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EmbeddingBuddy/src/embeddingbuddy/app.py
Austin Godber 68f5cf8617
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embed fontawesome
2025-10-02 07:16:58 -07:00

210 lines
7.7 KiB
Python

"""
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")
app = dash.Dash(
__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
app.config.suppress_callback_exceptions = True
layout_manager = AppLayout()
app.layout = layout_manager.create_layout()
DataProcessingCallbacks()
VisualizationCallbacks()
InteractionCallbacks()
# Register client-side callback for embedding generation
_register_client_side_callbacks(app)
return app
def _register_client_side_callbacks(app):
"""Register client-side callbacks for browser-based processing."""
from dash import Input, Output, State
# Client-side callback for embedding generation
app.clientside_callback(
"""
function(nClicks, textContent, modelName, tokenizationMethod, batchSize, category, subcategory) {
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' &&
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') {
errorMsg += 'dash_clientside not found.';
} else if (typeof window.dash_clientside.transformers === 'undefined') {
errorMsg += 'transformers module not found.';
} 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.' },
false
];
}
""",
[
Output("embeddings-generated-trigger", "data"),
Output("generate-embeddings-btn", "disabled", allow_duplicate=True),
],
[Input("generate-embeddings-btn", "n_clicks")],
[
State("text-input-area", "value"),
State("model-selection", "value"),
State("tokenization-method", "value"),
State("batch-size", "value"),
State("text-category", "value"),
State("text-subcategory", "value"),
],
prevent_initial_call=True,
)
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()
app.run(
debug=debug if debug is not None else AppSettings.DEBUG,
host=host if host is not None else AppSettings.HOST,
port=port if port is not None else AppSettings.PORT,
)
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"):
mode = "development" if dev else ("debug" if debug else "production")
print(f"Starting EmbeddingBuddy 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()
# 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()