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Update app.py
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app.py
CHANGED
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#!/usr/bin/env python3
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"""
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LibreChat Pyodide Code Interpreter -
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"""
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import gradio as gr
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def create_pyodide_interface():
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"""Create a Gradio interface with
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pyodide_html = """
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<div id="pyodide-container" style="border: 1px solid #ddd; padding: 15px; border-radius: 5px; margin: 10px 0;">
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<div id="pyodide-status" style="font-weight: bold; padding: 10px; background: #f0f0f0; border-radius: 3px;">
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🔄 Loading Pyodide with Plotly...
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</div>
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<div id="debug-info" style="display:none; margin-top: 10px; padding: 10px; background: #fff3cd; border-radius: 3px; font-size: 12px;">
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<strong>Debug Info:</strong>
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<div id="debug-text"></div>
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</div>
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<div id="pyodide-output" style="display:none; margin-top: 10px;">
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<h4>Execution Results:</h4>
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<pre id="output-text" style="background: #f8f8f8; padding: 10px; border-radius: 3px; max-height:
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<div id="plot-container" style="
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</div>
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</div>
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<!-- Load Plotly.js
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<script src="https://cdn.plot.ly/plotly-2.27.0.min.js"></script>
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<script>
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// Global variables
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let pyodide = null;
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let pyodideReady = false;
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let
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let debugMode = true;
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function updateStatus(message, color) {
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color = color || 'black';
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const statusDiv = document.getElementById('pyodide-status');
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if (statusDiv) {
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statusDiv.innerHTML = message;
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statusDiv.style.color = color;
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}
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console.log('
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}
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}
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}
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async function initPyodide() {
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if (initializationStarted) {
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debugLog('Initialization already started');
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return;
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}
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initializationStarted = true;
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try {
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// Check prerequisites
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if (typeof loadPyodide === 'undefined') {
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throw new Error('Pyodide CDN not loaded');
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}
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throw new Error('Plotly CDN not loaded');
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}
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updateStatus('🔄 Loading Pyodide
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debugLog('Starting Pyodide with Plotly support...');
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pyodide = await loadPyodide({
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indexURL: "https://cdn.jsdelivr.net/pyodide/v0.25.0/full/"
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});
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updateStatus('📦 Installing Python packages...', 'blue');
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// Install
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debugLog(`⚠ ${pkg} failed: ${error.message}`);
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}
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}
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// Install plotly via pip in Pyodide
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updateStatus('📦 Installing Plotly via pip...', 'blue');
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try {
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await pyodide.loadPackage(['micropip']);
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await pyodide.runPythonAsync(`
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import micropip
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await micropip.install('plotly')
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`);
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debugLog('✓ Plotly installed via micropip');
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} catch (error) {
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debugLog('⚠ Plotly installation failed: ' + error.message);
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}
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updateStatus('🔧 Setting up
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// Setup Python environment with Plotly
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pyodide.runPython(`
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import sys
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_matplotlib_data = None
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_plotly_data = None
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try:
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import matplotlib.pyplot as plt
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import io
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import base64
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if len(plt.get_fignums()) > 0:
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buffer = io.BytesIO()
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plt.savefig(buffer, format='png', bbox_inches='tight', dpi=100)
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buffer.seek(0)
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plot_data = buffer.getvalue()
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buffer.close()
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_matplotlib_data = base64.b64encode(plot_data).decode()
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plt.close('all')
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return _matplotlib_data
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return None
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except Exception as e:
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print("Matplotlib capture error: " + str(e))
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return None
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def
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try:
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# Convert
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#
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except Exception as e:
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print("
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try:
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import json
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_plotly_data = json.dumps(fig.to_dict())
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print("Plotly captured as JSON (fallback)")
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return _plotly_data
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except:
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return None
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def get_matplotlib_data():
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return _matplotlib_data
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def get_plotly_data():
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return _plotly_data
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global _matplotlib_data, _plotly_data
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_matplotlib_data = None
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_plotly_data = None
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# Setup matplotlib if available
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try:
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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original_show = plt.show
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def custom_show(*args, **kwargs):
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return capture_matplotlib()
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plt.show = custom_show
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print("✅ Matplotlib configured")
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except ImportError:
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print("❌ Matplotlib not available")
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# Setup plotly if available
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try:
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import plotly.graph_objects as go
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import plotly.express as px
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#
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print("✅ Plotly configured")
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print("Available: plotly.graph_objects as 'go', plotly.express as 'px'")
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except ImportError as e:
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print("❌ Plotly
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# Test basic functionality
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try:
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import numpy as np
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print("✅ NumPy available")
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except ImportError:
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print("❌ NumPy not available")
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try:
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import
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except ImportError:
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print("❌
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print("
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`);
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pyodideReady = true;
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updateStatus('✅ Pyodide + Plotly ready!', 'green');
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debugLog('Full initialization complete');
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// Show output area
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const outputDiv = document.getElementById('pyodide-output');
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const outputText = document.getElementById('output-text');
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if (outputText) {
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outputText.textContent = 'Pyodide ready with Plotly support!
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}
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} catch (error) {
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console.error('Initialization error:', error);
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debugLog('Init error: ' + error.message);
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updateStatus('❌ Failed: ' + error.message, 'red');
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pyodideReady = false;
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}
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}
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async function executePyodideCode(code) {
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debugLog('Execute function called');
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if (!pyodideReady) {
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return 'Pyodide
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}
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if (!code || code.trim() === '') {
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return '
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}
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try {
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updateStatus('▶️ Executing
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debugLog('Executing: ' + code.substring(0, 50) + '...');
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// Clear previous plots
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// Capture stdout
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pyodide.runPython(`
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captured_output.getvalue()
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`);
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//
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let matplotlibData = pyodide.runPython('get_matplotlib_data()');
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let plotlyData = pyodide.runPython('get_plotly_data()');
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debugLog('Execution completed');
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// Display results
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const outputText = document.getElementById('output-text');
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const plotContainer = document.getElementById('plot-container');
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// Handle text output
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if (outputText) {
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let textOutput = stdout || '';
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if (result !== undefined && result !== null && result !== '') {
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if (textOutput) textOutput += '\\n';
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textOutput += 'Return: ' + result;
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}
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outputText.textContent = textOutput || 'Code executed successfully
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}
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// Handle plots
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let plotHTML = '';
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if (matplotlibData && matplotlibData.length > 100) {
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plotHTML += `
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<div style="margin: 10px 0;">
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<h5>📊 Matplotlib Plot:</h5>
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<img src="data:image/png;base64,${matplotlibData}"
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style="max-width: 100%; height: auto; border: 1px solid #ddd;"
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alt="Matplotlib Plot">
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</div>
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`;
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}
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if (plotlyData && plotlyData.length > 100) {
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// Check if it's JSON (fallback method)
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if (plotlyData.startsWith('{') || plotlyData.startsWith('[')) {
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try {
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const plotData = JSON.parse(plotlyData);
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plotHTML += `
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<div style="margin: 10px 0;">
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<h5>📈 Interactive Plotly Chart:</h5>
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<div id="plotly-chart-${Date.now()}" style="width: 100%; height: 500px; border: 1px solid #ddd;"></div>
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</div>
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`;
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// Render after DOM update
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setTimeout(() => {
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const chartId = document.querySelector('[id^="plotly-chart-"]').id;
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Plotly.newPlot(chartId, plotData.data, plotData.layout);
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}, 100);
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} catch (e) {
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debugLog('JSON plot rendering failed: ' + e.message);
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}
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} else {
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// HTML method
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plotHTML += `
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<div style="margin: 10px 0;">
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<h5>📈 Interactive Plotly Chart:</h5>
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<div style="border: 1px solid #ddd; border-radius: 5px; padding: 10px;">
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${plotlyData}
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</div>
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</div>
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`;
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}
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}
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if (plotContainer) {
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plotContainer.innerHTML = plotHTML;
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}
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if (plotHTML) {
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updateStatus('✅ Executed with plot(s)!', 'green');
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} else {
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updateStatus('✅ Executed successfully!', 'green');
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}
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return stdout || 'Code executed successfully';
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} catch (error) {
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console.error('Execution error:', error);
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debugLog('Error: ' + error.message);
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const outputText = document.getElementById('output-text');
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if (outputText) {
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outputText.textContent = 'Error: ' + error.toString();
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}
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updateStatus('❌
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return 'Error: ' + error.toString();
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}
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}
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//
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await initPyodide();
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return;
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}
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} catch (error) {
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debugLog(`Init attempt ${retries + 1} failed: ${error.message}`);
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}
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retries++;
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if (retries < maxRetries) {
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debugLog(`Retrying in ${retries * 2} seconds...`);
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await new Promise(resolve => setTimeout(resolve, retries * 2000));
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}
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}
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updateStatus('❌ Initialization failed after ' + maxRetries + ' attempts', 'red');
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}
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//
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function waitForCDNs() {
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const checkInterval = setInterval(() => {
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if (typeof loadPyodide !== 'undefined' && typeof Plotly !== 'undefined') {
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clearInterval(checkInterval);
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debugLog('Both CDNs loaded, starting init');
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safeInit();
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} else {
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debugLog('Waiting for CDNs... Pyodide: ' + (typeof loadPyodide !== 'undefined') + ', Plotly: ' + (typeof Plotly !== 'undefined'));
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}
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}, 1000);
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// Timeout after 30 seconds
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setTimeout(() => {
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clearInterval(checkInterval);
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if (!pyodideReady) {
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updateStatus('❌ CDN loading timeout', 'red');
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}
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}, 30000);
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}
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// Start when DOM is ready
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if (document.readyState === 'loading') {
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document.addEventListener('DOMContentLoaded',
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} else {
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}
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// Global functions
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window.executePyodideCode = executePyodideCode;
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window.checkPyodideStatus = () => pyodideReady;
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window.toggleDebugMode = function() {
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debugMode = !debugMode;
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const debugDiv = document.getElementById('debug-info');
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if (debugDiv) debugDiv.style.display = debugMode ? 'block' : 'none';
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return debugMode;
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};
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</script>
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<script src="https://cdn.jsdelivr.net/pyodide/v0.25.0/full/pyodide.js" async></script>
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"""
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return pyodide_html
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# Create the Gradio interface
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| 450 |
-
with gr.Blocks(title="Pyodide + Plotly Code Interpreter") as demo:
|
| 451 |
-
gr.Markdown("# 🐍📈 Pyodide + Plotly Code Interpreter")
|
| 452 |
-
gr.Markdown("**Interactive Python with Plotly charts** - runs entirely in your browser!")
|
| 453 |
-
|
| 454 |
-
# Pyodide interface
|
| 455 |
-
pyodide_interface = gr.HTML(create_pyodide_interface())
|
| 456 |
-
|
| 457 |
-
with gr.Row():
|
| 458 |
-
with gr.Column(scale=2):
|
| 459 |
-
code_input = gr.Textbox(
|
| 460 |
-
value="""# Plotly Example 1: Simple Line Chart
|
| 461 |
-
import plotly.graph_objects as go
|
| 462 |
-
import numpy as np
|
| 463 |
-
|
| 464 |
-
# Generate data
|
| 465 |
-
x = np.linspace(0, 10, 100)
|
| 466 |
-
y1 = np.sin(x)
|
| 467 |
-
y2 = np.cos(x)
|
| 468 |
-
|
| 469 |
-
# Create figure
|
| 470 |
-
fig = go.Figure()
|
| 471 |
-
fig.add_trace(go.Scatter(x=x, y=y1, name='sin(x)', line=dict(color='blue')))
|
| 472 |
-
fig.add_trace(go.Scatter(x=x, y=y2, name='cos(x)', line=dict(color='red')))
|
| 473 |
-
|
| 474 |
-
fig.update_layout(
|
| 475 |
-
title='Interactive Sine and Cosine Waves',
|
| 476 |
-
xaxis_title='X values',
|
| 477 |
-
yaxis_title='Y values',
|
| 478 |
-
hovermode='x unified'
|
| 479 |
-
)
|
| 480 |
-
|
| 481 |
-
fig.show()
|
| 482 |
-
print("Interactive Plotly chart created! 🎉")""",
|
| 483 |
-
lines=18,
|
| 484 |
-
label="Python Code with Plotly"
|
| 485 |
-
)
|
| 486 |
-
|
| 487 |
-
with gr.Row():
|
| 488 |
-
execute_btn = gr.Button("🚀 Execute", variant="primary", size="lg")
|
| 489 |
-
examples_btn = gr.Button("📋 Load Examples", variant="secondary")
|
| 490 |
-
|
| 491 |
-
with gr.Column(scale=1):
|
| 492 |
-
gr.Markdown("### 🎛️ Controls")
|
| 493 |
-
|
| 494 |
-
status_display = gr.Textbox(
|
| 495 |
-
label="Status",
|
| 496 |
-
interactive=False,
|
| 497 |
-
lines=4
|
| 498 |
-
)
|
| 499 |
-
|
| 500 |
-
with gr.Row():
|
| 501 |
-
check_btn = gr.Button("📊 Status", size="sm")
|
| 502 |
-
debug_btn = gr.Button("🐛 Debug", size="sm")
|
| 503 |
-
|
| 504 |
-
# Example code snippets
|
| 505 |
-
examples = {
|
| 506 |
-
"Plotly Bar Chart": """import plotly.express as px
|
| 507 |
-
import pandas as pd
|
| 508 |
-
|
| 509 |
-
# Sample data
|
| 510 |
-
data = {
|
| 511 |
-
'Category': ['A', 'B', 'C', 'D', 'E'],
|
| 512 |
-
'Values': [23, 45, 56, 78, 32],
|
| 513 |
-
'Colors': ['red', 'blue', 'green', 'orange', 'purple']
|
| 514 |
-
}
|
| 515 |
-
df = pd.DataFrame(data)
|
| 516 |
-
|
| 517 |
-
# Create bar chart
|
| 518 |
-
fig = px.bar(df, x='Category', y='Values', color='Colors',
|
| 519 |
-
title='Interactive Bar Chart',
|
| 520 |
-
labels={'Values': 'Count'})
|
| 521 |
-
|
| 522 |
-
fig.show()
|
| 523 |
-
print("Bar chart created!")""",
|
| 524 |
-
|
| 525 |
-
"Plotly 3D Scatter": """import plotly.graph_objects as go
|
| 526 |
-
import numpy as np
|
| 527 |
-
|
| 528 |
-
# Generate 3D data
|
| 529 |
-
n = 100
|
| 530 |
-
x = np.random.randn(n)
|
| 531 |
-
y = np.random.randn(n)
|
| 532 |
-
z = np.random.randn(n)
|
| 533 |
-
colors = np.random.randn(n)
|
| 534 |
-
|
| 535 |
-
# Create 3D scatter plot
|
| 536 |
-
fig = go.Figure(data=go.Scatter3d(
|
| 537 |
-
x=x, y=y, z=z,
|
| 538 |
-
mode='markers',
|
| 539 |
-
marker=dict(
|
| 540 |
-
size=8,
|
| 541 |
-
color=colors,
|
| 542 |
-
colorscale='Viridis',
|
| 543 |
-
showscale=True
|
| 544 |
-
)
|
| 545 |
-
))
|
| 546 |
-
|
| 547 |
-
fig.update_layout(
|
| 548 |
-
title='Interactive 3D Scatter Plot',
|
| 549 |
-
scene=dict(
|
| 550 |
-
xaxis_title='X Axis',
|
| 551 |
-
yaxis_title='Y Axis',
|
| 552 |
-
zaxis_title='Z Axis'
|
| 553 |
-
)
|
| 554 |
-
)
|
| 555 |
-
|
| 556 |
-
fig.show()
|
| 557 |
-
print("3D scatter plot created!")""",
|
| 558 |
-
|
| 559 |
-
"Plotly Dashboard": """import plotly.graph_objects as go
|
| 560 |
-
from plotly.subplots import make_subplots
|
| 561 |
-
import numpy as np
|
| 562 |
-
|
| 563 |
-
# Generate sample data
|
| 564 |
-
x = np.linspace(0, 10, 50)
|
| 565 |
-
y1 = np.sin(x)
|
| 566 |
-
y2 = np.cos(x)
|
| 567 |
-
y3 = np.random.normal(0, 0.1, len(x))
|
| 568 |
-
|
| 569 |
-
# Create subplots
|
| 570 |
-
fig = make_subplots(
|
| 571 |
-
rows=2, cols=2,
|
| 572 |
-
subplot_titles=('Line Plot', 'Histogram', 'Box Plot', 'Heatmap'),
|
| 573 |
-
specs=[[{"secondary_y": True}, {}],
|
| 574 |
-
[{}, {}]]
|
| 575 |
-
)
|
| 576 |
-
|
| 577 |
-
# Add line plot
|
| 578 |
-
fig.add_trace(go.Scatter(x=x, y=y1, name='sin(x)'), row=1, col=1)
|
| 579 |
-
fig.add_trace(go.Scatter(x=x, y=y2, name='cos(x)', yaxis='y2'), row=1, col=1, secondary_y=True)
|
| 580 |
-
|
| 581 |
-
# Add histogram
|
| 582 |
-
fig.add_trace(go.Histogram(x=np.random.normal(0, 1, 1000), name='Normal Dist'), row=1, col=2)
|
| 583 |
-
|
| 584 |
-
# Add box plot
|
| 585 |
-
categories = ['A', 'B', 'C']
|
| 586 |
-
values = [np.random.normal(i, 0.5, 100) for i in range(len(categories))]
|
| 587 |
-
for i, (cat, vals) in enumerate(zip(categories, values)):
|
| 588 |
-
fig.add_trace(go.Box(y=vals, name=cat), row=2, col=1)
|
| 589 |
-
|
| 590 |
-
# Add heatmap
|
| 591 |
-
z = np.random.randn(10, 10)
|
| 592 |
-
fig.add_trace(go.Heatmap(z=z, colorscale='RdBu'), row=2, col=2)
|
| 593 |
-
|
| 594 |
-
fig.update_layout(height=600, title_text="Multi-Plot Dashboard")
|
| 595 |
-
fig.show()
|
| 596 |
-
print("Dashboard created with multiple charts!")"""
|
| 597 |
-
}
|
| 598 |
-
|
| 599 |
-
def load_example():
|
| 600 |
-
return examples["Plotly Bar Chart"]
|
| 601 |
-
|
| 602 |
-
examples_btn.click(
|
| 603 |
-
fn=load_example,
|
| 604 |
-
inputs=[],
|
| 605 |
-
outputs=[code_input]
|
| 606 |
-
)
|
| 607 |
-
|
| 608 |
-
# Event handlers
|
| 609 |
-
execute_btn.click(
|
| 610 |
-
fn=None,
|
| 611 |
-
inputs=[code_input],
|
| 612 |
-
outputs=[status_display],
|
| 613 |
-
js="""
|
| 614 |
-
function(code) {
|
| 615 |
-
try {
|
| 616 |
-
if (window.executePyodideCode) {
|
| 617 |
-
return window.executePyodideCode(code);
|
| 618 |
-
} else {
|
| 619 |
-
return 'Execution function not available';
|
| 620 |
-
}
|
| 621 |
-
} catch (error) {
|
| 622 |
-
return 'Error: ' + error.message;
|
| 623 |
-
}
|
| 624 |
-
}
|
| 625 |
-
"""
|
| 626 |
-
)
|
| 627 |
-
|
| 628 |
-
check_btn.click(
|
| 629 |
-
fn=None,
|
| 630 |
-
inputs=[],
|
| 631 |
-
outputs=[status_display],
|
| 632 |
-
js="""
|
| 633 |
-
function() {
|
| 634 |
-
try {
|
| 635 |
-
const ready = window.checkPyodideStatus ? window.checkPyodideStatus() : false;
|
| 636 |
-
return ready ? '✅ Ready for Plotly!' : '⏳ Still loading...';
|
| 637 |
-
} catch (error) {
|
| 638 |
-
return 'Status error: ' + error.message;
|
| 639 |
-
}
|
| 640 |
-
}
|
| 641 |
-
"""
|
| 642 |
-
)
|
| 643 |
-
|
| 644 |
-
debug_btn.click(
|
| 645 |
-
fn=None,
|
| 646 |
-
inputs=[],
|
| 647 |
-
outputs=[status_display],
|
| 648 |
-
js="""
|
| 649 |
-
function() {
|
| 650 |
-
try {
|
| 651 |
-
if (window.toggleDebugMode) {
|
| 652 |
-
return window.toggleDebugMode() ? '🐛 Debug ON' : '🐛 Debug OFF';
|
| 653 |
-
}
|
| 654 |
-
return 'Debug toggle unavailable';
|
| 655 |
-
} catch (error) {
|
| 656 |
-
return 'Debug error: ' + error.message;
|
| 657 |
-
}
|
| 658 |
-
}
|
| 659 |
-
"""
|
| 660 |
-
)
|
| 661 |
-
|
| 662 |
-
if __name__ == "__main__":
|
| 663 |
-
print("🚀 Starting Pyodide + Plotly Interpreter...")
|
| 664 |
-
demo.launch(
|
| 665 |
-
server_name="0.0.0.0",
|
| 666 |
-
server_port=7860,
|
| 667 |
-
share=False
|
| 668 |
-
)
|
|
|
|
| 1 |
#!/usr/bin/env python3
|
| 2 |
"""
|
| 3 |
+
LibreChat Pyodide Code Interpreter - Working Plotly Integration
|
| 4 |
"""
|
| 5 |
|
| 6 |
import gradio as gr
|
| 7 |
|
| 8 |
def create_pyodide_interface():
|
| 9 |
+
"""Create a Gradio interface with working Plotly support"""
|
| 10 |
|
| 11 |
pyodide_html = """
|
| 12 |
<div id="pyodide-container" style="border: 1px solid #ddd; padding: 15px; border-radius: 5px; margin: 10px 0;">
|
| 13 |
<div id="pyodide-status" style="font-weight: bold; padding: 10px; background: #f0f0f0; border-radius: 3px;">
|
| 14 |
+
🔄 Loading Pyodide with Plotly...
|
|
|
|
|
|
|
|
|
|
|
|
|
| 15 |
</div>
|
| 16 |
<div id="pyodide-output" style="display:none; margin-top: 10px;">
|
| 17 |
<h4>Execution Results:</h4>
|
| 18 |
+
<pre id="output-text" style="background: #f8f8f8; padding: 10px; border-radius: 3px; max-height: 200px; overflow-y: auto; white-space: pre-wrap;"></pre>
|
| 19 |
+
<div id="plot-container" style="margin-top: 15px;"></div>
|
| 20 |
</div>
|
| 21 |
</div>
|
| 22 |
|
| 23 |
+
<!-- Load Plotly.js -->
|
| 24 |
<script src="https://cdn.plot.ly/plotly-2.27.0.min.js"></script>
|
| 25 |
|
| 26 |
<script>
|
|
|
|
| 27 |
let pyodide = null;
|
| 28 |
let pyodideReady = false;
|
| 29 |
+
let plotCounter = 0;
|
|
|
|
| 30 |
|
| 31 |
+
function updateStatus(message, color = 'black') {
|
|
|
|
| 32 |
const statusDiv = document.getElementById('pyodide-status');
|
| 33 |
if (statusDiv) {
|
| 34 |
statusDiv.innerHTML = message;
|
| 35 |
statusDiv.style.color = color;
|
| 36 |
}
|
| 37 |
+
console.log('Status:', message);
|
| 38 |
}
|
| 39 |
|
| 40 |
+
// Custom Plotly renderer for Pyodide
|
| 41 |
+
window.renderPlotlyFromPython = function(plotData, plotLayout, plotConfig) {
|
| 42 |
+
try {
|
| 43 |
+
plotCounter++;
|
| 44 |
+
const plotId = 'pyodide-plot-' + plotCounter;
|
| 45 |
+
const plotContainer = document.getElementById('plot-container');
|
| 46 |
+
|
| 47 |
+
if (!plotContainer) {
|
| 48 |
+
console.error('Plot container not found');
|
| 49 |
+
return false;
|
| 50 |
+
}
|
| 51 |
+
|
| 52 |
+
// Create new plot div
|
| 53 |
+
const plotDiv = document.createElement('div');
|
| 54 |
+
plotDiv.id = plotId;
|
| 55 |
+
plotDiv.style.width = '100%';
|
| 56 |
+
plotDiv.style.height = '500px';
|
| 57 |
+
plotDiv.style.margin = '10px 0';
|
| 58 |
+
plotDiv.style.border = '1px solid #ddd';
|
| 59 |
+
plotDiv.style.borderRadius = '5px';
|
| 60 |
+
|
| 61 |
+
// Add title
|
| 62 |
+
const title = document.createElement('h5');
|
| 63 |
+
title.textContent = '📈 Interactive Plotly Chart #' + plotCounter;
|
| 64 |
+
title.style.margin = '10px 0 5px 0';
|
| 65 |
+
|
| 66 |
+
plotContainer.appendChild(title);
|
| 67 |
+
plotContainer.appendChild(plotDiv);
|
| 68 |
+
|
| 69 |
+
// Parse data if it's a string
|
| 70 |
+
if (typeof plotData === 'string') {
|
| 71 |
+
plotData = JSON.parse(plotData);
|
| 72 |
+
}
|
| 73 |
+
if (typeof plotLayout === 'string') {
|
| 74 |
+
plotLayout = JSON.parse(plotLayout);
|
| 75 |
+
}
|
| 76 |
+
if (typeof plotConfig === 'string') {
|
| 77 |
+
plotConfig = JSON.parse(plotConfig);
|
| 78 |
+
}
|
| 79 |
+
|
| 80 |
+
// Create the plot
|
| 81 |
+
Plotly.newPlot(plotId, plotData, plotLayout, plotConfig || {responsive: true});
|
| 82 |
+
|
| 83 |
+
console.log('Plotly chart rendered successfully:', plotId);
|
| 84 |
+
return true;
|
| 85 |
+
|
| 86 |
+
} catch (error) {
|
| 87 |
+
console.error('Plotly rendering error:', error);
|
| 88 |
+
return false;
|
| 89 |
}
|
| 90 |
+
};
|
| 91 |
|
| 92 |
async function initPyodide() {
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 93 |
try {
|
|
|
|
| 94 |
if (typeof loadPyodide === 'undefined') {
|
| 95 |
throw new Error('Pyodide CDN not loaded');
|
| 96 |
}
|
|
|
|
| 98 |
throw new Error('Plotly CDN not loaded');
|
| 99 |
}
|
| 100 |
|
| 101 |
+
updateStatus('🔄 Loading Pyodide...', 'blue');
|
|
|
|
| 102 |
|
| 103 |
pyodide = await loadPyodide({
|
| 104 |
indexURL: "https://cdn.jsdelivr.net/pyodide/v0.25.0/full/"
|
| 105 |
});
|
| 106 |
|
| 107 |
+
updateStatus('📦 Installing packages...', 'blue');
|
|
|
|
| 108 |
|
| 109 |
+
// Install packages
|
| 110 |
+
await pyodide.loadPackage(['numpy', 'pandas']);
|
| 111 |
|
| 112 |
+
// Install plotly via micropip
|
| 113 |
+
await pyodide.loadPackage(['micropip']);
|
| 114 |
+
await pyodide.runPythonAsync(`
|
| 115 |
+
import micropip
|
| 116 |
+
await micropip.install('plotly')
|
| 117 |
+
`);
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 118 |
|
| 119 |
+
updateStatus('🔧 Setting up Plotly integration...', 'blue');
|
| 120 |
|
| 121 |
+
// Setup Python environment with proper Plotly integration
|
| 122 |
pyodide.runPython(`
|
| 123 |
import sys
|
| 124 |
+
import json
|
| 125 |
+
from js import renderPlotlyFromPython
|
| 126 |
|
| 127 |
+
print("Setting up Plotly integration...")
|
|
|
|
|
|
|
| 128 |
|
| 129 |
+
# Global storage
|
| 130 |
+
_plots_created = 0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 131 |
|
| 132 |
+
def show_plotly_figure(fig):
|
| 133 |
+
"""Custom show function that renders plots in the browser"""
|
| 134 |
+
global _plots_created
|
| 135 |
try:
|
| 136 |
+
# Convert figure to JSON
|
| 137 |
+
fig_json = fig.to_json()
|
| 138 |
+
fig_dict = json.loads(fig_json)
|
| 139 |
|
| 140 |
+
# Extract components
|
| 141 |
+
data = json.dumps(fig_dict.get('data', []))
|
| 142 |
+
layout = json.dumps(fig_dict.get('layout', {}))
|
| 143 |
+
config = json.dumps({'responsive': True, 'displayModeBar': True})
|
| 144 |
+
|
| 145 |
+
# Call JavaScript renderer
|
| 146 |
+
success = renderPlotlyFromPython(data, layout, config)
|
| 147 |
+
|
| 148 |
+
if success:
|
| 149 |
+
_plots_created += 1
|
| 150 |
+
print(f"✅ Plot #{_plots_created} rendered successfully!")
|
| 151 |
+
return True
|
| 152 |
+
else:
|
| 153 |
+
print("❌ Plot rendering failed")
|
| 154 |
+
return False
|
| 155 |
|
| 156 |
except Exception as e:
|
| 157 |
+
print(f"❌ Plot error: {e}")
|
| 158 |
+
return False
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 159 |
|
| 160 |
+
# Patch Plotly's show methods
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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| 161 |
try:
|
| 162 |
import plotly.graph_objects as go
|
| 163 |
import plotly.express as px
|
| 164 |
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| 165 |
+
# Override the show method for graph_objects
|
| 166 |
+
original_show = go.Figure.show
|
| 167 |
+
def custom_show(self, *args, **kwargs):
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| 168 |
+
return show_plotly_figure(self)
|
| 169 |
+
go.Figure.show = custom_show
|
| 170 |
|
| 171 |
+
print("✅ Plotly graph_objects patched")
|
| 172 |
+
|
| 173 |
+
# Test basic functionality
|
| 174 |
+
print("✅ Plotly integration ready!")
|
| 175 |
+
print("Use fig.show() to display interactive plots")
|
| 176 |
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| 177 |
except ImportError as e:
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| 178 |
+
print(f"❌ Plotly import failed: {e}")
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| 179 |
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| 180 |
+
# Also set up matplotlib fallback
|
| 181 |
try:
|
| 182 |
+
import matplotlib
|
| 183 |
+
matplotlib.use('Agg')
|
| 184 |
+
import matplotlib.pyplot as plt
|
| 185 |
+
print("✅ Matplotlib also available")
|
| 186 |
except ImportError:
|
| 187 |
+
print("❌ Matplotlib not available")
|
| 188 |
|
| 189 |
+
print("🎉 Python environment ready!")
|
| 190 |
`);
|
| 191 |
|
| 192 |
pyodideReady = true;
|
| 193 |
updateStatus('✅ Pyodide + Plotly ready!', 'green');
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|
| 194 |
|
| 195 |
// Show output area
|
| 196 |
const outputDiv = document.getElementById('pyodide-output');
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|
| 198 |
|
| 199 |
const outputText = document.getElementById('output-text');
|
| 200 |
if (outputText) {
|
| 201 |
+
outputText.textContent = 'Pyodide ready with Plotly support! Try the examples.';
|
| 202 |
}
|
| 203 |
|
| 204 |
} catch (error) {
|
| 205 |
console.error('Initialization error:', error);
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|
| 206 |
updateStatus('❌ Failed: ' + error.message, 'red');
|
| 207 |
pyodideReady = false;
|
| 208 |
}
|
| 209 |
}
|
| 210 |
|
| 211 |
async function executePyodideCode(code) {
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|
| 212 |
if (!pyodideReady) {
|
| 213 |
+
return 'Pyodide not ready. Please wait for green status.';
|
| 214 |
}
|
| 215 |
|
| 216 |
if (!code || code.trim() === '') {
|
| 217 |
+
return 'No code provided.';
|
| 218 |
}
|
| 219 |
|
| 220 |
try {
|
| 221 |
+
updateStatus('▶️ Executing...', 'blue');
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|
| 222 |
|
| 223 |
// Clear previous plots
|
| 224 |
+
const plotContainer = document.getElementById('plot-container');
|
| 225 |
+
if (plotContainer) plotContainer.innerHTML = '';
|
| 226 |
|
| 227 |
// Capture stdout
|
| 228 |
pyodide.runPython(`
|
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|
| 241 |
captured_output.getvalue()
|
| 242 |
`);
|
| 243 |
|
| 244 |
+
// Display text output
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|
| 245 |
const outputText = document.getElementById('output-text');
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|
| 246 |
if (outputText) {
|
| 247 |
let textOutput = stdout || '';
|
| 248 |
if (result !== undefined && result !== null && result !== '') {
|
| 249 |
if (textOutput) textOutput += '\\n';
|
| 250 |
textOutput += 'Return: ' + result;
|
| 251 |
}
|
| 252 |
+
outputText.textContent = textOutput || 'Code executed successfully';
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|
| 253 |
}
|
| 254 |
|
| 255 |
+
updateStatus('✅ Executed!', 'green');
|
| 256 |
return stdout || 'Code executed successfully';
|
| 257 |
|
| 258 |
} catch (error) {
|
| 259 |
console.error('Execution error:', error);
|
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|
| 260 |
|
| 261 |
const outputText = document.getElementById('output-text');
|
| 262 |
if (outputText) {
|
| 263 |
outputText.textContent = 'Error: ' + error.toString();
|
| 264 |
}
|
| 265 |
+
updateStatus('❌ Error', 'red');
|
| 266 |
return 'Error: ' + error.toString();
|
| 267 |
}
|
| 268 |
}
|
| 269 |
|
| 270 |
+
// Wait for both CDNs
|
| 271 |
+
function waitForReady() {
|
| 272 |
+
if (typeof loadPyodide !== 'undefined' && typeof Plotly !== 'undefined') {
|
| 273 |
+
console.log('Both CDNs loaded, initializing...');
|
| 274 |
+
initPyodide();
|
| 275 |
+
} else {
|
| 276 |
+
console.log('Waiting for CDNs... Pyodide:', typeof loadPyodide !== 'undefined', 'Plotly:', typeof Plotly !== 'undefined');
|
| 277 |
+
setTimeout(waitForReady, 1000);
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|
| 278 |
}
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|
| 279 |
}
|
| 280 |
|
| 281 |
+
// Start when ready
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|
| 282 |
if (document.readyState === 'loading') {
|
| 283 |
+
document.addEventListener('DOMContentLoaded', waitForReady);
|
| 284 |
} else {
|
| 285 |
+
waitForReady();
|
| 286 |
}
|
| 287 |
|
| 288 |
// Global functions
|
| 289 |
window.executePyodideCode = executePyodideCode;
|
| 290 |
window.checkPyodideStatus = () => pyodideReady;
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|
| 291 |
|
| 292 |
</script>
|
| 293 |
+
<script src="https://cdn.jsdelivr.net/pyodide/v0.25.0/full/pyodide.js" async></script>
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