bump version to v0.8.2

This changes the dockerfile as well.

.claude/settings.local.json

@@ -4,7 +4,9 @@
       "Bash(mkdir:*)",
       "Bash(uv run:*)",
       "Bash(uv add:*)",
-      "Bash(uv sync:*)"
+      "Bash(uv sync:*)",
+      "Bash(tree:*)",
+      "WebFetch(domain:www.dash-bootstrap-components.com)"
     ],
     "deny": [],
     "ask": [],

.gitea/workflows/bump-and-release.yml

@@ -0,0 +1,52 @@
+name: Bump Version and Release
+
+on:
+  workflow_dispatch:
+    inputs:
+      bump_type:
+        description: 'Version bump type'
+        required: true
+        type: choice
+        options:
+          - patch
+          - minor
+          - major
+
+jobs:
+  bump-and-release:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          token: ${{ secrets.GITEA_TOKEN }}
+          fetch-depth: 0
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Bump version
+        id: bump
+        run: |
+          python bump_version.py ${{ github.event.inputs.bump_type }}
+          NEW_VERSION=$(grep -oP 'version = "\K[^"]+' pyproject.toml)
+          echo "version=$NEW_VERSION" >> $GITHUB_OUTPUT
+          echo "tag=v$NEW_VERSION" >> $GITHUB_OUTPUT
+
+      - name: Commit and tag
+        run: |
+          git config user.name "gitea-actions[bot]"
+          git config user.email "gitea-actions[bot]@users.noreply.gitea.io"
+          git add pyproject.toml
+          git commit -m "bump version to v${{ steps.bump.outputs.version }}"
+          git tag v${{ steps.bump.outputs.version }}
+
+      - name: Push changes
+        run: |
+          git push origin main
+          git push origin v${{ steps.bump.outputs.version }}

.gitea/workflows/release.yml

@@ -66,27 +66,20 @@ jobs:
           echo "## Installation" >> release-notes.md
           echo "" >> release-notes.md
           echo '```bash' >> release-notes.md
-          echo 'uv sync' >> release-notes.md
-          echo 'uv run python main.py' >> release-notes.md
+          echo 'pip install embeddingbuddy' >> release-notes.md
+          echo 'embeddingbuddy serve' >> release-notes.md
           echo '```' >> release-notes.md
 
       - name: Create Release
-        uses: actions/create-release@v1
+        uses: akkuman/gitea-release-action@v1
         env:
-          GITHUB_TOKEN: ${{ secrets.GITEA_TOKEN }}
+          NODE_OPTIONS: '--experimental-fetch'
         with:
+          token: ${{ secrets.GITEA_TOKEN }}
           tag_name: ${{ github.ref_name || github.event.inputs.version }}
           release_name: Release ${{ github.ref_name || github.event.inputs.version }}
           body_path: release-notes.md
           draft: false
           prerelease: false
-
-      - name: Upload Release Assets
-        uses: actions/upload-release-asset@v1
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITEA_TOKEN }}
-        with:
-          upload_url: ${{ steps.create_release.outputs.upload_url }}
-          asset_path: dist/
-          asset_name: embeddingbuddy-dist
-          asset_content_type: application/zip
+          files: |-
+            dist/*

.github/workflows/docker-release.yml

@@ -0,0 +1,54 @@
+name: Docker Release
+
+on:
+  push:
+    tags:
+      - 'v[0-9]+.[0-9]+.[0-9]+'
+  workflow_dispatch:
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Log in to Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+          tags: |
+            type=ref,event=tag
+            type=semver,pattern={{version}}
+            type=semver,pattern={{major}}.{{minor}}
+            type=semver,pattern={{major}}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          platforms: linux/amd64,linux/arm64
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max

.github/workflows/pypi-release.yml

@@ -0,0 +1,33 @@
+name: PyPI Release
+
+on:
+  push:
+    tags:
+      - 'v[0-9]+.[0-9]+.[0-9]+'
+  workflow_dispatch:
+
+jobs:
+  pypi-publish:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      id-token: write  # For trusted publishing
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+
+      - name: Build package
+        run: |
+          uv build
+
+      - name: Publish to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1

CLAUDE.md

@@ -21,26 +21,23 @@ uv sync
 
 **Run the application:**
 
-Development mode (with auto-reload):
+Using the CLI (recommended):
+
 ```bash
-uv run run_dev.py
+# Production mode (no debug, no auto-reload)
+embeddingbuddy serve
+
+# Development mode (debug + auto-reload on code changes)
+embeddingbuddy serve --dev
+
+# Debug logging only (no auto-reload)
+embeddingbuddy serve --debug
+
+# With custom host/port
+embeddingbuddy serve --host 0.0.0.0 --port 8080
 ```
 
-Production mode (with Gunicorn WSGI server):
-```bash
-# First install production dependencies
-uv sync --extra prod
-
-# Then run in production mode
-uv run run_prod.py
-```
-
-Legacy mode (basic Dash server):
-```bash
-uv run main.py
-```
-
-The app will be available at http://127.0.0.1:8050
+The app will be available at <http://127.0.0.1:8050> by default
 
 **Run tests:**
 
@@ -201,6 +198,52 @@ Uses modern Python stack with uv for dependency management:
 - **Testing:** pytest for test framework
 - **Dev Tools:** uv for package management
 
+## CI/CD and Release Management
+
+### Repository Setup
+
+This project uses a **dual-repository workflow**:
+
+- **Primary repository:** Gitea instance at `git.hawt.cloud` (read-write)
+- **Mirror repository:** GitHub (read-only mirror)
+
+### Workflow Organization
+
+**Gitea Workflows (`.gitea/workflows/`):**
+- **`bump-and-release.yml`** - Manual version bumping workflow
+  - Runs `bump_version.py` to update version in `pyproject.toml`
+  - Commits changes and creates git tag
+  - Pushes to Gitea (main branch + tag)
+  - Triggered manually via workflow_dispatch with choice of patch/minor/major bump
+- **`release.yml`** - Automated release creation
+  - Triggered when version tags are pushed
+  - Runs tests, builds packages
+  - Creates Gitea release with artifacts
+- **`test.yml`** - Test suite execution
+- **`security.yml`** - Security scanning
+
+**GitHub Workflows (`.github/workflows/`):**
+- **`docker-release.yml`** - Builds and publishes Docker images
+- **`pypi-release.yml`** - Publishes packages to PyPI
+- These workflows are read-only (no git commits/pushes) and create artifacts only
+
+### Release Process
+
+1. Run manual bump workflow on Gitea: **Actions → Bump Version and Release**
+2. Select version bump type (patch/minor/major)
+3. Workflow commits version change and pushes tag to Gitea
+4. Tag push triggers `release.yml` on Gitea (creates release)
+5. GitHub mirror receives tag and triggers artifact builds (Docker, PyPI)
+
+### Version Management
+
+Use `bump_version.py` for version updates:
+```bash
+python bump_version.py patch    # 0.3.0 -> 0.3.1
+python bump_version.py minor    # 0.3.0 -> 0.4.0
+python bump_version.py major    # 0.3.0 -> 1.0.0
+```
+
 ## Development Guidelines
 
 **When adding new features:**
@@ -214,7 +257,7 @@ Uses modern Python stack with uv for dependency management:
 **Code Organization Principles:**
 
 - Single responsibility principle
-- Clear module boundaries  
+- Clear module boundaries
 - Testable, isolated components
 - Configuration over hardcoding
 - Error handling at appropriate layers

Dockerfile

@@ -2,6 +2,9 @@
 # Stage 1: Builder
 FROM python:3.11-slim as builder
 
+# Create non-root user early in builder stage
+RUN groupadd -r appuser && useradd -r -g appuser appuser
+
 # Install system dependencies for building Python packages
 RUN apt-get update && apt-get install -y \
     build-essential \
@@ -20,11 +23,17 @@ COPY pyproject.toml uv.lock ./
 
 # Copy source code (needed for editable install)
 COPY src/ src/
-COPY main.py .
-COPY wsgi.py .
-COPY run_prod.py .
 COPY assets/ assets/
 
+# Change ownership of source files before building (lighter I/O)
+RUN chown -R appuser:appuser /app
+
+# Create and set permissions for appuser home directory (needed for uv cache)
+RUN mkdir -p /home/appuser && chown -R appuser:appuser /home/appuser
+
+# Switch to non-root user before building
+USER appuser
+
 # Create virtual environment and install dependencies (including production extras)
 RUN uv venv .venv
 RUN uv sync --frozen --extra prod 
@@ -32,23 +41,25 @@ RUN uv sync --frozen --extra prod
 # Stage 2: Runtime
 FROM python:3.11-slim as runtime
 
+# Create non-root user in runtime stage
+RUN groupadd -r appuser && useradd -r -g appuser appuser
+
 # Install runtime dependencies for compiled packages
 RUN apt-get update && apt-get install -y \
     libgomp1 \
     && rm -rf /var/lib/apt/lists/*
 
-# Set working directory
+# Set working directory and change ownership (small directory)
 WORKDIR /app
+RUN chown appuser:appuser /app
 
-# Copy virtual environment from builder stage
-COPY --from=builder /app/.venv /app/.venv
+# Copy files from builder with correct ownership
+COPY --from=builder --chown=appuser:appuser /app/.venv /app/.venv
+COPY --from=builder --chown=appuser:appuser /app/src /app/src
+COPY --from=builder --chown=appuser:appuser /app/assets /app/assets
 
-# Copy application files from builder stage
-COPY --from=builder /app/src /app/src
-COPY --from=builder /app/main.py /app/main.py
-COPY --from=builder /app/assets /app/assets
-COPY --from=builder /app/wsgi.py /app/wsgi.py
-COPY --from=builder /app/run_prod.py /app/run_prod.py
+# Switch to non-root user
+USER appuser
 
 # Make sure the virtual environment is in PATH
 ENV PATH="/app/.venv/bin:$PATH"
@@ -69,5 +80,5 @@ EXPOSE 8050
 HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
     CMD python -c "import requests; requests.get('http://localhost:8050/', timeout=5)" || exit 1
 
-# Run application with Gunicorn in production
-CMD ["python", "run_prod.py"]
+# Run application in production mode (no debug, no auto-reload)
+CMD ["embeddingbuddy", "serve"]

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 Austin Godber - EmbeddingBuddy
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -28,6 +28,61 @@ documents and prompts to understand how queries relate to your content.
 - **Sidebar layout** with controls on left, large visualization area on right
 - **Real-time visualization** optimized for small to medium datasets
 
+## Network Dependency
+
+**Note:** The application loads the Transformers.js library (v3.0.0) from `cdn.jsdelivr.net` for client-side embedding generation. This requires an active internet connection and sends requests to a third-party CDN. The application will function without internet if you only use the file upload features for pre-computed embeddings.
+
+## Quick Start
+
+### Installation
+
+**Option 1: Install with uv (recommended)**
+
+```bash
+# Install as a CLI tool (no need to clone the repo)
+uv tool install embeddingbuddy
+
+# Run the application
+embeddingbuddy serve
+```
+
+**Option 2: Install with pip/pipx**
+
+```bash
+# Install with pipx (isolated environment)
+pipx install embeddingbuddy
+
+# Or install with pip
+pip install embeddingbuddy
+
+# Run the application
+embeddingbuddy
+```
+
+**Option 3: Run with Docker**
+
+```bash
+# Pull and run the Docker image
+docker run -p 8050:8050 ghcr.io/godber/embedding-buddy:latest
+```
+
+The application will be available at <http://127.0.0.1:8050>
+
+### Using the Application
+
+1. **Open your browser** to <http://127.0.0.1:8050>
+2. **Upload your data**:
+   - Drag and drop an NDJSON file containing embeddings (see Data Format below)
+   - Optionally upload a second file with prompts to compare against documents
+3. **Choose visualization settings**:
+   - Select dimensionality reduction method (PCA, t-SNE, or UMAP)
+   - Choose 2D or 3D visualization
+   - Pick color coding (by category, subcategory, or tags)
+4. **Explore**:
+   - Click points to view full content
+   - Toggle prompt visibility
+   - Rotate and zoom 3D plots
+
 ## Data Format
 
 EmbeddingBuddy accepts newline-delimited JSON (NDJSON) files for both documents
@@ -73,26 +128,18 @@ uv sync
 
 2. **Run the application:**
 
-**Development mode** (with auto-reload):
-
 ```bash
-uv run run_dev.py
-```
+# Production mode (no debug, no auto-reload)
+embeddingbuddy serve
 
-**Production mode** (with Gunicorn WSGI server):
+# Development mode (debug + auto-reload on code changes)
+embeddingbuddy serve --dev
 
-```bash
-# Install production dependencies
-uv sync --extra prod
+# Debug logging only (no auto-reload)
+embeddingbuddy serve --debug
 
-# Run in production mode
-uv run run_prod.py
-```
-
-**Legacy mode** (basic Dash server):
-
-```bash
-uv run main.py
+# Custom host/port
+embeddingbuddy serve --host 0.0.0.0 --port 8080
 ```
 
 3. **Open your browser** to <http://127.0.0.1:8050>
@@ -152,22 +199,36 @@ The application follows a modular architecture for improved maintainability and
 
 ```text
 src/embeddingbuddy/
-├── config/          # Configuration management
-│   └── settings.py  # Centralized app settings
-├── data/           # Data parsing and processing
-│   ├── parser.py   # NDJSON parsing logic
-│   └── processor.py # Data transformation utilities
-├── models/         # Data schemas and algorithms
-│   ├── schemas.py  # Pydantic data models
-│   └── reducers.py # Dimensionality reduction algorithms
-├── visualization/ # Plot creation and styling
-│   ├── plots.py   # Plot factory and creation logic
-│   └── colors.py  # Color mapping utilities
-├── ui/            # User interface components
-│   ├── layout.py  # Main application layout
-│   ├── components/ # Reusable UI components
-│   └── callbacks/ # Organized callback functions
-└── utils/         # Utility functions
+├── app.py                     # Main application entry point and factory
+├── config/                    # Configuration management
+│   └── settings.py            # Centralized app settings
+├── data/                      # Data parsing and processing
+│   ├── parser.py              # NDJSON parsing logic
+│   ├── processor.py           # Data transformation utilities
+│   └── sources/               # Data source integrations
+│       └── opensearch.py      # OpenSearch data source
+├── models/                    # Data schemas and algorithms
+│   ├── schemas.py             # Pydantic data models
+│   ├── reducers.py            # Dimensionality reduction algorithms
+│   └── field_mapper.py        # Field mapping utilities
+├── visualization/             # Plot creation and styling
+│   ├── plots.py               # Plot factory and creation logic
+│   └── colors.py              # Color mapping utilities
+├── ui/                        # User interface components
+│   ├── layout.py              # Main application layout
+│   ├── components/            # Reusable UI components
+│   │   ├── sidebar.py         # Sidebar component
+│   │   ├── upload.py          # Upload components
+│   │   ├── textinput.py       # Text input components
+│   │   └── datasource.py      # Data source components
+│   └── callbacks/             # Organized callback functions
+│       ├── data_processing.py # Data upload/processing callbacks
+│       ├── visualization.py   # Plot update callbacks
+│       └── interactions.py    # User interaction callbacks
+└── utils/                     # Utility functions
+
+# CLI entry point
+embeddingbuddy serve    # Main CLI command to start the server
 ```
 
 ### Testing

main.py

@@ -1,10 +0,0 @@
-from src.embeddingbuddy.app import create_app, run_app
-
-
-def main():
-    app = create_app()
-    run_app(app)
-
-
-if __name__ == "__main__":
-    main()

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "embeddingbuddy"
-version = "0.4.0"
+version = "0.8.2"
 description = "A Python Dash application for interactive exploration and visualization of embedding vectors through dimensionality reduction techniques."
 readme = "README.md"
 requires-python = ">=3.11"
@@ -17,6 +17,10 @@ dependencies = [
     "opensearch-py>=3.0.0",
 ]
 
+[project.scripts]
+embeddingbuddy = "embeddingbuddy.cli:main"
+embeddingbuddy-serve = "embeddingbuddy.app:serve"
+
 [project.optional-dependencies]
 test = [
     "pytest>=8.4.1",
@@ -50,3 +54,6 @@ where = ["src"]
 
 [tool.setuptools.package-dir]
 "" = "src"
+
+[tool.setuptools.package-data]
+embeddingbuddy = ["assets/**/*"]

run_dev.py

@@ -1,26 +0,0 @@
-#!/usr/bin/env python3
-"""
-Development runner with auto-reload enabled.
-This runs the Dash development server with hot reloading.
-"""
-import os
-from src.embeddingbuddy.app import create_app, run_app
-
-def main():
-    """Run the application in development mode with auto-reload."""
-    # Force development settings
-    os.environ["EMBEDDINGBUDDY_ENV"] = "development"
-    os.environ["EMBEDDINGBUDDY_DEBUG"] = "true"
-    
-    print("🚀 Starting EmbeddingBuddy in development mode...")
-    print("📁 Auto-reload enabled - changes will trigger restart")
-    print("🌐 Server will be available at http://127.0.0.1:8050")
-    print("⏹️  Press Ctrl+C to stop")
-    
-    app = create_app()
-    
-    # Run with development server (includes auto-reload when debug=True)
-    run_app(app, debug=True)
-
-if __name__ == "__main__":
-    main()

run_prod.py

@@ -1,49 +0,0 @@
-#!/usr/bin/env python3
-"""
-Production runner using Gunicorn WSGI server.
-This provides better performance and stability for production deployments.
-"""
-import os
-import subprocess
-import sys
-from src.embeddingbuddy.config.settings import AppSettings
-
-def main():
-    """Run the application in production mode with Gunicorn."""
-    # Force production settings
-    os.environ["EMBEDDINGBUDDY_ENV"] = "production"
-    os.environ["EMBEDDINGBUDDY_DEBUG"] = "false"
-    
-    print("🚀 Starting EmbeddingBuddy in production mode...")
-    print(f"⚙️  Workers: {AppSettings.GUNICORN_WORKERS}")
-    print(f"🌐 Server will be available at http://{AppSettings.GUNICORN_BIND}")
-    print("⏹️  Press Ctrl+C to stop")
-    
-    # Gunicorn command
-    cmd = [
-        "gunicorn",
-        "--workers", str(AppSettings.GUNICORN_WORKERS),
-        "--bind", AppSettings.GUNICORN_BIND,
-        "--timeout", str(AppSettings.GUNICORN_TIMEOUT),
-        "--keepalive", str(AppSettings.GUNICORN_KEEPALIVE),
-        "--access-logfile", "-",
-        "--error-logfile", "-",
-        "--log-level", "info",
-        "wsgi:application"
-    ]
-    
-    try:
-        subprocess.run(cmd, check=True)
-    except KeyboardInterrupt:
-        print("\n🛑 Shutting down...")
-        sys.exit(0)
-    except subprocess.CalledProcessError as e:
-        print(f"❌ Error running Gunicorn: {e}")
-        sys.exit(1)
-    except FileNotFoundError:
-        print("❌ Gunicorn not found. Install it with: uv add gunicorn")
-        print("💡 Or run in development mode with: python run_dev.py")
-        sys.exit(1)
-
-if __name__ == "__main__":
-    main()

src/embeddingbuddy/app.py

@@ -1,21 +1,53 @@
-import dash
-import dash_bootstrap_components as dbc
-from .config.settings import AppSettings
-from .ui.layout import AppLayout
-from .ui.callbacks.data_processing import DataProcessingCallbacks
-from .ui.callbacks.visualization import VisualizationCallbacks
-from .ui.callbacks.interactions import InteractionCallbacks
+"""
+EmbeddingBuddy application factory and server functions.
+
+This module contains the main application creation logic with imports
+moved inside functions to avoid loading heavy dependencies at module level.
+"""
 
 
 def create_app():
+    """Create and configure the Dash application instance."""
     import os
+    import dash
+    import dash_bootstrap_components as dbc
+    from .ui.layout import AppLayout
+    from .ui.callbacks.data_processing import DataProcessingCallbacks
+    from .ui.callbacks.visualization import VisualizationCallbacks
+    from .ui.callbacks.interactions import InteractionCallbacks
 
-    # Get the project root directory (two levels up from this file)
-    project_root = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
-    assets_path = os.path.join(project_root, "assets")
+    # Get the assets directory relative to this module
+    module_dir = os.path.dirname(__file__)
+    assets_path = os.path.join(module_dir, "assets")
 
     app = dash.Dash(
-        __name__, external_stylesheets=[dbc.themes.BOOTSTRAP], assets_folder=assets_path
+        __name__,
+        title="EmbeddingBuddy",
+        external_stylesheets=[
+            dbc.themes.BOOTSTRAP,
+        ],
+        assets_folder=assets_path,
+        meta_tags=[
+            {
+                "name": "description",
+                "content": "Interactive embedding visualization tool for exploring high-dimensional vectors through dimensionality reduction techniques like PCA, t-SNE, and UMAP.",
+            },
+            {"name": "author", "content": "EmbeddingBuddy"},
+            {
+                "name": "keywords",
+                "content": "embeddings, visualization, dimensionality reduction, PCA, t-SNE, UMAP, machine learning, data science",
+            },
+            {"name": "viewport", "content": "width=device-width, initial-scale=1.0"},
+            {
+                "property": "og:title",
+                "content": "EmbeddingBuddy - Interactive Embedding Visualization",
+            },
+            {
+                "property": "og:description",
+                "content": "Explore and visualize embedding vectors through interactive 2D/3D plots with multiple dimensionality reduction techniques.",
+            },
+            {"property": "og:type", "content": "website"},
+        ],
     )
 
     # Allow callbacks to components that are dynamically created in tabs
@@ -45,22 +77,22 @@ def _register_client_side_callbacks(app):
             if (!nClicks || !textContent || !textContent.trim()) {
                 return window.dash_clientside.no_update;
             }
-            
+
             console.log('🔍 Checking for Transformers.js...');
             console.log('window.dash_clientside:', typeof window.dash_clientside);
             console.log('window.dash_clientside.transformers:', typeof window.dash_clientside?.transformers);
             console.log('generateEmbeddings function:', typeof window.dash_clientside?.transformers?.generateEmbeddings);
-            
-            if (typeof window.dash_clientside !== 'undefined' && 
+
+            if (typeof window.dash_clientside !== 'undefined' &&
                 typeof window.dash_clientside.transformers !== 'undefined' &&
                 typeof window.dash_clientside.transformers.generateEmbeddings === 'function') {
-                
+
                 console.log('✅ Calling Transformers.js generateEmbeddings...');
                 return window.dash_clientside.transformers.generateEmbeddings(
                     nClicks, textContent, modelName, tokenizationMethod, category, subcategory
                 );
             }
-            
+
             // More detailed error information
             let errorMsg = '❌ Transformers.js not available. ';
             if (typeof window.dash_clientside === 'undefined') {
@@ -70,21 +102,17 @@ def _register_client_side_callbacks(app):
             } else if (typeof window.dash_clientside.transformers.generateEmbeddings !== 'function') {
                 errorMsg += 'generateEmbeddings function not found.';
             }
-            
+
             console.error(errorMsg);
-            
+
             return [
                 { error: 'Transformers.js not loaded. Please refresh the page and try again.' },
-                errorMsg + ' Please refresh the page.',
-                'danger',
                 false
             ];
         }
         """,
         [
             Output("embeddings-generated-trigger", "data"),
-            Output("text-input-status-immediate", "children"),
-            Output("text-input-status-immediate", "color"),
             Output("generate-embeddings-btn", "disabled", allow_duplicate=True),
         ],
         [Input("generate-embeddings-btn", "n_clicks")],
@@ -101,6 +129,9 @@ def _register_client_side_callbacks(app):
 
 
 def run_app(app=None, debug=None, host=None, port=None):
+    """Run the Dash application with specified settings."""
+    from .config.settings import AppSettings
+
     if app is None:
         app = create_app()
 
@@ -111,6 +142,75 @@ def run_app(app=None, debug=None, host=None, port=None):
     )
 
 
-if __name__ == "__main__":
+def serve(host=None, port=None, dev=False, debug=False):
+    """Start the EmbeddingBuddy web server.
+
+    Args:
+        host: Host to bind to (default: 127.0.0.1)
+        port: Port to bind to (default: 8050)
+        dev: Development mode - enable debug logging and auto-reload (default: False)
+        debug: Enable debug logging only, no auto-reload (default: False)
+    """
+    import os
+    from .config.settings import AppSettings
+
+    # Determine actual values to use
+    actual_host = host if host is not None else AppSettings.HOST
+    actual_port = port if port is not None else AppSettings.PORT
+
+    # Determine mode
+    # --dev takes precedence and enables both debug and auto-reload
+    # --debug enables only debug logging
+    # No flags = production mode (no debug, no auto-reload)
+    use_reloader = dev
+    use_debug = dev or debug
+
+    # Only print startup messages in main process (not in Flask reloader)
+    if not os.environ.get("WERKZEUG_RUN_MAIN"):
+        from importlib.metadata import version
+
+        try:
+            pkg_version = version("embeddingbuddy")
+        except Exception:
+            pkg_version = "unknown"
+
+        mode = "development" if dev else ("debug" if debug else "production")
+        print(f"Starting EmbeddingBuddy v{pkg_version} in {mode} mode...")
+        print("Loading dependencies (this may take a few seconds)...")
+        print(f"Server will start at http://{actual_host}:{actual_port}")
+        if use_reloader:
+            print("Auto-reload enabled - server will restart on code changes")
+
     app = create_app()
-    run_app(app)
+
+    # Suppress Flask development server warning in production mode
+    if not use_debug and not use_reloader:
+        import warnings
+        import logging
+
+        # Suppress the werkzeug warning
+        warnings.filterwarnings("ignore", message=".*development server.*")
+
+        # Set werkzeug logger to ERROR level to suppress the warning
+        werkzeug_logger = logging.getLogger("werkzeug")
+        werkzeug_logger.setLevel(logging.ERROR)
+
+    # Use Flask's built-in server with appropriate settings
+    app.run(
+        debug=use_debug, host=actual_host, port=actual_port, use_reloader=use_reloader
+    )
+
+
+def main():
+    """Legacy entry point - redirects to cli module.
+
+    This is kept for backward compatibility but the main CLI
+    is now in embeddingbuddy.cli for faster startup.
+    """
+    from .cli import main as cli_main
+
+    cli_main()
+
+
+if __name__ == "__main__":
+    main()

src/embeddingbuddy/assets/custom.css

@@ -0,0 +1,17 @@
+/* CSS override for transparent hover boxes in Plotly plots */
+
+/* Make hover boxes transparent while preserving text readability */
+.hovertext {
+    fill-opacity: 0.8 !important;
+    stroke-opacity: 1 !important;
+}
+
+/* Alternative selector for different Plotly versions */
+g.hovertext > path {
+    opacity: 0.8 !important;
+}
+
+/* Ensure text remains fully visible */
+.hovertext text {
+    opacity: 1 !important;
+}

src/embeddingbuddy/assets/embeddings.js

@@ -45,28 +45,12 @@ class TransformersEmbedder {
                 console.log('✅ Using globally loaded Transformers.js pipeline');
             }
             
-            // Show loading progress to user
-            if (window.updateModelLoadingProgress) {
-                window.updateModelLoadingProgress(0, `Loading ${modelName}...`);
-            }
-            
-            this.extractor = await window.transformers.pipeline('feature-extraction', modelName, {
-                progress_callback: (data) => {
-                    if (window.updateModelLoadingProgress && data.progress !== undefined) {
-                        const progress = Math.round(data.progress);
-                        window.updateModelLoadingProgress(progress, data.status || 'Loading...');
-                    }
-                }
-            });
-            
+            this.extractor = await window.transformers.pipeline('feature-extraction', modelName);
+
             this.modelCache.set(modelName, this.extractor);
             this.currentModel = modelName;
             this.isLoading = false;
-            
-            if (window.updateModelLoadingProgress) {
-                window.updateModelLoadingProgress(100, 'Model loaded successfully');
-            }
-            
+
             return { success: true, model: modelName };
         } catch (error) {
             this.isLoading = false;
@@ -116,17 +100,8 @@ class TransformersEmbedder {
                     }
                 });
                 
-                // Update progress
-                const progress = Math.min(100, ((i + batch.length) / texts.length) * 100);
-                if (window.updateEmbeddingProgress) {
-                    window.updateEmbeddingProgress(progress, `Processing ${i + batch.length}/${texts.length} texts`);
-                }
             }
-            
-            if (window.updateEmbeddingProgress) {
-                window.updateEmbeddingProgress(100, `Generated ${embeddings.length} embeddings successfully`);
-            }
-            
+
             return embeddings;
         } catch (error) {
             console.error('Embedding generation error:', error);
@@ -139,30 +114,6 @@ class TransformersEmbedder {
 window.transformersEmbedder = new TransformersEmbedder();
 console.log('📦 TransformersEmbedder instance created');
 
-// Global progress update functions
-window.updateModelLoadingProgress = function(progress, status) {
-    const progressBar = document.getElementById('model-loading-progress');
-    const statusText = document.getElementById('model-loading-status');
-    if (progressBar) {
-        progressBar.style.width = progress + '%';
-        progressBar.setAttribute('aria-valuenow', progress);
-    }
-    if (statusText) {
-        statusText.textContent = status;
-    }
-};
-
-window.updateEmbeddingProgress = function(progress, status) {
-    const progressBar = document.getElementById('embedding-progress');
-    const statusText = document.getElementById('embedding-status');
-    if (progressBar) {
-        progressBar.style.width = progress + '%';
-        progressBar.setAttribute('aria-valuenow', progress);
-    }
-    if (statusText) {
-        statusText.textContent = status;
-    }
-};
 
 // Dash clientside callback functions
 window.dash_clientside = window.dash_clientside || {};
@@ -170,31 +121,28 @@ console.log('🔧 Setting up window.dash_clientside.transformers');
 window.dash_clientside.transformers = {
     generateEmbeddings: async function(nClicks, textContent, modelName, tokenizationMethod, category, subcategory) {
         console.log('🚀 generateEmbeddings called with:', { nClicks, modelName, tokenizationMethod, textLength: textContent?.length });
-        
+
         if (!nClicks || !textContent || textContent.trim().length === 0) {
             console.log('⚠️ Early return - missing required parameters');
             return window.dash_clientside.no_update;
         }
-        
+
         try {
             // Initialize model if needed
             const initResult = await window.transformersEmbedder.initializeModel(modelName);
             if (!initResult.success) {
                 return [
-                    { error: initResult.error },
-                    `❌ Model loading error: ${initResult.error}`,
-                    "danger",
+                    { error: `Model loading error: ${initResult.error}` },
                     false
                 ];
             }
-            
+
             // Tokenize text based on method
             let textChunks;
             const trimmedText = textContent.trim();
-            
+
             switch (tokenizationMethod) {
                 case 'sentence':
-                    // Simple sentence splitting - can be enhanced with proper NLP
                     textChunks = trimmedText
                         .split(/[.!?]+/)
                         .map(s => s.trim())
@@ -215,28 +163,24 @@ window.dash_clientside.transformers = {
                 default:
                     textChunks = [trimmedText];
             }
-            
+
             if (textChunks.length === 0) {
                 return [
                     { error: 'No valid text chunks found after tokenization' },
-                    '❌ Error: No valid text chunks found after tokenization',
-                    "danger",
                     false
                 ];
             }
-            
+
             // Generate embeddings
             const embeddings = await window.transformersEmbedder.generateEmbeddings(textChunks);
-            
+
             if (!embeddings || embeddings.length !== textChunks.length) {
                 return [
-                    { error: 'Embedding generation failed - mismatch in text chunks and embeddings' },
-                    '❌ Error: Embedding generation failed',
-                    "danger",
+                    { error: 'Embedding generation failed' },
                     false
                 ];
             }
-            
+
             // Create documents structure
             const documents = textChunks.map((text, i) => ({
                 id: `text_input_${Date.now()}_${i}`,
@@ -246,33 +190,36 @@ window.dash_clientside.transformers = {
                 subcategory: subcategory || "Generated",
                 tags: []
             }));
-            
+
+            // Return the successful embeddings data
+            const embeddingsData = {
+                documents: documents,
+                embeddings: embeddings
+            };
+
+            console.log('✅ Embeddings generated successfully:', embeddingsData);
+
             return [
-                {
-                    documents: documents,
-                    embeddings: embeddings
-                },
-                `✅ Generated embeddings for ${documents.length} text chunks using ${modelName}`,
-                "success",
+                embeddingsData,
                 false
             ];
-            
+
         } catch (error) {
             console.error('Client-side embedding error:', error);
             return [
                 { error: error.message },
-                `❌ Error: ${error.message}`,
-                "danger", 
                 false
             ];
         }
     }
 };
 
+
 console.log('✅ Transformers.js client-side setup complete');
 console.log('Available:', {
     transformersEmbedder: !!window.transformersEmbedder,
     dashClientside: !!window.dash_clientside,
     transformersModule: !!window.dash_clientside?.transformers,
-    generateFunction: typeof window.dash_clientside?.transformers?.generateEmbeddings
+    generateFunction: typeof window.dash_clientside?.transformers?.generateEmbeddings,
+    processAsync: typeof window.processEmbeddingsAsync
 });

src/embeddingbuddy/assets/fontawesome.css

@@ -0,0 +1,2 @@
+/* Load Font Awesome from local assets */
+@import url("/assets/fontawesome/css/all.min.css");

src/embeddingbuddy/assets/fontawesome/LICENSE.txt

@@ -0,0 +1,165 @@
+Fonticons, Inc. (https://fontawesome.com)
+
+--------------------------------------------------------------------------------
+
+Font Awesome Free License
+
+Font Awesome Free is free, open source, and GPL friendly. You can use it for
+commercial projects, open source projects, or really almost whatever you want.
+Full Font Awesome Free license: https://fontawesome.com/license/free.
+
+--------------------------------------------------------------------------------
+
+# Icons: CC BY 4.0 License (https://creativecommons.org/licenses/by/4.0/)
+
+The Font Awesome Free download is licensed under a Creative Commons
+Attribution 4.0 International License and applies to all icons packaged
+as SVG and JS file types.
+
+--------------------------------------------------------------------------------
+
+# Fonts: SIL OFL 1.1 License
+
+In the Font Awesome Free download, the SIL OFL license applies to all icons
+packaged as web and desktop font files.
+
+Copyright (c) 2023 Fonticons, Inc. (https://fontawesome.com)
+with Reserved Font Name: "Font Awesome".
+
+This Font Software is licensed under the SIL Open Font License, Version 1.1.
+This license is copied below, and is also available with a FAQ at:
+http://scripts.sil.org/OFL
+
+SIL OPEN FONT LICENSE
+Version 1.1 - 26 February 2007
+
+PREAMBLE
+The goals of the Open Font License (OFL) are to stimulate worldwide
+development of collaborative font projects, to support the font creation
+efforts of academic and linguistic communities, and to provide a free and
+open framework in which fonts may be shared and improved in partnership
+with others.
+
+The OFL allows the licensed fonts to be used, studied, modified and
+redistributed freely as long as they are not sold by themselves. The
+fonts, including any derivative works, can be bundled, embedded,
+redistributed and/or sold with any software provided that any reserved
+names are not used by derivative works. The fonts and derivatives,
+however, cannot be released under any other type of license. The
+requirement for fonts to remain under this license does not apply
+to any document created using the fonts or their derivatives.
+
+DEFINITIONS
+"Font Software" refers to the set of files released by the Copyright
+Holder(s) under this license and clearly marked as such. This may
+include source files, build scripts and documentation.
+
+"Reserved Font Name" refers to any names specified as such after the
+copyright statement(s).
+
+"Original Version" refers to the collection of Font Software components as
+distributed by the Copyright Holder(s).
+
+"Modified Version" refers to any derivative made by adding to, deleting,
+or substituting — in part or in whole — any of the components of the
+Original Version, by changing formats or by porting the Font Software to a
+new environment.
+
+"Author" refers to any designer, engineer, programmer, technical
+writer or other person who contributed to the Font Software.
+
+PERMISSION & CONDITIONS
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of the Font Software, to use, study, copy, merge, embed, modify,
+redistribute, and sell modified and unmodified copies of the Font
+Software, subject to the following conditions:
+
+1) Neither the Font Software nor any of its individual components,
+in Original or Modified Versions, may be sold by itself.
+
+2) Original or Modified Versions of the Font Software may be bundled,
+redistributed and/or sold with any software, provided that each copy
+contains the above copyright notice and this license. These can be
+included either as stand-alone text files, human-readable headers or
+in the appropriate machine-readable metadata fields within text or
+binary files as long as those fields can be easily viewed by the user.
+
+3) No Modified Version of the Font Software may use the Reserved Font
+Name(s) unless explicit written permission is granted by the corresponding
+Copyright Holder. This restriction only applies to the primary font name as
+presented to the users.
+
+4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font
+Software shall not be used to promote, endorse or advertise any
+Modified Version, except to acknowledge the contribution(s) of the
+Copyright Holder(s) and the Author(s) or with their explicit written
+permission.
+
+5) The Font Software, modified or unmodified, in part or in whole,
+must be distributed entirely under this license, and must not be
+distributed under any other license. The requirement for fonts to
+remain under this license does not apply to any document created
+using the Font Software.
+
+TERMINATION
+This license becomes null and void if any of the above conditions are
+not met.
+
+DISCLAIMER
+THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT
+OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
+COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
+DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM
+OTHER DEALINGS IN THE FONT SOFTWARE.
+
+--------------------------------------------------------------------------------
+
+# Code: MIT License (https://opensource.org/licenses/MIT)
+
+In the Font Awesome Free download, the MIT license applies to all non-font and
+non-icon files.
+
+Copyright 2023 Fonticons, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in the
+Software without restriction, including without limitation the rights to use, copy,
+modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
+and to permit persons to whom the Software is furnished to do so, subject to the
+following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
+PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+--------------------------------------------------------------------------------
+
+# Attribution
+
+Attribution is required by MIT, SIL OFL, and CC BY licenses. Downloaded Font
+Awesome Free files already contain embedded comments with sufficient
+attribution, so you shouldn't need to do anything additional when using these
+files normally.
+
+We've kept attribution comments terse, so we ask that you do not actively work
+to remove them from files, especially code. They're a great way for folks to
+learn about Font Awesome.
+
+--------------------------------------------------------------------------------
+
+# Brand Icons
+
+All brand icons are trademarks of their respective owners. The use of these
+trademarks does not indicate endorsement of the trademark holder by Font
+Awesome, nor vice versa. **Please do not use brand logos for any purpose except
+to represent the company, product, or service to which they refer.**

src/embeddingbuddy/assets/transformers-loader.js

@@ -104,17 +104,28 @@ window.dash_clientside = window.dash_clientside || {};
 window.dash_clientside.transformers = {
     generateEmbeddings: async function(nClicks, textContent, modelName, tokenizationMethod, category, subcategory) {
         console.log('🚀 Client-side generateEmbeddings called');
-        
+
         if (!nClicks || !textContent || textContent.trim().length === 0) {
             console.log('⚠️ Missing required parameters');
             return window.dash_clientside.no_update;
         }
-        
+
         try {
+            // Ensure Transformers.js is loaded
+            if (!window.transformersLibraryLoaded) {
+                const loaded = await initializeTransformers();
+                if (!loaded) {
+                    return [
+                        { error: 'Failed to load Transformers.js' },
+                        false
+                    ];
+                }
+            }
+
             // Tokenize text
             let textChunks;
             const trimmedText = textContent.trim();
-            
+
             switch (tokenizationMethod) {
                 case 'sentence':
                     textChunks = trimmedText.split(/[.!?]+/).map(s => s.trim()).filter(s => s.length > 0);
@@ -128,45 +139,50 @@ window.dash_clientside.transformers = {
                 default:
                     textChunks = [trimmedText];
             }
-            
+
             if (textChunks.length === 0) {
-                throw new Error('No valid text chunks after tokenization');
+                return [
+                    { error: 'No valid text chunks after tokenization' },
+                    false
+                ];
             }
-            
+
             // Generate embeddings
             const embeddings = await window.simpleEmbedder.generateEmbeddings(textChunks, modelName);
-            
+
             // Create documents
             const documents = textChunks.map((text, i) => ({
                 id: `text_input_${Date.now()}_${i}`,
                 text: text,
                 embedding: embeddings[i],
                 category: category || "Text Input",
-                subcategory: subcategory || "Generated", 
+                subcategory: subcategory || "Generated",
                 tags: []
             }));
-            
+
+            // Return the successful embeddings data
+            const embeddingsData = {
+                documents: documents,
+                embeddings: embeddings
+            };
+
+            console.log('✅ Embeddings generated successfully:', embeddingsData);
+
             return [
-                {
-                    documents: documents,
-                    embeddings: embeddings
-                },
-                `✅ Generated embeddings for ${documents.length} text chunks using ${modelName}`,
-                "success",
+                embeddingsData,
                 false
             ];
-            
+
         } catch (error) {
             console.error('❌ Error generating embeddings:', error);
             return [
                 { error: error.message },
-                `❌ Error: ${error.message}`,
-                "danger",
                 false
             ];
         }
     }
 };
 
+
 console.log('✅ Simple Transformers.js setup complete');
 console.log('Available functions:', Object.keys(window.dash_clientside.transformers));

src/embeddingbuddy/cli.py

@@ -0,0 +1,67 @@
+"""
+Lightweight CLI entry point for EmbeddingBuddy.
+
+This module provides a fast command-line interface that only imports
+heavy dependencies when actually needed by subcommands.
+"""
+
+import argparse
+import sys
+
+
+def main():
+    """Main CLI entry point with minimal imports for fast help text."""
+    parser = argparse.ArgumentParser(
+        prog="embeddingbuddy",
+        description="EmbeddingBuddy - Interactive embedding visualization tool",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+Examples:
+  embeddingbuddy serve                    # Production mode (no debug, no auto-reload)
+  embeddingbuddy serve --dev              # Development mode (debug + auto-reload)
+  embeddingbuddy serve --debug            # Debug logging only (no auto-reload)
+  embeddingbuddy serve --port 8080        # Custom port
+  embeddingbuddy serve --host 0.0.0.0     # Bind to all interfaces
+        """,
+    )
+
+    subparsers = parser.add_subparsers(
+        dest="command", help="Available commands", metavar="<command>"
+    )
+
+    # Serve subcommand
+    serve_parser = subparsers.add_parser(
+        "serve",
+        help="Start the web server",
+        description="Start the EmbeddingBuddy web server for interactive visualization",
+    )
+    serve_parser.add_argument(
+        "--host", default=None, help="Host to bind to (default: 127.0.0.1)"
+    )
+    serve_parser.add_argument(
+        "--port", type=int, default=None, help="Port to bind to (default: 8050)"
+    )
+    serve_parser.add_argument(
+        "--dev",
+        action="store_true",
+        help="Development mode: enable debug logging and auto-reload",
+    )
+    serve_parser.add_argument(
+        "--debug", action="store_true", help="Enable debug logging (no auto-reload)"
+    )
+
+    args = parser.parse_args()
+
+    if args.command == "serve":
+        # Only import heavy dependencies when actually running serve
+        from embeddingbuddy.app import serve
+
+        serve(host=args.host, port=args.port, dev=args.dev, debug=args.debug)
+    else:
+        # No command specified, show help
+        parser.print_help()
+        sys.exit(0)
+
+
+if __name__ == "__main__":
+    main()

src/embeddingbuddy/config/settings.py

@@ -69,13 +69,15 @@ class AppSettings:
     TEXT_PREVIEW_LENGTH = 100
 
     # App Configuration
-    DEBUG = os.getenv("EMBEDDINGBUDDY_DEBUG", "True").lower() == "true"
+    DEBUG = os.getenv("EMBEDDINGBUDDY_DEBUG", "False").lower() == "true"
     HOST = os.getenv("EMBEDDINGBUDDY_HOST", "127.0.0.1")
     PORT = int(os.getenv("EMBEDDINGBUDDY_PORT", "8050"))
-    
+
     # Environment Configuration
-    ENVIRONMENT = os.getenv("EMBEDDINGBUDDY_ENV", "development")  # development, production
-    
+    ENVIRONMENT = os.getenv(
+        "EMBEDDINGBUDDY_ENV", "development"
+    )  # development, production
+
     # WSGI Server Configuration (for production)
     GUNICORN_WORKERS = int(os.getenv("GUNICORN_WORKERS", "4"))
     GUNICORN_BIND = os.getenv("GUNICORN_BIND", f"{HOST}:{PORT}")
@@ -83,6 +85,9 @@ class AppSettings:
     GUNICORN_KEEPALIVE = int(os.getenv("GUNICORN_KEEPALIVE", "5"))
 
     # OpenSearch Configuration
+    OPENSEARCH_ENABLED = (
+        os.getenv("EMBEDDINGBUDDY_OPENSEARCH_ENABLED", "True").lower() == "true"
+    )
     OPENSEARCH_DEFAULT_SIZE = 100
     OPENSEARCH_SAMPLE_SIZE = 5
     OPENSEARCH_CONNECTION_TIMEOUT = 30

src/embeddingbuddy/ui/callbacks/data_processing.py

@@ -82,19 +82,23 @@ class DataProcessingCallbacks:
         )
         def render_tab_content(active_tab):
             from ...ui.components.datasource import DataSourceComponent
+            from ...config.settings import AppSettings
 
             datasource = DataSourceComponent()
 
-            if active_tab == "opensearch-tab":
+            if active_tab == "opensearch-tab" and AppSettings.OPENSEARCH_ENABLED:
                 return [datasource.create_opensearch_tab()]
             elif active_tab == "text-input-tab":
                 return [datasource.create_text_input_tab()]
             else:
                 return [datasource.create_file_upload_tab()]
 
-        # Register callbacks for both data and prompts sections
-        self._register_opensearch_callbacks("data", self.opensearch_client_data)
-        self._register_opensearch_callbacks("prompts", self.opensearch_client_prompts)
+        # Register callbacks for both data and prompts sections (only if OpenSearch is enabled)
+        if AppSettings.OPENSEARCH_ENABLED:
+            self._register_opensearch_callbacks("data", self.opensearch_client_data)
+            self._register_opensearch_callbacks(
+                "prompts", self.opensearch_client_prompts
+            )
 
         # Register collapsible section callbacks
         self._register_collapse_callbacks()
@@ -621,6 +625,12 @@ class DataProcessingCallbacks:
             if not embeddings_data:
                 return no_update, no_update, no_update, no_update, no_update
 
+            # Check if this is a request trigger (contains textContent) vs actual embeddings data
+            if isinstance(embeddings_data, dict) and "textContent" in embeddings_data:
+                # This is a processing request trigger, not the actual results
+                # The JavaScript will handle the async processing and update the UI directly
+                return no_update, no_update, no_update, no_update, no_update
+
             processed_data = self.processor.process_client_embeddings(embeddings_data)
 
             if processed_data.error:
@@ -650,14 +660,12 @@ class DataProcessingCallbacks:
         import os
 
         try:
-            # Get the project root directory (four levels up from this file)
+            # Get the embeddingbuddy package directory (three levels up from this file)
             current_file = os.path.abspath(__file__)
-            project_root = os.path.dirname(
-                os.path.dirname(
-                    os.path.dirname(os.path.dirname(os.path.dirname(current_file)))
-                )
+            package_dir = os.path.dirname(
+                os.path.dirname(os.path.dirname(current_file))
             )
-            sample_file_path = os.path.join(project_root, "assets", "sample-txt.md")
+            sample_file_path = os.path.join(package_dir, "assets", "sample-txt.md")
 
             if os.path.exists(sample_file_path):
                 with open(sample_file_path, "r", encoding="utf-8") as file:

src/embeddingbuddy/ui/callbacks/interactions.py

@@ -1,6 +1,5 @@
 import dash
-from dash import callback, Input, Output, State, html
-import dash_bootstrap_components as dbc
+from dash import callback, Input, Output
 
 
 class InteractionCallbacks:
@@ -9,74 +8,25 @@ class InteractionCallbacks:
 
     def _register_callbacks(self):
         @callback(
-            Output("point-details", "children"),
-            Input("embedding-plot", "clickData"),
-            [State("processed-data", "data"), State("processed-prompts", "data")],
+            Output("about-modal", "is_open"),
+            [Input("about-button", "n_clicks"), Input("about-modal-close", "n_clicks")],
+            prevent_initial_call=True,
         )
-        def display_click_data(clickData, data, prompts_data):
-            if not clickData or not data:
-                return "Click on a point to see details"
-
-            point_data = clickData["points"][0]
-            trace_name = point_data.get("fullData", {}).get("name", "Documents")
-
-            if "pointIndex" in point_data:
-                point_index = point_data["pointIndex"]
-            elif "pointNumber" in point_data:
-                point_index = point_data["pointNumber"]
-            else:
-                return "Could not identify clicked point"
-
-            if (
-                trace_name.startswith("Prompts")
-                and prompts_data
-                and "prompts" in prompts_data
-            ):
-                item = prompts_data["prompts"][point_index]
-                item_type = "Prompt"
-            else:
-                item = data["documents"][point_index]
-                item_type = "Document"
-
-            return self._create_detail_card(item, item_type)
+        def toggle_about_modal(about_clicks, close_clicks):
+            if about_clicks or close_clicks:
+                return True if about_clicks else False
+            return False
 
         @callback(
             [
                 Output("processed-data", "data", allow_duplicate=True),
                 Output("processed-prompts", "data", allow_duplicate=True),
-                Output("point-details", "children", allow_duplicate=True),
             ],
             Input("reset-button", "n_clicks"),
             prevent_initial_call=True,
         )
         def reset_data(n_clicks):
             if n_clicks is None or n_clicks == 0:
-                return dash.no_update, dash.no_update, dash.no_update
+                return dash.no_update, dash.no_update
 
-            return None, None, "Click on a point to see details"
-
-    @staticmethod
-    def _create_detail_card(item, item_type):
-        return dbc.Card(
-            [
-                dbc.CardBody(
-                    [
-                        html.H5(f"{item_type}: {item['id']}", className="card-title"),
-                        html.P(f"Text: {item['text']}", className="card-text"),
-                        html.P(
-                            f"Category: {item.get('category', 'Unknown')}",
-                            className="card-text",
-                        ),
-                        html.P(
-                            f"Subcategory: {item.get('subcategory', 'Unknown')}",
-                            className="card-text",
-                        ),
-                        html.P(
-                            f"Tags: {', '.join(item.get('tags', [])) if item.get('tags') else 'None'}",
-                            className="card-text",
-                        ),
-                        html.P(f"Type: {item_type}", className="card-text text-muted"),
-                    ]
-                )
-            ]
-        )
+            return None, None

src/embeddingbuddy/ui/components/about.py

@@ -0,0 +1,90 @@
+from dash import html, dcc
+import dash_bootstrap_components as dbc
+
+
+class AboutComponent:
+    def _get_about_content(self):
+        return """
+# 🔍 Interactive Embedding Vector Visualization
+
+EmbeddingBuddy is a web application for interactive exploration and
+visualization of embedding vectors through dimensionality reduction techniques
+(PCA, t-SNE, UMAP).
+
+You have two ways to get started:
+
+1. Generate embeddings directly in the browser if it supports WebGPU.
+2. Upload your NDJSON file containing embedding vectors and metadata.
+
+## Generating Embeddings in Browser
+
+1. Expand the "Generate Embeddings" section.
+2. Input your text data (one entry per line).
+    1. Optionally you can use the built in sample data by clicking "Load Sample Data" button.
+3. Click "Generate Embeddings" to create vectors using a pre-trained model.
+
+## NDJSON File Format
+
+```json
+{"id": "doc_001", "embedding": [0.1, -0.3, 0.7, ...], "text": "Sample text content", "category": "news", "subcategory": "politics", "tags": ["election", "politics"]}
+{"id": "doc_002", "embedding": [0.2, -0.1, 0.9, ...], "text": "Another example", "category": "review", "subcategory": "product", "tags": ["tech", "gadget"]}
+```
+
+
+## ✨ Features
+
+- Drag-and-drop NDJSON file upload
+- Multiple dimensionality reduction algorithms
+- 2D/3D interactive plots with Plotly
+- Color coding by categories, subcategories, or tags
+- In-browser embedding generation
+- OpenSearch integration for data loading
+
+## 🔧 Supported Algorithms
+
+- **PCA** (Principal Component Analysis)
+- **t-SNE** (t-Distributed Stochastic Neighbor Embedding)
+- **UMAP** (Uniform Manifold Approximation and Projection)
+
+---
+
+📂 [View on GitHub](https://github.com/godber/EmbeddingBuddy)
+
+*Built with: Python, Dash, Plotly, scikit-learn, OpenTSNE, UMAP*
+        """.strip()
+
+    def create_about_modal(self):
+        return dbc.Modal(
+            [
+                dbc.ModalHeader(
+                    dbc.ModalTitle("Welcome to EmbeddingBuddy"),
+                    close_button=True,
+                ),
+                dbc.ModalBody(
+                    [dcc.Markdown(self._get_about_content(), className="mb-0")]
+                ),
+                dbc.ModalFooter(
+                    [
+                        dbc.Button(
+                            "Close",
+                            id="about-modal-close",
+                            color="secondary",
+                            n_clicks=0,
+                        )
+                    ]
+                ),
+            ],
+            id="about-modal",
+            is_open=True,
+            size="lg",
+        )
+
+    def create_about_button(self):
+        return dbc.Button(
+            [html.I(className="fas fa-info-circle me-2"), "About"],
+            id="about-button",
+            color="outline-info",
+            size="sm",
+            n_clicks=0,
+            className="ms-2",
+        )

src/embeddingbuddy/ui/components/datasource.py

@@ -1,26 +1,27 @@
 from dash import dcc, html
 import dash_bootstrap_components as dbc
 from .upload import UploadComponent
-from .textinput import TextInputComponent
+from embeddingbuddy.config.settings import AppSettings
 
 
 class DataSourceComponent:
     def __init__(self):
         self.upload_component = UploadComponent()
-        self.text_input_component = TextInputComponent()
 
     def create_tabbed_interface(self):
         """Create tabbed interface for different data sources."""
+        tabs = [dbc.Tab(label="File Upload", tab_id="file-tab")]
+
+        # Only add OpenSearch tab if enabled
+        if AppSettings.OPENSEARCH_ENABLED:
+            tabs.append(dbc.Tab(label="OpenSearch", tab_id="opensearch-tab"))
+
         return dbc.Card(
             [
                 dbc.CardHeader(
                     [
                         dbc.Tabs(
-                            [
-                                dbc.Tab(label="File Upload", tab_id="file-tab"),
-                                dbc.Tab(label="OpenSearch", tab_id="opensearch-tab"),
-                                dbc.Tab(label="Text Input", tab_id="text-input-tab"),
-                            ],
+                            tabs,
                             id="data-source-tabs",
                             active_tab="file-tab",
                         )
@@ -211,10 +212,6 @@ class DataSourceComponent:
             ]
         )
 
-    def create_text_input_tab(self):
-        """Create text input tab content for browser-based embedding generation."""
-        return html.Div([self.text_input_component.create_text_input_interface()])
-
     def _create_opensearch_section(self, section_type):
         """Create a complete OpenSearch section for either 'data' or 'prompts'."""
         section_id = section_type  # 'data' or 'prompts'

src/embeddingbuddy/ui/components/sidebar.py

@@ -2,31 +2,27 @@ from dash import dcc, html
 import dash_bootstrap_components as dbc
 from .upload import UploadComponent
 from .datasource import DataSourceComponent
+from .textinput import TextInputComponent
+from embeddingbuddy.config.settings import AppSettings
 
 
 class SidebarComponent:
     def __init__(self):
         self.upload_component = UploadComponent()
         self.datasource_component = DataSourceComponent()
+        self.textinput_component = TextInputComponent()
 
     def create_layout(self):
         return dbc.Col(
             [
-                html.H5("Data Sources", className="mb-3"),
-                self.datasource_component.create_error_alert(),
-                self.datasource_component.create_success_alert(),
-                self.datasource_component.create_tabbed_interface(),
-                html.H5("Visualization Controls", className="mb-3 mt-4"),
-            ]
-            + self._create_method_dropdown()
-            + self._create_color_dropdown()
-            + self._create_dimension_toggle()
-            + self._create_prompts_toggle()
-            + [
-                html.H5("Point Details", className="mb-3"),
-                html.Div(
-                    id="point-details", children="Click on a point to see details"
-                ),
+                dbc.Accordion(
+                    [
+                        self._create_data_sources_item(),
+                        self._create_generate_embeddings_item(),
+                        self._create_visualization_controls_item(),
+                    ],
+                    always_open=True,
+                )
             ],
             width=3,
             style={"padding-right": "20px"},
@@ -86,3 +82,67 @@ class SidebarComponent:
                 style={"margin-bottom": "20px"},
             ),
         ]
+
+    def _create_generate_embeddings_item(self):
+        return dbc.AccordionItem(
+            [
+                self.textinput_component.create_text_input_interface(),
+            ],
+            title=html.Span(
+                [
+                    "Generate Embeddings ",
+                    html.I(
+                        className="fas fa-info-circle text-muted",
+                        style={"cursor": "pointer"},
+                        id="generate-embeddings-info-icon",
+                        title="Create new embeddings from text input using various in-browser models",
+                    ),
+                ]
+            ),
+            item_id="generate-embeddings-accordion",
+        )
+
+    def _create_data_sources_item(self):
+        tooltip_text = "Load existing embeddings: upload files"
+        if AppSettings.OPENSEARCH_ENABLED:
+            tooltip_text += " or read from OpenSearch"
+
+        return dbc.AccordionItem(
+            [
+                self.datasource_component.create_error_alert(),
+                self.datasource_component.create_success_alert(),
+                self.datasource_component.create_tabbed_interface(),
+            ],
+            title=html.Span(
+                [
+                    "Load Embeddings ",
+                    html.I(
+                        className="fas fa-info-circle text-muted",
+                        style={"cursor": "pointer"},
+                        id="load-embeddings-info-icon",
+                        title=tooltip_text,
+                    ),
+                ]
+            ),
+            item_id="data-sources-accordion",
+        )
+
+    def _create_visualization_controls_item(self):
+        return dbc.AccordionItem(
+            self._create_method_dropdown()
+            + self._create_color_dropdown()
+            + self._create_dimension_toggle()
+            + self._create_prompts_toggle(),
+            title=html.Span(
+                [
+                    "Visualization Controls ",
+                    html.I(
+                        className="fas fa-info-circle text-muted",
+                        style={"cursor": "pointer"},
+                        id="visualization-controls-info-icon",
+                        title="Configure plot settings: select dimensionality reduction method, colors, and display options",
+                    ),
+                ]
+            ),
+            item_id="visualization-controls-accordion",
+        )

src/embeddingbuddy/ui/components/textinput.py

@@ -16,23 +16,20 @@ class TextInputComponent:
         """Create the complete text input interface with model selection and processing options."""
         return html.Div(
             [
-                # Model selection section
-                self._create_model_selection(),
-                html.Hr(),
                 # Text input section
                 self._create_text_input_area(),
                 # Text action buttons
                 self._create_text_action_buttons(),
                 html.Hr(),
+                # Model selection section
+                self._create_model_selection(),
+                html.Hr(),
                 # Processing options
                 self._create_processing_options(),
                 html.Hr(),
                 # Generation controls
                 self._create_generation_controls(),
                 html.Hr(),
-                # Progress indicators
-                self._create_progress_indicators(),
-                html.Hr(),
                 # Status and results
                 self._create_status_section(),
                 # Hidden components for data flow
@@ -297,65 +294,10 @@ class TextInputComponent:
             ]
         )
 
-    def _create_progress_indicators(self):
-        """Create progress bars for model loading and embedding generation."""
-        return html.Div(
-            [
-                # Model loading progress
-                html.Div(
-                    [
-                        html.H6("Model Loading Progress", className="mb-2"),
-                        dbc.Progress(
-                            id="model-loading-progress",
-                            value=0,
-                            striped=True,
-                            animated=True,
-                            className="mb-2",
-                        ),
-                        html.Small(
-                            id="model-loading-status",
-                            children="No model loading in progress",
-                            className="text-muted",
-                        ),
-                    ],
-                    id="model-loading-section",
-                    style={"display": "none"},
-                ),
-                html.Br(),
-                # Embedding generation progress
-                html.Div(
-                    [
-                        html.H6("Embedding Generation Progress", className="mb-2"),
-                        dbc.Progress(
-                            id="embedding-progress",
-                            value=0,
-                            striped=True,
-                            animated=True,
-                            className="mb-2",
-                        ),
-                        html.Small(
-                            id="embedding-status",
-                            children="No embedding generation in progress",
-                            className="text-muted",
-                        ),
-                    ],
-                    id="embedding-progress-section",
-                    style={"display": "none"},
-                ),
-            ]
-        )
-
     def _create_status_section(self):
         """Create status alerts and results preview."""
         return html.Div(
             [
-                # Immediate status (from client-side)
-                dbc.Alert(
-                    id="text-input-status-immediate",
-                    children="Ready to generate embeddings",
-                    color="light",
-                    className="mb-3",
-                ),
                 # Server-side status
                 dbc.Alert(
                     id="text-input-status",

src/embeddingbuddy/ui/components/upload.py

@@ -5,39 +5,75 @@ import dash_bootstrap_components as dbc
 class UploadComponent:
     @staticmethod
     def create_data_upload():
-        return dcc.Upload(
-            id="upload-data",
-            children=html.Div(["Drag and Drop or ", html.A("Select Files")]),
-            style={
-                "width": "100%",
-                "height": "60px",
-                "lineHeight": "60px",
-                "borderWidth": "1px",
-                "borderStyle": "dashed",
-                "borderRadius": "5px",
-                "textAlign": "center",
-                "margin-bottom": "20px",
-            },
-            multiple=False,
+        return html.Div(
+            [
+                dcc.Upload(
+                    id="upload-data",
+                    children=html.Div(
+                        [
+                            "Upload Data ",
+                            html.I(
+                                className="fas fa-info-circle",
+                                style={"color": "#6c757d", "fontSize": "14px"},
+                                id="data-upload-info",
+                            ),
+                        ]
+                    ),
+                    style={
+                        "width": "100%",
+                        "height": "60px",
+                        "lineHeight": "60px",
+                        "borderWidth": "1px",
+                        "borderStyle": "dashed",
+                        "borderRadius": "5px",
+                        "textAlign": "center",
+                        "margin-bottom": "20px",
+                    },
+                    multiple=False,
+                ),
+                dbc.Tooltip(
+                    "Click here or drag and drop NDJSON files containing document embeddings",
+                    target="data-upload-info",
+                    placement="top",
+                ),
+            ]
         )
 
     @staticmethod
     def create_prompts_upload():
-        return dcc.Upload(
-            id="upload-prompts",
-            children=html.Div(["Drag and Drop Prompts or ", html.A("Select Files")]),
-            style={
-                "width": "100%",
-                "height": "60px",
-                "lineHeight": "60px",
-                "borderWidth": "1px",
-                "borderStyle": "dashed",
-                "borderRadius": "5px",
-                "textAlign": "center",
-                "margin-bottom": "20px",
-                "borderColor": "#28a745",
-            },
-            multiple=False,
+        return html.Div(
+            [
+                dcc.Upload(
+                    id="upload-prompts",
+                    children=html.Div(
+                        [
+                            "Upload Prompts ",
+                            html.I(
+                                className="fas fa-info-circle",
+                                style={"color": "#6c757d", "fontSize": "14px"},
+                                id="prompts-upload-info",
+                            ),
+                        ]
+                    ),
+                    style={
+                        "width": "100%",
+                        "height": "60px",
+                        "lineHeight": "60px",
+                        "borderWidth": "1px",
+                        "borderStyle": "dashed",
+                        "borderRadius": "5px",
+                        "textAlign": "center",
+                        "margin-bottom": "20px",
+                        "borderColor": "#28a745",
+                    },
+                    multiple=False,
+                ),
+                dbc.Tooltip(
+                    "Click here or drag and drop NDJSON files containing prompt embeddings",
+                    target="prompts-upload-info",
+                    placement="top",
+                ),
+            ]
         )
 
     @staticmethod

src/embeddingbuddy/ui/layout.py

@@ -1,16 +1,19 @@
 from dash import dcc, html
 import dash_bootstrap_components as dbc
 from .components.sidebar import SidebarComponent
+from .components.about import AboutComponent
 
 
 class AppLayout:
     def __init__(self):
         self.sidebar = SidebarComponent()
+        self.about = AboutComponent()
 
     def create_layout(self):
         return dbc.Container(
             [self._create_header(), self._create_main_content()]
-            + self._create_stores(),
+            + self._create_stores()
+            + [self.about.create_about_modal()],
             fluid=True,
         )
 
@@ -19,7 +22,19 @@ class AppLayout:
             [
                 dbc.Col(
                     [
-                        html.H1("EmbeddingBuddy", className="text-center mb-4"),
+                        html.Div(
+                            [
+                                html.H1(
+                                    "EmbeddingBuddy",
+                                    className="text-center mb-4 d-inline",
+                                ),
+                                html.Div(
+                                    [self.about.create_about_button()],
+                                    className="float-end",
+                                ),
+                            ],
+                            className="d-flex justify-content-between align-items-center",
+                        ),
                         # Load Transformers.js from CDN
                         html.Script(
                             """

src/embeddingbuddy/visualization/plots.py

@@ -38,9 +38,9 @@ class PlotFactory:
         if dimensions == "3d":
             fig = px.scatter_3d(
                 df,
-                x="dim_1",
-                y="dim_2",
-                z="dim_3",
+                x="x",
+                y="y",
+                z="z",
                 color=color_values,
                 hover_data=hover_fields,
                 title=f"3D Embedding Visualization - {method} (colored by {color_by})",
@@ -49,8 +49,8 @@ class PlotFactory:
         else:
             fig = px.scatter(
                 df,
-                x="dim_1",
-                y="dim_2",
+                x="x",
+                y="y",
                 color=color_values,
                 hover_data=hover_fields,
                 title=f"2D Embedding Visualization - {method} (colored by {color_by})",
@@ -77,17 +77,17 @@ class PlotFactory:
         if dimensions == "3d":
             doc_fig = px.scatter_3d(
                 doc_df,
-                x="dim_1",
-                y="dim_2",
-                z="dim_3",
+                x="x",
+                y="y",
+                z="z",
                 color=doc_color_values,
                 hover_data=hover_fields,
             )
         else:
             doc_fig = px.scatter(
                 doc_df,
-                x="dim_1",
-                y="dim_2",
+                x="x",
+                y="y",
                 color=doc_color_values,
                 hover_data=hover_fields,
             )
@@ -114,17 +114,17 @@ class PlotFactory:
             if dimensions == "3d":
                 prompt_fig = px.scatter_3d(
                     prompt_df,
-                    x="dim_1",
-                    y="dim_2",
-                    z="dim_3",
+                    x="x",
+                    y="y",
+                    z="z",
                     color=prompt_color_values,
                     hover_data=hover_fields,
                 )
             else:
                 prompt_fig = px.scatter(
                     prompt_df,
-                    x="dim_1",
-                    y="dim_2",
+                    x="x",
+                    y="y",
                     color=prompt_color_values,
                     hover_data=hover_fields,
                 )
@@ -168,11 +168,11 @@ class PlotFactory:
                 "category": doc.category,
                 "subcategory": doc.subcategory,
                 "tags_str": ", ".join(doc.tags) if doc.tags else "None",
-                "dim_1": coordinates[i, 0],
-                "dim_2": coordinates[i, 1],
+                "x": coordinates[i, 0],
+                "y": coordinates[i, 1],
             }
             if dimensions == "3d":
-                row["dim_3"] = coordinates[i, 2]
+                row["z"] = coordinates[i, 2]
             df_data.append(row)
 
         return pd.DataFrame(df_data)

src/embeddingbuddy/wsgi.py

@@ -0,0 +1,12 @@
+"""
+WSGI entry point for production deployment.
+Use this with a production WSGI server like Gunicorn.
+"""
+
+from embeddingbuddy.app import create_app
+
+# Create the application instance
+application = create_app()
+
+# For compatibility with different WSGI servers
+app = application

uv.lock

@@ -412,7 +412,7 @@ wheels = [
 
 [[package]]
 name = "embeddingbuddy"
-version = "0.3.0"
+version = "0.8.1"
 source = { editable = "." }
 dependencies = [
     { name = "dash" },

wsgi.py

@@ -1,20 +0,0 @@
-"""
-WSGI entry point for production deployment.
-Use this with a production WSGI server like Gunicorn.
-"""
-from src.embeddingbuddy.app import create_app
-
-# Create the application instance
-application = create_app()
-
-# For compatibility with different WSGI servers
-app = application
-
-if __name__ == "__main__":
-    # This won't be used in production, but useful for testing
-    from src.embeddingbuddy.config.settings import AppSettings
-    application.run(
-        host=AppSettings.HOST,
-        port=AppSettings.PORT,
-        debug=False
-    )