acionar campo de de geração do script avançado e proficssional do trading view e automaatico , crie pela rede neural, crie a evolução da rede neural da curva financeira - Follow Up Deployment

index.html

@@ -96,6 +96,25 @@
                     </div>
                 </div>
                 
+                <!-- TradingView Script Generator -->
+                <div class="card-glass p-4 mb-6">
+                    <h2 class="text-xl font-semibold mb-4">NeuralNet Script Generator</h2>
+                    <div class="mb-4">
+                        <label class="block text-sm font-medium mb-2">Strategy Complexity</label>
+                        <select class="w-full bg-gray-800 border border-gray-700 rounded-md px-3 py-2 text-sm">
+                            <option>Basic Mean Reversion</option>
+                            <option>Advanced Momentum</option>
+                            <option selected>NeuralNet HFT</option>
+                            <option>Quantum Pattern</option>
+                        </select>
+                    </div>
+                    <div class="mb-4">
+                        <label class="block text-sm font-medium mb-2">Custom Parameters</label>
+                        <textarea class="w-full bg-gray-800 border border-gray-700 rounded-md px-3 py-2 text-sm h-32" placeholder="// Custom neural network parameters..."></textarea>
+                    </div>
+                    <button class="w-full bg-blue-600 hover:bg-blue-500 py-2 rounded-md">Generate TradingView Script</button>
+                </div>
+
                 <!-- Performance Metrics -->
                 <div class="card-glass p-4">
                     <h2 class="text-xl font-semibold mb-4">Performance Metrics</h2>
@@ -317,12 +336,116 @@
                 }
             });
 
+            // Initialize neural network evolution chart
+            const nnCtx = document.getElementById('nnChart').getContext('2d');
+            
+            // Generate mock neural network training data
+            const nnData = [];
+            let accuracy = 80;
+            for (let i = 0; i < 50; i++) {
+                accuracy += Math.random() * 0.5;
+                if (accuracy > 98) accuracy = 98;
+                nnData.push(accuracy);
+            }
+            
+            const nnChart = new Chart(nnCtx, {
+                type: 'line',
+                data: {
+                    labels: Array.from({length: 50}, (_, i) => i + 1),
+                    datasets: [
+                        {
+                            label: 'Accuracy',
+                            data: nnData,
+                            borderColor: '#00b3ff',
+                            borderWidth: 2,
+                            pointRadius: 0,
+                            tension: 0.3,
+                            yAxisID: 'y'
+                        },
+                        {
+                            label: 'Loss',
+                            data: nnData.map(v => 100-v),
+                            borderColor: '#ff4d4d',
+                            borderWidth: 1,
+                            pointRadius: 0,
+                            tension: 0.3,
+                            yAxisID: 'y1'
+                        }
+                    ]
+                },
+                options: {
+                    responsive: true,
+                    maintainAspectRatio: false,
+                    interaction: {
+                        mode: 'index',
+                        intersect: false,
+                    },
+                    plugins: {
+                        legend: {
+                            position: 'top',
+                            labels: {
+                                color: 'rgba(255, 255, 255, 0.7)'
+                            }
+                        },
+                        tooltip: {
+                            mode: 'index',
+                            intersect: false,
+                        }
+                    },
+                    scales: {
+                        x: {
+                            grid: {
+                                color: 'rgba(255, 255, 255, 0.05)'
+                            },
+                            ticks: {
+                                color: 'rgba(255, 255, 255, 0.7)'
+                            }
+                        },
+                        y: {
+                            type: 'linear',
+                            display: true,
+                            position: 'left',
+                            min: 70,
+                            max: 100,
+                            grid: {
+                                color: 'rgba(255, 255, 255, 0.05)'
+                            },
+                            ticks: {
+                                color: 'rgba(255, 255, 255, 0.7)'
+                            }
+                        },
+                        y1: {
+                            type: 'linear',
+                            display: true,
+                            position: 'right',
+                            min: 0,
+                            max: 30,
+                            grid: {
+                                drawOnChartArea: false,
+                            },
+                            ticks: {
+                                color: 'rgba(255, 255, 255, 0.7)'
+                            }
+                        }
+                    }
+                }
+            });
+
             // Simulate live data updates
             setInterval(() => {
                 const newValue = data[data.length - 1] + (Math.random() - 0.5) * 0.001;
                 data.push(newValue);
                 data.shift();
                 chart.update();
+                
+                // Update neural network chart
+                const newAccuracy = nnData[nnData.length - 1] + (Math.random() - 0.45) * 0.2;
+                if (newAccuracy > 98.5) nnData.push(98.5);
+                else if (newAccuracy < 97.5) nnData.push(97.5);
+                else nnData.push(newAccuracy);
+                nnData.shift();
+                nnChart.data.datasets[1].data = nnData.map(v => 100-v);
+                nnChart.update();
             }, 2000);
         });
     </script>