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Sahil commited on Oct 30, 2025

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1dacc08

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1 Parent(s): 9b276f2

Update index.html

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index.html +96 -172

index.html CHANGED Viewed

@@ -4,7 +4,7 @@
 <head>
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>ContinuumLearner - AI Training Pipeline</title>
     <style>
         * {
             margin: 0;
@@ -67,7 +67,20 @@
             font-size: 14px;
         }
-        .training-area {
             background: white;
             padding: 30px;
             border-radius: 20px;
@@ -75,32 +88,6 @@
             margin-bottom: 30px;
         }
-        .model-selector {
-            display: grid;
-            grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
-            gap: 10px;
-            margin-bottom: 20px;
-        }
-        .model-btn {
-            padding: 15px;
-            background: linear-gradient(135deg, #667eea, #764ba2);
-            color: white;
-            border: none;
-            border-radius: 10px;
-            cursor: pointer;
-            font-size: 14px;
-            transition: transform 0.2s;
-        }
-        .model-btn:hover {
-            transform: translateY(-2px);
-        }
-        .model-btn.active {
-            background: linear-gradient(135deg, #f093fb, #f5576c);
-        }
         .input-area {
             margin-bottom: 20px;
         }
@@ -132,11 +119,6 @@
             transform: translateY(-2px);
         }
-        .btn:disabled {
-            opacity: 0.5;
-            cursor: not-allowed;
-        }
         .response-area {
             background: #f8f9fa;
             padding: 20px;
@@ -165,184 +147,110 @@
             font-size: 14px;
         }
-        .log-entry:last-child {
-            border-bottom: none;
-        }
-        .success {
-            color: #28a745;
-        }
-        .error {
-            color: #dc3545;
-        }
-        .loading {
-            display: inline-block;
-            width: 20px;
-            height: 20px;
-            border: 2px solid rgba(255, 255, 255, 0.3);
-            border-radius: 50%;
-            border-top-color: white;
-            animation: spin 1s linear infinite;
-        }
-        @keyframes spin {
-            to { transform: rotate(360deg); }
-        }
     </style>
 </head>
 <body>
     <div class="container">
         <div class="header">
-            <h1>🧠 ContinuumLearner</h1>
-            <p>Model Training Pipeline - Copy AI Behavior</p>
             <p style="margin-top: 10px; color: #666;">
-                Training dataset: <a href="https://huggingface.co/datasets/Sahil5112/ContinuumGPT" target="_blank" style="color: #667eea;">Sahil5112/ContinuumGPT</a>
             </p>
             <p style="margin-top: 5px; color: #999; font-size: 13px;">
-                🎓 Train ContinuumGPT by copying responses from top AI models
             </p>
         </div>
         <div class="stats">
             <div class="stat-card">
-                <h3 id="totalConversations">0</h3>
-                <p>Training Examples</p>
-            </div>
-            <div class="stat-card">
-                <h3 id="totalTokens">0</h3>
-                <p>Total Tokens</p>
             </div>
             <div class="stat-card">
-                <h3 id="autoGenerated">0</h3>
-                <p>Auto-Generated</p>
             </div>
             <div class="stat-card">
-                <h3 id="manualGenerated">0</h3>
-                <p>Manual</p>
             </div>
             <div class="stat-card">
                 <h3 id="bufferedCount">0</h3>
                 <p>Buffered (Unsaved)</p>
             </div>
             <div class="stat-card">
-                <h3 id="sessionCount">0</h3>
-                <p>This Session</p>
             </div>
         </div>
-        <div class="training-area">
-            <h2 style="margin-bottom: 20px; color: #667eea;">AI Model</h2>
-            <div class="model-selector" id="modelSelector">
-                <button class="model-btn active" data-model="gpt-4o-mini">GPT-4o-mini (Low Credits)</button>
-            </div>
             <div class="input-area">
-                <h3 style="margin-bottom: 10px; color: #667eea;">Training Input</h3>
-                <textarea id="userInput" placeholder="Enter a message to train the AI..."></textarea>
             </div>
-            <button class="btn" onclick="trainModel()">🚀 Train Model</button>
-            <button class="btn" onclick="flushBuffer()">💾 Save to HuggingFace</button>
-            <button class="btn" onclick="refreshStats()">🔄 Refresh Stats</button>
             <div class="response-area">
-                <h3>AI Response</h3>
                 <div id="responseText" style="white-space: pre-wrap;"></div>
             </div>
         </div>
         <div class="log">
-            <h2 style="margin-bottom: 15px; color: #667eea;">Training Log</h2>
-            <div id="trainingLog"></div>
         </div>
     </div>
     <script>
-        let selectedModel = "gpt-4o-mini";
-        let sessionCount = 0;
-        // Model selector
-        document.querySelectorAll('.model-btn').forEach(btn => {
-            btn.addEventListener('click', function() {
-                document.querySelectorAll('.model-btn').forEach(b => b.classList.remove('active'));
-                this.classList.add('active');
-                selectedModel = this.dataset.model;
-                addLog(`Selected model: ${selectedModel}`, 'success');
-            });
-        });
-        async function trainModel() {
-            const userInput = document.getElementById('userInput').value.trim();
-            if (!userInput) {
                 alert('Please enter a message');
                 return;
             }
             const responseText = document.getElementById('responseText');
-            responseText.innerHTML = '<div class="loading"></div> Generating response...';
             try {
-                // Get AI response from backend
-                addLog(`🔄 Calling ${selectedModel}...`, 'success');
-                const generateResponse = await fetch('/api/generate', {
                     method: 'POST',
                     headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({
-                        prompt: userInput,
-                        model: selectedModel
-                    })
                 });
-                const generateData = await generateResponse.json();
-                if (!generateData.success) {
-                    responseText.textContent = `Error: ${generateData.error}`;
-                    addLog(`❌ Error: ${generateData.error}`, 'error');
-                    if (generateData.error.includes('OPENAI_API_KEY')) {
-                        addLog('💡 Add OPENAI_API_KEY to Secrets to enable AI model training', 'error');
-                    }
                     return;
                 }
-                const response = generateData.response;
-                responseText.textContent = response;
-                addLog(`✅ Generated response using ${selectedModel}`, 'success');
-                // Send to backend for training
-                const trainResponse = await fetch('/api/train', {
-                    method: 'POST',
-                    headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({
-                        user_input: userInput,
-                        ai_response: response,
-                        model_used: selectedModel
-                    })
-                });
-                const trainData = await trainResponse.json();
-                if (trainData.success) {
-                    sessionCount++;
-                    document.getElementById('sessionCount').textContent = sessionCount;
-                    document.getElementById('bufferedCount').textContent = trainData.buffered;
-                    addLog(trainData.message, 'success');
-                    // Clear input
-                    document.getElementById('userInput').value = '';
-                    // Auto-save when buffer is full
-                    if (trainData.buffered >= 10) {
-                        addLog('Buffer full! Auto-saving to HuggingFace...', 'success');
-                        await flushBuffer();
-                    }
-                } else {
-                    addLog('❌ Failed to save training data', 'error');
-                }
             } catch (error) {
                 responseText.textContent = `Error: ${error.message}`;
                 addLog(`❌ Error: ${error.message}`, 'error');
@@ -358,10 +266,27 @@
                     addLog(`💾 ${data.message}`, 'success');
                     await refreshStats();
                 } else {
-                    addLog(data.message || 'Buffer empty', 'success');
                 }
             } catch (error) {
-                addLog(`❌ Error flushing buffer: ${error.message}`, 'error');
             }
         }
@@ -371,46 +296,45 @@
                 const data = await response.json();
                 if (data.success) {
-                    document.getElementById('totalConversations').textContent = data.total_examples;
-                    document.getElementById('totalTokens').textContent = data.total_tokens.toLocaleString();
-                    document.getElementById('autoGenerated').textContent = data.auto_generated || 0;
-                    document.getElementById('manualGenerated').textContent = data.manual_generated || 0;
                     document.getElementById('bufferedCount').textContent = data.buffered;
                     addLog('📊 Stats refreshed', 'success');
                 }
             } catch (error) {
-                addLog(`❌ Error refreshing stats: ${error.message}`, 'error');
             }
         }
         function addLog(message, type = '') {
-            const log = document.getElementById('trainingLog');
             const entry = document.createElement('div');
             entry.className = `log-entry ${type}`;
             entry.textContent = `[${new Date().toLocaleTimeString()}] ${message}`;
             log.insertBefore(entry, log.firstChild);
-            // Keep only last 50 entries
             while (log.children.length > 50) {
                 log.removeChild(log.lastChild);
             }
         }
-        // Initialize stats on load
         refreshStats();
-        addLog('🚀 ContinuumLearner initialized', 'success');
-        addLog('🤖 AUTO-TRAINING ACTIVE - Training runs every 5 minutes', 'success');
-        addLog('💡 You can also manually train by entering prompts!', 'success');
-        // Auto-refresh stats every 30 seconds
         setInterval(refreshStats, 30000);
-        // Enter key to submit
-        document.getElementById('userInput').addEventListener('keydown', function(e) {
             if (e.key === 'Enter' && e.ctrlKey) {
-                trainModel();
             }
         });
-    </script>
 </body>
 </html>

 <head>
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>ContinuumGPT - Hierarchical Memory</title>
     <style>
         * {
             margin: 0;
             font-size: 14px;
         }
+        .level-badge {
+            display: inline-block;
+            padding: 2px 8px;
+            border-radius: 12px;
+            font-size: 11px;
+            font-weight: bold;
+            margin-top: 5px;
+        }
+        .level-1 { background: #4CAF50; color: white; }
+        .level-2 { background: #FF9800; color: white; }
+        .level-3 { background: #9C27B0; color: white; }
+        .chat-area {
             background: white;
             padding: 30px;
             border-radius: 20px;
             margin-bottom: 30px;
         }
         .input-area {
             margin-bottom: 20px;
         }
             transform: translateY(-2px);
         }
         .response-area {
             background: #f8f9fa;
             padding: 20px;
             font-size: 14px;
         }
+        .success { color: #28a745; }
+        .error { color: #dc3545; }
     </style>
 </head>
 <body>
     <div class="container">
         <div class="header">
+            <h1>🧠 ContinuumGPT</h1>
+            <p>Hierarchical Memory System</p>
             <p style="margin-top: 10px; color: #666;">
+                Dataset: <a href="https://huggingface.co/datasets/Sahil5112/ContinuumGPT" target="_blank" style="color: #667eea;">Sahil5112/ContinuumGPT</a>
             </p>
             <p style="margin-top: 5px; color: #999; font-size: 13px;">
+                🗄️ Level 1: Fresh → Level 2: Archived → Level 3: Super-Summary
             </p>
         </div>
         <div class="stats">
             <div class="stat-card">
+                <h3 id="level1Count">0</h3>
+                <p>Level 1 (Fresh)</p>
+                <span class="level-badge level-1">Detailed Q&A</span>
             </div>
             <div class="stat-card">
+                <h3 id="level2Count">0</h3>
+                <p>Level 2 (Archived)</p>
+                <span class="level-badge level-2">Compressed</span>
             </div>
             <div class="stat-card">
+                <h3 id="level3Count">0</h3>
+                <p>Level 3 (Super)</p>
+                <span class="level-badge level-3">Global Knowledge</span>
             </div>
             <div class="stat-card">
                 <h3 id="bufferedCount">0</h3>
                 <p>Buffered (Unsaved)</p>
             </div>
             <div class="stat-card">
+                <h3 id="totalEntries">0</h3>
+                <p>Total Entries</p>
             </div>
         </div>
+        <div class="chat-area">
+            <h2 style="margin-bottom: 20px; color: #667eea;">Chat with ContinuumGPT</h2>
             <div class="input-area">
+                <textarea id="userQuery" placeholder="Ask me anything..."></textarea>
             </div>
+            <button class="btn" onclick="sendMessage()">💬 Send</button>
+            <button class="btn" onclick="flushBuffer()">💾 Save Buffer</button>
+            <button class="btn" onclick="archiveNow()">📦 Archive Now</button>
+            <button class="btn" onclick="refreshStats()">🔄 Refresh</button>
             <div class="response-area">
+                <h3>Response</h3>
                 <div id="responseText" style="white-space: pre-wrap;"></div>
+                <div id="summaryText" style="margin-top: 10px; font-style: italic; color: #666;"></div>
             </div>
         </div>
         <div class="log">
+            <h2 style="margin-bottom: 15px; color: #667eea;">Activity Log</h2>
+            <div id="activityLog"></div>
         </div>
     </div>
     <script>
+        async function sendMessage() {
+            const query = document.getElementById('userQuery').value.trim();
+            if (!query) {
                 alert('Please enter a message');
                 return;
             }
             const responseText = document.getElementById('responseText');
+            const summaryText = document.getElementById('summaryText');
+            responseText.innerHTML = '🔄 Thinking...';
+            summaryText.innerHTML = '';
             try {
+                const response = await fetch('/api/chat', {
                     method: 'POST',
                     headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ query })
                 });
+                const data = await response.json();
+                if (!data.success) {
+                    responseText.textContent = `Error: ${data.error}`;
+                    addLog(`❌ Error: ${data.error}`, 'error');
                     return;
                 }
+                responseText.textContent = data.response;
+                summaryText.innerHTML = `📝 Summary: ${data.summary}`;
+                addLog(`✅ Response saved to Level ${data.level} (${data.buffered} buffered)`, 'success');
+                document.getElementById('userQuery').value = '';
+                document.getElementById('bufferedCount').textContent = data.buffered;
+                await refreshStats();
             } catch (error) {
                 responseText.textContent = `Error: ${error.message}`;
                 addLog(`❌ Error: ${error.message}`, 'error');
                     addLog(`💾 ${data.message}`, 'success');
                     await refreshStats();
                 } else {
+                    addLog(data.message, 'success');
                 }
             } catch (error) {
+                addLog(`❌ Error: ${error.message}`, 'error');
+            }
+        }
+        async function archiveNow() {
+            try {
+                addLog('🔄 Running archive process...', 'success');
+                const response = await fetch('/api/archive-now', { method: 'POST' });
+                const data = await response.json();
+                if (data.success) {
+                    addLog(`📦 ${data.message}`, 'success');
+                    await refreshStats();
+                } else {
+                    addLog(`Error: ${data.error}`, 'error');
+                }
+            } catch (error) {
+                addLog(`❌ Error: ${error.message}`, 'error');
             }
         }
                 const data = await response.json();
                 if (data.success) {
+                    document.getElementById('level1Count').textContent = data.level_1_fresh;
+                    document.getElementById('level2Count').textContent = data.level_2_archived;
+                    document.getElementById('level3Count').textContent = data.level_3_super;
                     document.getElementById('bufferedCount').textContent = data.buffered;
+                    document.getElementById('totalEntries').textContent = data.total_entries;
                     addLog('📊 Stats refreshed', 'success');
                 }
             } catch (error) {
+                addLog(`❌ Error: ${error.message}`, 'error');
             }
         }
         function addLog(message, type = '') {
+            const log = document.getElementById('activityLog');
             const entry = document.createElement('div');
             entry.className = `log-entry ${type}`;
             entry.textContent = `[${new Date().toLocaleTimeString()}] ${message}`;
             log.insertBefore(entry, log.firstChild);
             while (log.children.length > 50) {
                 log.removeChild(log.lastChild);
             }
         }
+        // Initialize
         refreshStats();
+        addLog('🚀 ContinuumGPT Hierarchical Memory initialized', 'success');
+        addLog('🗄️ Auto-archiving runs every 10 minutes', 'success');
+        // Auto-refresh
         setInterval(refreshStats, 30000);
+        // Enter to send
+        document.getElementById('userQuery').addEventListener('keydown', function(e) {
             if (e.key === 'Enter' && e.ctrlKey) {
+                sendMessage();
             }
         });
+</script>
 </body>
 </html>