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jjmandog commited on Jun 9

Commit

2470a41

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1 Parent(s): fd46987

Buttons still don’t work. I still can’t train. Fix make everything functional - Follow Up Deployment

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Files changed (2) hide show

index.html +267 -64
prompts.txt +3 -1

index.html CHANGED Viewed

@@ -1,4 +1,4 @@
-<!DOCTYPE html>
 <html lang="en">
 <head>
     <meta charset="UTF-8">
@@ -627,16 +627,43 @@
         // Initialize Natural Language Processing
         const nlp = {
             processInput: function(text) {
-                // Simple NLP processing
                 text = text.toLowerCase().trim();
-                const keywords = {
-                    business: ["work", "job", "meeting", "business"],
-                    personal: ["family", "friend", "mom", "dad"],
-                    spam: ["spam", "block", "unwanted", "telemarketer"],
-                    question: ["what", "when", "where", "how", "why", "can you", "would you"]
                 };
-                return text;
             },
             learnResponse: function(inputText, preferredResponse) {
                 // Tokenize input and learn patterns
@@ -794,96 +821,272 @@
                 chatContainer.appendChild(userBubble);
                 // Process user input and generate AI response
-                setTimeout(async () => {
-                    const isTeachingExample = userMessage.includes("should respond");
                     let aiResponse;
                     if (isTeachingExample) {
-                        // Extract teaching example
-                        const parts = userMessage.split("should respond");
-                        const question = parts[0].trim();
-                        const answer = parts[1].replace(/with/i, '').trim();
-                        // Teach the AI this response
-                        nlp.learnResponse(question, answer);
-                        aiResponse = `
-                            <p>Got it! I've learned this response:</p>
-                            <div class="mt-2 bg-blue-50 dark:bg-blue-900 rounded-lg p-3">
-                                <p><strong>Question:</strong> ${question}</p>
-                                <p><strong>Answer:</strong> ${answer}</p>
-                            </div>
-                            <p class="mt-2">I'll use this response when I hear similar questions.</p>
-                        `;
                     } else {
-                        // Get smart response based on learned data
                         const response = nlp.getBestResponse(userMessage);
                         aiResponse = `
-                            <p>Based on what you've taught me, here's how I would respond:</p>
                             <div class="mt-2 bg-blue-50 dark:bg-blue-900 rounded-lg p-3">
                                 <p>${response}</p>
                             </div>
                         `;
                     }
                     const aiBubble = document.createElement('div');
                     aiBubble.className = 'ai-bubble mt-4 animate-fadeIn';
-                    aiBubble.innerHTML = aiResponse + `
-                        <div class="mt-3 flex gap-2">
-                            <button class="flex-1 py-2 bg-green-500 text-white rounded-lg" onclick="acceptResponse(this)">
-                                Accept <i class="fas fa-check ml-1"></i>
-                            </button>
-                            <button class="flex-1 py-2 bg-red-500 text-white rounded-lg" onclick="editResponse(this)">
-                                Edit <i class="fas fa-edit ml-1"></i>
-                            </button>
-                            <button class="px-3 py-2 bg-accent text-white rounded-lg" onclick="playResponse(this)">
-                                <i class="fas fa-volume-up"></i>
-                            </button>
-                        </div>
-                    `;
                     chatContainer.appendChild(aiBubble);
                     chatContainer.scrollTop = chatContainer.scrollHeight;
-                }, 800);
                 input.value = '';
             }
         }
         function acceptResponse(button) {
-            const responseText = button.closest('.ai-bubble').querySelector('div p').textContent;
-            const context = nlp.determineContext(responseText);
-            trainingData.customResponses[context] = responseText;
-            nlp.saveToLocalStorage();
-            button.innerHTML = '<i class="fas fa-check-circle"></i> Saved';
-            button.classList.remove('bg-green-500');
-            button.classList.add('bg-emerald-600');
         }
         function editResponse(button) {
             const bubble = button.closest('.ai-bubble');
             const responseDiv = bubble.querySelector('div.bg-blue-50');
-            const currentText = responseDiv.querySelector('p').textContent;
             responseDiv.innerHTML = `
-                <textarea class="w-full p-2 rounded border border-gray-300">${currentText}</textarea>
-                <button onclick="saveEditedResponse(this)" class="mt-2 px-4 py-1 bg-accent text-white rounded">
-                    Save Changes
-                </button>
             `;
         }
-        function saveEditedResponse(button) {
-            const newText = button.parentElement.querySelector('textarea').value;
             const bubble = button.closest('.ai-bubble');
-            const responseDiv = button.parentElement;
-            responseDiv.innerHTML = `<p>${newText}</p>`;
-            // Update the training data with edited response
-            const context = nlp.determineContext(newText);
-            trainingData.customResponses[context] = newText;
-            nlp.saveToLocalStorage();
         }
         function handleTrainingKeyPress(e) {

+d mm<!DOCTYPE html>
 <html lang="en">
 <head>
     <meta charset="UTF-8">
         // Initialize Natural Language Processing
         const nlp = {
             processInput: function(text) {
+                // Enhanced NLP processing
                 text = text.toLowerCase().trim();
+                // Tokenize and clean input
+                const tokens = text
+                    .replace(/[^\w\s]/g, '')
+                    .split(/\s+/)
+                    .filter(token => token.length > 2);
+                // Context detection with weights
+                const contextScores = {
+                    business: ['work', 'job', 'meeting', 'service', 'price', 'appointment', 'business', 'company']
+                        .filter(word => text.includes(word)).length,
+                    personal: ['family', 'friend', 'mom', 'dad', 'home', 'personal']
+                        .filter(word => text.includes(word)).length,
+                    spam: ['spam', 'block', 'unwanted', 'telemarketer', 'sales', 'offer']
+                        .filter(word => text.includes(word)).length * 2, // Higher weight
+                    question: ['what', 'when', 'where', 'how', 'why', 'can you', 'would you', '?']
+                        .filter(word => text.includes(word)).length
                 };
+                // Determine primary context
+                let primaryContext = 'general';
+                let maxScore = 0;
+                for (const [context, score] of Object.entries(contextScores)) {
+                    if (score > maxScore) {
+                        maxScore = score;
+                        primaryContext = context;
+                    }
+                }
+                return {
+                    text,
+                    tokens,
+                    context: primaryContext,
+                    isQuestion: contextScores.question > 0
+                };
             },
             learnResponse: function(inputText, preferredResponse) {
                 // Tokenize input and learn patterns
                 chatContainer.appendChild(userBubble);
                 // Process user input and generate AI response
+                setTimeout(() => {
                     let aiResponse;
+                    const isTeachingExample = /how should i respond|please reply with|respond with/i.test(userMessage);
                     if (isTeachingExample) {
+                        const teachingMatch = userMessage.match(/(how should i respond to|please reply to|respond to) (.*?) (with|by saying) (.*)/i);
+                        if (teachingMatch) {
+                            const question = teachingMatch[2];
+                            const answer = teachingMatch[4];
+                            nlp.learnResponse(question, answer);
+                            aiResponse = `
+                                <p>Got it! I've learned this response:</p>
+                                <div class="mt-2 bg-blue-50 dark:bg-blue-900 rounded-lg p-3">
+                                    <p><strong>When asked:</strong> ${question}</p>
+                                    <p><strong>I'll respond:</strong> ${answer}</p>
+                                </div>
+                                <p class="mt-2">I'll use this response pattern for similar questions.</p>
+                            `;
+                        } else {
+                            aiResponse = `
+                                <div class="ai-bubble mt-4 animate-fadeIn">
+                                    <p>I can learn how to respond! Try phrasing like:</p>
+                                    <div class="mt-2 bg-blue-50 dark:bg-blue-900 rounded-lg p-3">
+                                        <p>"How should I respond to questions about pricing?"</p>
+                                        <p>"Please reply to appointment requests with: 'Would you like morning or afternoon?'"</p>
+                                    </div>
+                                </div>
+                            `;
+                        }
                     } else {
                         const response = nlp.getBestResponse(userMessage);
                         aiResponse = `
+                            <p>Based on my training, here's how I would respond:</p>
                             <div class="mt-2 bg-blue-50 dark:bg-blue-900 rounded-lg p-3">
                                 <p>${response}</p>
                             </div>
+                            <p class="mt-2">Would you like to:</p>
                         `;
                     }
                     const aiBubble = document.createElement('div');
                     aiBubble.className = 'ai-bubble mt-4 animate-fadeIn';
+                    aiBubble.innerHTML = aiResponse;
+                    if (!aiResponse.includes('Try phrasing')) {
+                        aiBubble.innerHTML += `
+                            <div class="mt-3 flex gap-2">
+                                <button class="flex-1 py-2 bg-green-500 text-white rounded-lg hover:bg-green-600 transition"
+                                    onclick="acceptResponse(this)">
+                                    Accept <i class="fas fa-check ml-1"></i>
+                                </button>
+                                <button class="flex-1 py-2 bg-red-500 text-white rounded-lg hover:bg-red-600 transition"
+                                    onclick="editResponse(this)">
+                                    Edit <i class="fas fa-edit ml-1"></i>
+                                </button>
+                                <button class="px-3 py-2 bg-accent text-white rounded-lg hover:bg-blue-600 transition"
+                                    onclick="playResponse(this)">
+                                    <i class="fas fa-volume-up"></i>
+                                </button>
+                            </div>
+                        `;
+                    }
                     chatContainer.appendChild(aiBubble);
                     chatContainer.scrollTop = chatContainer.scrollHeight;
+                }, 500);
                 input.value = '';
             }
         }
         function acceptResponse(button) {
+            try {
+                const responseDiv = button.closest('.ai-bubble').querySelector('div.bg-blue-50');
+                if (!responseDiv) throw new Error('Response not found');
+                let responseText = '';
+                // Handle both single p and multi-line responses
+                const pTags = responseDiv.querySelectorAll('p');
+                if (pTags.length > 1) {
+                    responseText = Array.from(pTags)
+                        .filter(p => !p.innerHTML.includes('<strong>'))
+                        .map(p => p.textContent)
+                        .join('\n');
+                } else {
+                    responseText = pTags[0].textContent;
+                }
+                const context = nlp.determineContext(responseText);
+                // If it's a teaching example, find the question too
+                const strongTags = responseDiv.querySelectorAll('strong');
+                if (strongTags.length >= 2) {
+                    const question = strongTags[0].nextSibling.textContent.trim();
+                    const answer = strongTags[1].nextSibling.textContent.trim();
+                    nlp.learnResponse(question, answer);
+                } else {
+                    trainingData.customResponses[context] = responseText;
+                }
+                nlp.saveToLocalStorage();
+                button.innerHTML = '<i class="fas fa-check-circle"></i> Saved';
+                button.classList.remove('bg-green-500');
+                button.classList.add('bg-emerald-600');
+                button.disabled = true;
+                // Disable other buttons
+                const buttons = button.closest('.flex').querySelectorAll('button');
+                buttons.forEach(btn => {
+                    if (btn !== button) {
+                        btn.classList.add('opacity-50', 'cursor-not-allowed');
+                        btn.disabled = true;
+                    }
+                });
+            } catch (error) {
+                console.error('Error accepting response:', error);
+                alert('There was an error saving this response. Please try again.');
+            }
         }
         function editResponse(button) {
             const bubble = button.closest('.ai-bubble');
             const responseDiv = bubble.querySelector('div.bg-blue-50');
+            const pTags = responseDiv.querySelectorAll('p');
+            let currentText = '';
+            if (pTags.length > 1) {
+                // For teaching examples, combine response
+                currentText = Array.from(pTags)
+                    .filter(p => !p.innerHTML.includes('<strong>'))
+                    .map(p => p.textContent)
+                    .join('\n\n');
+            } else {
+                currentText = pTags[0].textContent;
+            }
             responseDiv.innerHTML = `
+                <textarea class="w-full p-2 rounded border border-gray-300 dark:border-gray-600 bg-white dark:bg-gray-700"
+                    rows="4">${currentText}</textarea>
+                <div class="mt-2 flex justify-end gap-2">
+                    <button onclick="cancelEdit(this)"
+                        class="px-4 py-1 bg-gray-300 dark:bg-gray-600 text-gray-800 dark:text-gray-200 rounded">
+                        Cancel
+                    </button>
+                    <button onclick="saveEditedResponse(this)"
+                        class="px-4 py-1 bg-accent text-white rounded hover:bg-blue-600 transition">
+                        Save Changes
+                    </button>
+                </div>
             `;
         }
+        function cancelEdit(button) {
             const bubble = button.closest('.ai-bubble');
+            const responseDiv = button.closest('.bg-blue-50');
+            const originalText = responseDiv.querySelector('textarea').value;
+            // Re-create the original response display
+            if (originalText.includes('\n\n')) {
+                responseDiv.innerHTML = originalText.split('\n\n')
+                    .map(text => `<p>${text}</p>`)
+                    .join('');
+            } else {
+                responseDiv.innerHTML = `<p>${originalText}</p>`;
+            }
+        }
+        function saveEditedResponse(button) {
+            try {
+                const newText = button.closest('.bg-blue-50').querySelector('textarea').value;
+                const bubble = button.closest('.ai-bubble');
+                const responseDiv = button.closest('.bg-blue-50');
+                // Determine if this was a teaching example
+                const wasTeachingExample = bubble.innerHTML.includes('<strong>When asked:</strong>');
+                if (wasTeachingExample) {
+                    // Parse the edited teaching example
+                    const lines = newText.split('\n');
+                    if (lines.length >= 2) {
+                        const question = lines[0].replace('When asked:', '').trim();
+                        const answer = lines[1].replace('I\'ll respond:', '').trim();
+                        nlp.learnResponse(question, answer);
+                    }
+                } else {
+                    // Update regular response
+                    const context = nlp.determineContext(newText);
+                    trainingData.customResponses[context] = newText;
+                }
+                nlp.saveToLocalStorage();
+                // Update display
+                if (newText.includes('\n')) {
+                    responseDiv.innerHTML = newText.split('\n')
+                        .map(text => `<p>${text}</p>`)
+                        .join('');
+                } else {
+                    responseDiv.innerHTML = `<p>${newText}</p>`;
+                }
+                // Reset action buttons
+                const actionDiv = document.createElement('div');
+                actionDiv.className = 'mt-3 flex gap-2';
+                actionDiv.innerHTML = `
+                    <button class="flex-1 py-2 bg-green-500 text-white rounded-lg hover:bg-green-600 transition"
+                        onclick="acceptResponse(this)">
+                        Accept <i class="fas fa-check ml-1"></i>
+                    </button>
+                    <button class="flex-1 py-2 bg-red-500 text-white rounded-lg hover:bg-red-600 transition"
+                        onclick="editResponse(this)">
+                        Edit <i class="fas fa-edit ml-1"></i>
+                    </button>
+                    <button class="px-3 py-2 bg-accent text-white rounded-lg hover:bg-blue-600 transition"
+                        onclick="playResponse(this)">
+                        <i class="fas fa-volume-up"></i>
+                    </button>
+                `;
+                responseDiv.insertAdjacentElement('afterend', actionDiv);
+            } catch (error) {
+                console.error('Error saving edits:', error);
+                alert('There was an error saving your changes. Please try again.');
+            }
+        }
+        function playResponse(button) {
+            try {
+                const responseDiv = button.closest('.ai-bubble').querySelector('div.bg-blue-50');
+                let responseText = '';
+                if (responseDiv.querySelector('strong')) {
+                    // For teaching examples
+                    const pTags = responseDiv.querySelectorAll('p');
+                    responseText = Array.from(pTags)
+                        .filter(p => !p.innerHTML.includes('<strong>'))
+                        .map(p => p.textContent)
+                        .join(' ');
+                } else {
+                    // For regular responses
+                    responseText = responseDiv.textContent;
+                }
+                // Simulate voice playback
+                button.innerHTML = '<i class="fas fa-spinner fa-spin"></i>';
+                button.disabled = true;
+                setTimeout(() => {
+                    button.innerHTML = '<i class="fas fa-volume-up"></i>';
+                    button.disabled = false;
+                    console.log('Would play:', responseText);
+                    // In a real app: voiceProcessor.speak(responseText).play();
+                    // Show visual feedback
+                    const bubble = button.closest('.ai-bubble');
+                    bubble.classList.add('ring-2', 'ring-accent');
+                    setTimeout(() => {
+                        bubble.classList.remove('ring-2', 'ring-accent');
+                    }, 1000);
+                }, 1500);
+            } catch (error) {
+                console.error('Error playing response:', error);
+                button.innerHTML = '<i class="fas fa-volume-up"></i>';
+                button.disabled = false;
+            }
         }
         function handleTrainingKeyPress(e) {

prompts.txt CHANGED Viewed

@@ -1,3 +1,5 @@
 Make voice humanistic . Add rvc technology and okada tts
 Please make the training work. Currently doesn’t . Add intelligence and smart learning. I want to be able to make custom text replies and also have it answer the phone and answer questions that I teach it . Have it learn diction. Make everything work and insure that this can and is used whenever someone callls my phone number 5622289429
-I own a car detailing business. Teach ai about it

 Make voice humanistic . Add rvc technology and okada tts
 Please make the training work. Currently doesn’t . Add intelligence and smart learning. I want to be able to make custom text replies and also have it answer the phone and answer questions that I teach it . Have it learn diction. Make everything work and insure that this can and is used whenever someone callls my phone number 5622289429
+I own a car detailing business. Teach ai about it
+Buttons still don’t work. I still can’t train. Fix make everything functional
+Buttons still don’t work. I still can’t train. Fix make everything functional