_MODELS_PATH and it will be used automatically
+```
+
+## Model Directory Structure
+
+Brainy will search for models in the following subdirectories (in order):
+
+```
+/app/models/
+├── universal-sentence-encoder/          # Direct path
+├── models/universal-sentence-encoder/   # @soulcraft/brainy-models structure
+├── tfhub/universal-sentence-encoder/    # TensorFlow Hub structure
+├── use/                                 # Short name
+└── model.json                          # Root directory
+```
+
+## Cloud Run Deployment
+
+For Google Cloud Run, use the embedded models strategy:
+
+```dockerfile
+FROM node:24-alpine
+WORKDIR /app
+COPY package*.json ./
+RUN npm ci --only=production
+COPY . .
+
+# Copy models during build
+RUN if [ -d "./node_modules/@soulcraft/brainy-models" ]; then \
+        mkdir -p /app/models && \
+        cp -r ./node_modules/@soulcraft/brainy-models/models/* /app/models/; \
+    fi
+
+ENV BRAINY_MODELS_PATH=/app/models
+ENV PORT=8080
+EXPOSE 8080
+
+CMD ["node", "dist/server.js"]
+```
+
+Deploy with:
+
+```bash
+gcloud run deploy brainy-app \
+  --source . \
+  --platform managed \
+  --region us-central1 \
+  --allow-unauthenticated \
+  --memory 2Gi \
+  --cpu 1
+```
+
+## AWS Lambda/ECS Deployment
+
+Similar approach works for AWS services:
+
+```dockerfile
+FROM public.ecr.aws/lambda/nodejs:24
+
+# Copy models during build
+COPY package*.json ./
+RUN npm ci --only=production
+COPY . .
+RUN mkdir -p /var/task/models && \
+    cp -r ./node_modules/@soulcraft/brainy-models/models/* /var/task/models/
+
+ENV BRAINY_MODELS_PATH=/var/task/models
+
+CMD ["index.handler"]
+```
+
+## Verification
+
+Your application logs should show:
+
+```
+✅ Found model at custom path: /app/models/universal-sentence-encoder/model.json
+✅ Successfully loaded model from custom directory
+   Using custom model path for Docker/production deployment
+```
+
+Instead of:
+
+```
+⚠️ Local model not found. Falling back to remote model loading.
+```
+
+## Benefits
+
+1. **Faster startup**: No model download time
+2. **Offline deployment**: Works without internet access
+3. **Predictable performance**: No network dependency
+4. **Smaller runtime image**: Can exclude dev dependencies
+5. **Security**: No external network calls required
+
+## Troubleshooting
+
+### Models not found
+
+1. Check the environment variable is set: `echo $BRAINY_MODELS_PATH`
+2. Verify models directory exists: `ls -la /app/models`
+3. Check model structure: `find /app/models -name "model.json"`
+
+### Memory issues
+
+Models require approximately 500MB of RAM. Ensure your container has sufficient memory:
+
+```yaml
+deploy:
+  resources:
+    limits:
+      memory: 2G
+```
+
+### Build failures
+
+If `@soulcraft/brainy-models` is not available during build:
+1. Ensure it's in `dependencies`, not `devDependencies`
+2. Use `npm ci --only=production` instead of `npm install`
+3. Check the package is properly published and accessible