Add configurable OpenSearch feature and UI improvements

- Add MIT license with Austin Godber copyright
  - Implement optional OpenSearch feature toggle via EMBEDDINGBUDDY_OPENSEARCH_ENABLED
  - Disable OpenSearch by default in production for security
  - Add development environment flag to test OpenSearch disable state
  - Update about modal to open by default with improved content
  - Reorganize text input component: move model selection below text input
  - Conditionally show/hide OpenSearch tab and callbacks based on configuration
  - Update tooltips to reflect OpenSearch availability status

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.

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "embeddingbuddy"
-version = "0.5.1"
+version = "0.6.0"
 description = "A Python Dash application for interactive exploration and visualization of embedding vectors through dimensionality reduction techniques."
 readme = "README.md"
 requires-python = ">=3.11"

run_dev.py

@@ -11,10 +11,16 @@ def main():
     # Force development settings
     os.environ["EMBEDDINGBUDDY_ENV"] = "development"
     os.environ["EMBEDDINGBUDDY_DEBUG"] = "true"
+
+    # Check for OpenSearch disable flag (optional for testing)
+    # Set EMBEDDINGBUDDY_OPENSEARCH_ENABLED=false to test without OpenSearch
+    opensearch_status = os.getenv("EMBEDDINGBUDDY_OPENSEARCH_ENABLED", "true")
+    opensearch_enabled = opensearch_status.lower() == "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(f"🔍 OpenSearch: {'Enabled' if opensearch_enabled else 'Disabled'}")
     print("⏹️  Press Ctrl+C to stop")
     
     app = create_app()

run_prod.py

@@ -13,6 +13,9 @@ def main():
     # Force production settings
     os.environ["EMBEDDINGBUDDY_ENV"] = "production"
     os.environ["EMBEDDINGBUDDY_DEBUG"] = "false"
+    # Disable OpenSearch by default in production (can be overridden by setting env var)
+    if "EMBEDDINGBUDDY_OPENSEARCH_ENABLED" not in os.environ:
+        os.environ["EMBEDDINGBUDDY_OPENSEARCH_ENABLED"] = "false"
     
     print("🚀 Starting EmbeddingBuddy in production mode...")
     print(f"⚙️  Workers: {AppSettings.GUNICORN_WORKERS}")

src/embeddingbuddy/config/settings.py

@@ -85,6 +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
+        # Register callbacks for both data and prompts sections (only if OpenSearch is enabled)
-        self._register_opensearch_callbacks("data", self.opensearch_client_data)
+        if AppSettings.OPENSEARCH_ENABLED:
-        self._register_opensearch_callbacks("prompts", self.opensearch_client_prompts)
+            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()

src/embeddingbuddy/ui/components/about.py

@@ -5,9 +5,31 @@ import dash_bootstrap_components as dbc
 class AboutComponent:
     def _get_about_content(self):
         return """
-# 🔍 Interactive Embedding Visualization
+# 🔍 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"]}
+```
 
-EmbeddingBuddy is a modular Python Dash web application for interactive exploration and visualization of embedding vectors through dimensionality reduction techniques (PCA, t-SNE, UMAP).
 
 ## ✨ Features
 
@@ -35,7 +57,7 @@ EmbeddingBuddy is a modular Python Dash web application for interactive explorat
         return dbc.Modal(
             [
                 dbc.ModalHeader(
-                    dbc.ModalTitle("About EmbeddingBuddy"),
+                    dbc.ModalTitle("Welcome to EmbeddingBuddy"),
                     close_button=True,
                 ),
                 dbc.ModalBody(
@@ -53,7 +75,7 @@ EmbeddingBuddy is a modular Python Dash web application for interactive explorat
                 ),
             ],
             id="about-modal",
-            is_open=False,
+            is_open=True,
             size="lg",
         )
 

src/embeddingbuddy/ui/components/datasource.py

@@ -1,6 +1,7 @@
 from dash import dcc, html
 import dash_bootstrap_components as dbc
 from .upload import UploadComponent
+from embeddingbuddy.config.settings import AppSettings
 
 
 class DataSourceComponent:
@@ -9,15 +10,18 @@ class DataSourceComponent:
 
     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(
-                            [
+                            tabs,
-                                dbc.Tab(label="File Upload", tab_id="file-tab"),
-                                dbc.Tab(label="OpenSearch", tab_id="opensearch-tab"),
-                            ],
                             id="data-source-tabs",
                             active_tab="file-tab",
                         )

src/embeddingbuddy/ui/components/sidebar.py

@@ -3,6 +3,7 @@ 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:
@@ -102,6 +103,10 @@ class SidebarComponent:
         )
 
     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(),
@@ -115,7 +120,7 @@ class SidebarComponent:
                         className="fas fa-info-circle text-muted",
                         style={"cursor": "pointer"},
                         id="load-embeddings-info-icon",
-                        title="Load existing embeddings: upload files or read from OpenSearch",
+                        title=tooltip_text,
                     ),
                 ]
             ),

src/embeddingbuddy/ui/components/textinput.py

@@ -16,14 +16,14 @@ 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(),