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* API Adapter for Flask Backend (android.py)
*
* This file provides a pywebview.api compatible interface that works with
* the Flask REST API instead of the pywebview Python bridge.
*
* Include this BEFORE app.js when running on Android/Flask:
* <script src="api-adapter.js"></script>
* <script src="app.js"></script>
*/
(function() {
'use strict';
// API base URL - will be automatically set to current origin
const API_BASE = window.location.origin;
/**
* Make API call to Flask backend
*/
async function apiCall(endpoint, data = null) {
const url = `${API_BASE}/api/${endpoint}`;
const options = {
method: data ? 'POST' : 'GET',
headers: {
'Content-Type': 'application/json',
}
};
if (data) {
options.body = JSON.stringify(data);
}
try {
const response = await fetch(url, options);
if (!response.ok) {
throw new Error(`HTTP error! status: ${response.status}`);
}
const result = await response.json();
return result;
} catch (error) {
console.error(`API call failed: ${endpoint}`, error);
throw error;
}
}
/**
* Create pywebview.api compatible interface
*/
window.pywebview = {
api: {
// ==================== Synthetic Data Generation ====================
generate_simplex_points: async function(n, d, k, seed) {
return await apiCall('generate_simplex_points', { n, d, k, seed });
},
save_synthetic_dataset: async function(points) {
return await apiCall('save_synthetic_dataset', { points });
},
// ==================== MNIST Dataset ====================
load_mnist: async function(max_samples, subset) {
return await apiCall('load_mnist', { max_samples, subset });
},
// ==================== Upload Handling ====================
upload_csv: async function(name, content, delimiter) {
return await apiCall('upload_csv', { name, content, delimiter });
},
upload_images: async function(files) {
return await apiCall('upload_images', { files });
},
list_datasets: async function() {
return await apiCall('list_datasets');
},
prepare_csv_dataset: async function(dataset_id, selected_columns, handle_missing) {
return await apiCall('prepare_csv_dataset', {
dataset_id,
selected_columns,
handle_missing
});
},
// ==================== Embeddings ====================
compute_embeddings: async function(dataset_id, method) {
return await apiCall('compute_embeddings', { dataset_id, method });
},
// ==================== t-SNE ====================
run_tsne: async function(dataset_id, perplexity, learning_rate, n_iter,
early_exaggeration, momentum, init_method, init_data, seed) {
return await apiCall('run_tsne', {
dataset_id,
perplexity,
learning_rate,
n_iter,
early_exaggeration,
momentum,
init_method,
init_data,
seed
});
},
stop_tsne: async function() {
// Note: stop functionality needs to be implemented in Flask backend
return { success: true };
},
// ==================== Clustering ====================
run_clustering: async function(dataset_id, method, k, eps, min_samples) {
return await apiCall('run_clustering', {
dataset_id,
method,
k,
eps,
min_samples
});
},
// ==================== Export ====================
export_results: async function(dataset_id) {
return await apiCall('export_results', { dataset_id });
},
get_image_at_index: async function(dataset_id, index) {
return await apiCall('get_image_at_index', { dataset_id, index });
}
},
// ==================== API Status ====================
/**
* Check if we're running in Flask/Android mode
*/
isFlaskMode: function() {
return true;
},
/**
* Check MCP connection status
*/
checkMCPStatus: async function() {
try {
const status = await apiCall('mcp_status');
return status;
} catch (error) {
return { connected: false, available: false };
}
}
};
// ==================== Progress Updates ====================
/**
* Progress updates for t-SNE
* In Flask mode, we use polling instead of callbacks
*/
let progressInterval = null;
window.startProgressPolling = function() {
if (progressInterval) {
clearInterval(progressInterval);
}
// Poll for progress updates every 500ms
progressInterval = setInterval(async () => {
try {
const progress = await apiCall('tsne_progress');
if (progress && progress.current !== undefined) {
window.updateProgress(progress.current, progress.total, progress.message);
// Stop polling when complete
if (progress.current >= progress.total) {
clearInterval(progressInterval);
progressInterval = null;
}
}
} catch (error) {
// Silently fail if progress endpoint not available
}
}, 500);
};
window.stopProgressPolling = function() {
if (progressInterval) {
clearInterval(progressInterval);
progressInterval = null;
}
};
// ==================== Connection Status Indicator ====================
/**
* Show connection status in UI
*/
async function showConnectionStatus() {
try {
const health = await apiCall('health');
const statusDiv = document.createElement('div');
statusDiv.id = 'connection-status';
statusDiv.style.cssText = `
position: fixed;
top: 10px;
right: 10px;
padding: 8px 12px;
background: ${health.mcp_connected ? '#10b981' : '#f59e0b'};
color: white;
border-radius: 6px;
font-size: 0.85em;
font-weight: 600;
z-index: 9999;
box-shadow: 0 2px 8px rgba(0,0,0,0.2);
`;
statusDiv.innerHTML = health.mcp_connected
? '🟢 MCP Connected'
: '🟡 Local Mode';
document.body.appendChild(statusDiv);
// Add tooltip
statusDiv.title = health.mcp_connected
? 'Connected to MCP server for heavy computations'
: 'Using local fallback (computations may be slower)';
} catch (error) {
console.error('Failed to check connection status:', error);
}
}
// ==================== Initialization ====================
/**
* Initialize Flask API adapter
*/
function initAdapter() {
console.log('Flask API Adapter initialized');
console.log(`API Base URL: ${API_BASE}`);
// Show connection status
showConnectionStatus();
// Dispatch ready event
window.dispatchEvent(new Event('pywebviewready'));
}
// Wait for DOM to be ready
if (document.readyState === 'loading') {
document.addEventListener('DOMContentLoaded', initAdapter);
} else {
initAdapter();
}
// ==================== Helper Functions ====================
/**
* Download file helper (for CSV export)
*/
window.downloadFile = function(content, filename, type) {
const blob = new Blob([content], { type: type });
const url = URL.createObjectURL(blob);
const a = document.createElement('a');
a.href = url;
a.download = filename;
a.click();
URL.revokeObjectURL(url);
};
})();
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