Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


  2459→            }
  2460→
  2461→            $proxyResult = json_decode($proxyResponse, true);
  2462→            if (!$proxyResult || !$proxyResult['success']) {
  2463→                jsonError('AI proxy error: ' . ($proxyResult['error'] ?? 'Unknown error'));
  2464→            }
  2465→
  2466→            // Extract answer from proxy response
  2467→            // Proxy returns: {"success":true,"responses":{"openai_response":{"response":"...","model":"..."}}}
  2468→            $answer = '';
  2469→            $usedModel = $chatModel;
  2470→            $responses = $proxyResult['responses'] ?? [];
  2471→            if (!empty($responses)) {
  2472→                $firstResponse = reset($responses);
  2473→                $answer = $firstResponse['response'] ?? $firstResponse['content'] ?? '';
  2474→                $usedModel = $firstResponse['model'] ?? $chatModel;
  2475→            }
  2476→            if (!$answer) {
  2477→                // Fallback: try top-level content
  2478→                $answer = $proxyResult['content'] ?? $proxyResult['response'] ?? '';
  2479→            }
  2480→            if (!$answer) {
  2481→                jsonError('AI proxy returned empty response. Raw: ' . substr($proxyResponse, 0, 200));
  2482→            }
  2483→
  2484→            jsonResponse([
  2485→                'success' => true,
  2486→                'answer'  => $answer,
  2487→                'model'   => $usedModel,
  2488→                'provider'=> $chatProvider,
  2489→                'via'     => 'proxy'
  2490→            ]);
  2491→            break;
  2492→
  2493→
  2494→
  2495→        // ==========================================
  2496→        case 'generate_reply':
  2497→            if ($_SERVER['REQUEST_METHOD'] !== 'POST') {
  2498→                jsonError('POST required', 405);
  2499→            }
  2500→
  2501→            // Handle JSON or form data
  2502→            $contentType = $_SERVER['CONTENT_TYPE'] ?? '';
  2503→            if (strpos($contentType, 'application/json') !== false) {
  2504→                $jsonData = json_decode(file_get_contents('php://input'), true);
  2505→                $threadId = $jsonData['thread_id'] ?? '';
  2506→                $tone = $jsonData['tone'] ?? 'professional';
  2507→                $intent = $jsonData['intent'] ?? '';
  2508→                $customInstructions = $jsonData['custom_instructions'] ?? '';
  2509→                $aiModel = $jsonData['ai_model'] ?? 'openai';
  2510→            } else {
  2511→                $threadId = $_POST['thread_id'] ?? '';
  2512→                $tone = $_POST['tone'] ?? 'professional';
  2513→                $intent = $_POST['intent'] ?? '';
  2514→                $customInstructions = $_POST['custom_instructions'] ?? '';
  2515→                $aiModel = $_POST['ai_model'] ?? 'openai';
  2516→            }
  2517→
  2518→            if (!$threadId) jsonError('thread_id required');
  2519→
  2520→            // Auto-resolve long URL thread ID to short hex ID from cache
  2521→            $threadId = resolveThreadId($threadId);
  2522→
  2523→            // Get thread context from MongoDB
  2524→            $mongo = \EmailIntelligence\MongoDatabase::getInstance();
  2525→            $emails = $mongo->findAll('emails', ['thread_id' => $threadId], [
  2526→                'sort' => ['date' => 1]
  2527→            ]);
  2528→
  2529→            if (empty($emails)) {
  2530→                jsonError('Thread not found');
  2531→            }
  2532→
  2533→            // Get contact ID from the first email
  2534→            $contactId = $emails[0]['contact_id'] ?? null;
  2535→
  2536→            // Get contact profile if available
  2537→            $profile = null;
  2538→            $profileStr = '';
  2539→            if ($contactId) {
  2540→                $profile = $mongo->findOne('contact_profiles', ['contact_id' => (int)$contactId]);
  2541→                if ($profile) {
  2542→                    $profileStr = "\n\nCLIENT PROFILE:
  2543→- Communication Style: " . ($profile['communication_style'] ?? 'Unknown') . "
  2544→- Honesty Score: " . ($profile['honesty_score'] ?? 'N/A') . "%
  2545→- Best Approach: " . implode(', ', $profile['best_approach'] ?? []);
  2546→                }
  2547→            }
  2548→
  2549→            // Build thread summary from MongoDB emails
  2550→            $threadSummary = "";
  2551→            foreach ($emails as $email) {
  2552→                $direction = ($email['direction'] ?? '') === 'inbound' ? 'FROM THEM' : 'FROM US';
  2553→                $body = $email['body_text'] ?? $email['snippet'] ?? '';
  2554→                $threadSummary .= "{$direction} ({$email['date']}): " . substr($body, 0, 500) . "\n\n";
  2555→            }
  2556→
  2557→            // ========================================
  2558→            // ChromaDB: Get relevant context for reply

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


2682-  }
2683-
2684-  /**
2685-   * Load Ask AI About Contact tab
2686-   */
2687:  async function loadAskContactAI() {
2688-    askContactAIContent.innerHTML = '
Loading...
';
2689-
2690-    // Try to ensure contact is detected
2691-    await ensureContactDetected();
2692-

Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


Bash

grep -n "ai-quick-prompts\|ai-mode-btn" /var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php

Find quick prompts and mode buttons in HTML

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


565:                    <button class="ai-mode-btn active" data-mode="general" onclick="setAiChatMode('general',this)" style="background:#6366f1; color:#fff; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">💬 General</button>
566:                    <button class="ai-mode-btn" data-mode="thread" onclick="setAiChatMode('thread',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">📧 Thread</button>
567:                    <button class="ai-mode-btn" data-mode="contact" onclick="setAiChatMode('contact',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">👤 Contact</button>
568:                    <button class="ai-mode-btn" data-mode="quote" onclick="setAiChatMode('quote',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">💰 Quote</button>
569:                    <button class="ai-mode-btn" data-mode="reply" onclick="setAiChatMode('reply',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">✍ Reply</button>
583:

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


156-  }
157-
158-  /**
159-   * Load AI selection from Chrome storage
160-   */
161:  async function loadAISelection() {
162-    try {
163-      const storage = await chrome.storage.local.get(['aiProvider', 'aiModel']);
164-      if (storage.aiProvider && PROVIDER_MODELS[storage.aiProvider]) {
165-        selectedProvider = storage.aiProvider;
166-        selectedModel = storage.aiModel || PROVIDER_MODELS[storage.aiProvider][0].id;
--
172-  }
173-
174-  /**
175-   * Save AI selection to Chrome storage
176-   */
177:  async function saveAISelection() {
178-    try {
179-      await chrome.storage.local.set({ aiProvider: selectedProvider, aiModel: selectedModel });
180-      console.log("[Email Intelligence] Saved AI selection:", selectedProvider, selectedModel);
181-    } catch (e) {
182-      console.log("[Email Intelligence] Could not save AI selection:", e);
--
208-  // ==========================================
209-
210-  /**
211-   * Load conversation history from Chrome storage
212-   */
213:  async function loadAIConversationHistory() {
214-    try {
215-      const storage = await chrome.storage.local.get('aiConversationHistory');
216-      if (storage.aiConversationHistory && Array.isArray(storage.aiConversationHistory)) {
217-        aiConversationHistory = storage.aiConversationHistory;
218-        console.log("[Email Intelligence] Loaded", aiConversationHistory.length, "conversation history items");
--
223-  }
224-
225-  /**
226-   * Save conversation history to Chrome storage
227-   */
228:  async function saveAIConversationHistory() {
229-    try {
230-      await chrome.storage.local.set({ aiConversationHistory });
231-      console.log("[Email Intelligence] Saved conversation history:", aiConversationHistory.length, "items");
232-    } catch (e) {
233-      console.log("[Email Intelligence] Could not save conversation history:", e);
--
235-  }
236-
237-  /**
238-   * Add a Q&A exchange to conversation history
239-   */
240:  function addToAIConversation(question, answer, provider, model) {
241-    aiConversationHistory.push({
242-      timestamp: new Date().toISOString(),
243-      question: question,
244-      answer: answer,
245-      provider: provider,
--
274-  }
275-
276-  /**
277-   * Clear conversation history
278-   */
279:  function clearAIConversationHistory() {
280-    aiConversationHistory = [];
281-    saveAIConversationHistory();
282-    updateConversationHistoryDisplay();
283-  }
284-
--
335-  // ==========================================
336-
337-  /**
338-   * Load saved context from Chrome storage
339-   */
340:  async function loadSavedAIContext() {
341-    try {
342-      const storage = await chrome.storage.local.get('savedAIContext');
343-      if (storage.savedAIContext && Array.isArray(storage.savedAIContext)) {
344-        savedAIContext = storage.savedAIContext;
345-        console.log("[Email Intelligence] Loaded", savedAIContext.length, "saved context items");
--
350-  }
351-
352-  /**
353-   * Save context to Chrome storage
354-   */
355:  async function saveSavedAIContext() {
356-    try {
357-      await chrome.storage.local.set({ savedAIContext });
358-      console.log("[Email Intelligence] Saved context:", savedAIContext.length, "items");
359-    } catch (e) {
360-      console.log("[Email Intelligence] Could not save context:", e);
--
396-  }
397-
398-  /**
399-   * Clear all saved context
400-   */
401:  function clearSavedAIContext() {
402-    savedAIContext = [];
403-    saveSavedAIContext();
404-    updateSavedContextDisplay();
405-  }
406-
--
539-      setTimeout(() => toast.remove(), 300);
540-    }, duration);
541-  }
542-
543-  // Tab references
544:  let insightsTab, contactTab, patternsTab, aiTab, replyTab;
545-  let insightsContent, contactContent, patternsContent, aiContent, replyContent, logsContent, businessContent, protectContent, askContactAIContent;
546-
547-  /**
548-   * Create floating show button (always visible in Gmail)
549-   */
--
2680-
2681-    protectContent.innerHTML = html;
2682-  }
2683-
2684-  /**
2685:   * Load Ask AI About Contact tab
2686-   */
2687:  async function loadAskContactAI() {
2688-    askContactAIContent.innerHTML = '
Loading...
';
2689-
2690-    // Try to ensure contact is detected
2691-    await ensureContactDetected();
2692-
--
2736-        contextSummary.total_emails = contact.email_count || 0;
2737-        contextSummary.total_threads = contact.thread_count || 0;
2738-        contextSummary.total_quotes = contact.quote_count || 0;
2739-      }
2740-    } catch (e) {
2741:      console.log("[Email Intelligence] Could not load contact info for Ask AI tab");
2742-    }
2743-
2744-    // Build participants options
2745-    const participantOptions = participants.map(p =>
2746-      `<option value="${p.email}" ${p.email === currentContactEmail ? 'selected' : ''}>${escapeHtml(p.name ? `${p.name} (${p.email})` : p.email)}</option>`
--
3108-  }
3109-
3110-  /**
3111-   * Ask AI a question about the contact
3112-   */
3113:  async function askContactAIQuestion(question) {
3114-    const responseContainer = shadowRoot.getElementById('ask-contact-response-container');
3115-    const askBtn = shadowRoot.getElementById('ask-contact-ai-btn');
3116-
3117-    if (!currentContactId) {
3118-      responseContainer.innerHTML = `
--
3313-  }
3314-
3315-  /**
3316-   * Load AI chat with thread context
3317-   */
3318:  async function loadAIChat() {
3319:    aiContent.innerHTML = '
Loading...
';
3320-
3321-    // Resolve thread ID first if it's a URL-style ID (FMfcgz...)
3322-    if (currentThreadId && currentMessageId && !isRealGmailThreadId(currentThreadId)) {
3323-      await resolveRealThreadId();
3324-    }
--
3339-    }
3340-
3341-    const participantNames = participants.map(p => p.name || p.email.split('@')[0]).join(', ');
3342-    const hasContext = currentThreadId && participants.length > 0;
3343-
3344:    aiContent.innerHTML = `
3345-      ${hasContext ? `
3346-

3347-
ASKING ABOUT

3348-
${escapeHtml(threadSubject)}

3349-
With: ${escapeHtml(participantNames)}

--
3448-  }
3449-
3450-  /**
3451-   * Ask AI a question
3452-   */
3453:  async function askAI(question) {
3454-    const chatHistory = shadowRoot.getElementById('ai-chat-history');
3455-
3456-    // Add question
3457-    const questionDiv = document.createElement('div');
3458-    questionDiv.style.cssText = "background: #667eea; color: white; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px;";
--
3902-  }
3903-
3904-  /**
3905-   * Load AI-generated reply suggestions
3906-   */
3907:  async function loadAISuggestions() {
3908-    const container = shadowRoot.getElementById('ai-suggestions-container');
3909-    const btn = shadowRoot.getElementById('load-suggestions-btn');
3910-
3911-    if (!currentThreadId) {
3912-      container.innerHTML = 'No thread selected';
--
4687-  }
4688-
4689-  /**
4690-   * Format markdown-like text to HTML for display
4691-   */
4692:  function formatAIResponse(text) {
4693-    if (!text) return '';
4694-
4695-    // Escape HTML first
4696-    let html = escapeHtml(text);
4697-

Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


grep -n "case 'thread':" /var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php

Find thread API endpoint

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


417:        case 'thread':

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


   417→        case 'thread':
   418→            $threadId = $_GET['thread_id'] ?? '';
   419→            if (!$threadId) jsonError('Thread ID required');
   420→
   421→            // Auto-resolve long URL thread ID to short hex ID from cache
   422→            $threadId = resolveThreadId($threadId);
   423→
   424→            // Use QueryAdapter for automatic MySQL/MongoDB routing
   425→            $adapter = QueryAdapter::getInstance();
   426→            $threadData = $adapter->getThreadDetails($threadId);
   427→
   428→            if (empty($threadData['emails'])) {
   429→                jsonError('Thread not found', 404);
   430→            }
   431→
   432→            $emails = $threadData['emails'];
   433→            $analysis = $threadData['analysis'];
   434→
   435→            // Parse JSON fields in analysis (for MySQL string storage)
   436→            if ($analysis && isset($analysis['raw_analysis']) && is_string($analysis['raw_analysis'])) {
   437→                // Strip markdown code block markers if present (```json ... ```)
   438→                $rawStr = trim($analysis['raw_analysis']);
   439→                if (preg_match('/^```(?:json)?\s*([\s\S]*?)\s*```$/s', $rawStr, $matches)) {
   440→                    $rawStr = $matches[1];
   441→                }
   442→                $analysis['raw_analysis'] = json_decode($rawStr, true);
   443→            }
   444→            if ($analysis && isset($analysis['key_points']) && is_string($analysis['key_points'])) {
   445→                $analysis['key_points'] = json_decode($analysis['key_points'], true);
   446→            }
   447→
   448→            // Ensure raw_analysis is an array for safe access
   449→            if ($analysis && !isset($analysis['raw_analysis'])) {
   450→                $analysis['raw_analysis'] = [];
   451→            }
   452→
   453→            // Extract participants_analysis from raw_analysis for easier access
   454→            $participantsAnalysis = [];
   455→            if ($analysis && isset($analysis['raw_analysis']['participants_analysis'])) {
   456→                $participantsAnalysis = $analysis['raw_analysis']['participants_analysis'];
   457→            }
   458→
   459→            // Build response with extracted analysis fields
   460→            $rawAnalysis = $analysis['raw_analysis'] ?? [];
   461→
   462→            // Determine true analyzed state: trust the DB flag, but also consider
   463→            // that if summary + raw_analysis exist, the AI ran successfully even if
   464→            // is_analyzed=0 (can happen when post-analysis participant storage crashed).
   465→            $dbIsAnalyzed = $analysis ? (($analysis['is_analyzed'] ?? 0) == 1) : false;
   466→            $hasAnalysisData = $analysis && !empty($analysis['summary']) && !empty($rawAnalysis);
   467→            $isAnalyzed = $dbIsAnalyzed || $hasAnalysisData;
   468→
   469→            // Auto-repair: if data exists but flag is wrong, fix it in the DB
   470→            if ($hasAnalysisData && !$dbIsAnalyzed) {
   471→                try {
   472→                    $db->execute(
   473→                        "UPDATE thread_analysis SET is_analyzed = 1, needs_reanalysis = 0 WHERE thread_id = ?",
   474→                        [$threadId]
   475→                    );
   476→                } catch (Exception $e) {
   477→                    // Non-fatal - just log it
   478→                    error_log("Failed to auto-repair is_analyzed for thread {$threadId}: " . $e->getMessage());
   479→                }
   480→            }
   481→
   482→            $response = [
   483→                'thread_id' => $threadId,
   484→                'emails' => $emails,
   485→                'email_count' => count($emails),
   486→                'analysis' => $analysis ? [
   487→                    'summary' => $analysis['summary'] ?? $rawAnalysis['thread_summary'] ?? null,
   488→                    'trust_score' => $rawAnalysis['deception_indicators']['trust_score'] ?? 0.5,
   489→                    'deception_score' => $analysis['deception_score'] ?? $rawAnalysis['deception_indicators']['deception_score'] ?? 0,
   490→                    'risk_level' => $rawAnalysis['recommendations']['overall_risk_level'] ?? 'unknown',
   491→                    'key_points' => $analysis['key_points'] ?? $rawAnalysis['key_points'] ?? [],
   492→                    'warnings' => $rawAnalysis['deception_indicators']['red_flags'] ?? [],
   493→                    'participants_analysis' => $participantsAnalysis,
   494→                    'sentiment' => $rawAnalysis['sentiment_analysis'] ?? null,
   495→                    'negotiation' => $rawAnalysis['negotiation_analysis'] ?? null,
   496→                    'action_items' => $rawAnalysis['action_items'] ?? [],
   497→                    'recommendations' => $rawAnalysis['recommendations'] ?? null,
   498→                    // New fields for unified AI response
   499→                    'reply_suggestions' => $rawAnalysis['reply_suggestions'] ?? [],
   500→                    'business_opportunities' => $rawAnalysis['business_opportunities'] ?? null,
   501→                    'protective_analysis' => $rawAnalysis['protective_analysis'] ?? null,
   502→                    'raw' => $rawAnalysis
   503→                ] : null,
   504→                'status' => [
   505→                    'is_analyzed' => $isAnalyzed,
   506→                    'needs_reanalysis' => $analysis ? (($analysis['needs_reanalysis'] ?? 0) == 1) : false
   507→                ]
   508→            ];
   509→
   510→            jsonResponse($response);
   511→            break;
   512→
   513→        // ==========================================
   514→        // Thread Participants - Get all contacts in a thread
   515→        // ==========================================
   516→        case 'thread_participants':

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


3315→  /**
  3316→   * Load AI chat with thread context
  3317→   */
  3318→  async function loadAIChat() {
  3319→    aiContent.innerHTML = '
Loading...
';
  3320→
  3321→    // Resolve thread ID first if it's a URL-style ID (FMfcgz...)
  3322→    if (currentThreadId && currentMessageId && !isRealGmailThreadId(currentThreadId)) {
  3323→      await resolveRealThreadId();
  3324→    }
  3325→
  3326→    // Fetch thread participants for context
  3327→    let participants = [];
  3328→    let threadSubject = currentSubject || '';
  3329→    if (currentThreadId) {
  3330→      try {
  3331→        const resp = await sendMessage('getThreadParticipants', {thread_id: currentThreadId});
  3332→        if (resp.success && resp.data) {
  3333→          participants = resp.data.participants?.filter(p => p.participant_type === 'external') || [];
  3334→          threadSubject = resp.data.subject || threadSubject;
  3335→        }
  3336→      } catch (e) {
  3337→        console.log("[Email Intelligence] Could not load participants for AI context");
  3338→      }
  3339→    }
  3340→
  3341→    const participantNames = participants.map(p => p.name || p.email.split('@')[0]).join(', ');
  3342→    const hasContext = currentThreadId && participants.length > 0;
  3343→
  3344→    aiContent.innerHTML = `
  3345→      ${hasContext ? `
  3346→

  3347→
ASKING ABOUT

  3348→
${escapeHtml(threadSubject)}

  3349→
With: ${escapeHtml(participantNames)}

  3350→

  3351→      ` : ''}
  3352→
  3353→

  3354→
  3355→

  3356→
Quick Questions:

  3357→

  3358→          <button class="quick-question-btn" data-question="Summarize this email thread in bullet points" style="
  3359→            background: white;
  3360→            border: 1px solid #e0e0e0;
  3361→            padding: 6px 12px;
  3362→            border-radius: 16px;
  3363→            cursor: pointer;
  3364→            font-size: 11px;
  3365→            color: #667eea;
  3366→          ">Summarize thread</button>
  3367→          <button class="quick-question-btn" data-question="What are the key action items and next steps?" style="
  3368→            background: white;
  3369→            border: 1px solid #e0e0e0;
  3370→            padding: 6px 12px;
  3371→            border-radius: 16px;
  3372→            cursor: pointer;
  3373→            font-size: 11px;
  3374→            color: #667eea;
  3375→          ">Action items?</button>
  3376→          <button class="quick-question-btn" data-question="Are there any red flags or concerns in this conversation?" style="
  3377→            background: white;
  3378→            border: 1px solid #e0e0e0;
  3379→            padding: 6px 12px;
  3380→            border-radius: 16px;
  3381→            cursor: pointer;
  3382→            font-size: 11px;
  3383→            color: #667eea;
  3384→          ">Red flags?</button>
  3385→          <button class="quick-question-btn" data-question="What is the overall sentiment and tone of this conversation?" style="
  3386→            background: white;
  3387→            border: 1px solid #e0e0e0;
  3388→            padding: 6px 12px;
  3389→            border-radius: 16px;
  3390→            cursor: pointer;
  3391→            font-size: 11px;
  3392→            color: #667eea;
  3393→          ">Sentiment?</button>
  3394→          <button class="quick-question-btn" data-question="What questions are still unanswered in this thread?" style="
  3395→            background: white;
  3396→            border: 1px solid #e0e0e0;
  3397→            padding: 6px 12px;
  3398→            border-radius: 16px;
  3399→            cursor: pointer;
  3400→            font-size: 11px;
  3401→            color: #667eea;
  3402→          ">Unanswered?</button>
  3403→

  3404→

  3405→
  3406→

  3407→        <input type="text" id="ai-question-input" placeholder="Ask about this conversation..." style="
  3408→          flex: 1;
  3409→          padding: 10px;
  3410→          border: 1px solid #e0e0e0;
  3411→          border-radius: 6px;
  3412→          font-size: 13px;
  3413→        ">
  3414→        <button id="ai-send-btn" style="
  3415→          background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
  3416→          color: white;
  3417→          border: none;
  3418→          padding: 10px 16px;
  3419→          border-radius: 6px;
  3420→          cursor: pointer;
  3421→          font-weight: 600;
  3422→          font-size: 13px;
  3423→        ">Ask</button>
  3424→

  3425→    `;
  3426→
  3427→    // Event listeners
  3428→    shadowRoot.querySelectorAll('.quick-question-btn').forEach(btn => {
  3429→      btn.addEventListener('click', () => askAI(btn.dataset.question));
  3430→    });
  3431→
  3432→    const input = shadowRoot.getElementById('ai-question-input');
  3433→    const sendBtn = shadowRoot.getElementById('ai-send-btn');
  3434→
  3435→    sendBtn.addEventListener('click', () => {
  3436→      const question = input.value.trim();
  3437→      if (question) {
  3438→        askAI(question);
  3439→        input.value = '';
  3440→      }
  3441→    });
  3442→
  3443→    input.addEventListener('keypress', (e) => {
  3444→      if (e.key === 'Enter') {
  3445→        sendBtn.click();
  3446→      }
  3447→    });
  3448→  }
  3449→
  3450→  /**
  3451→   * Ask AI a question
  3452→   */
  3453→  async function askAI(question) {
  3454→    const chatHistory = shadowRoot.getElementById('ai-chat-history');
  3455→
  3456→    // Add question
  3457→    const questionDiv = document.createElement('div');
  3458→    questionDiv.style.cssText = "background: #667eea; color: white; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px;";
  3459→    questionDiv.textContent = question;
  3460→    chatHistory.appendChild(questionDiv);
  3461→
  3462→    // Add loading
  3463→    const loadingDiv = document.createElement('div');
  3464→    loadingDiv.style.cssText = "background: #f9fafb; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px; color: #999;";
  3465→    loadingDiv.textContent = "Thinking...";
  3466→    chatHistory.appendChild(loadingDiv);
  3467→    chatHistory.scrollTop = chatHistory.scrollHeight;
  3468→
  3469→    try {
  3470→      // Resolve thread ID first if it's a URL-style ID (FMfcgz...)
  3471→      if (currentThreadId && currentMessageId && !isRealGmailThreadId(currentThreadId)) {
  3472→        await resolveRealThreadId();
  3473→      }
  3474→
  3475→      const response = await sendMessage('askAI', {
  3476→        question: question,
  3477→        thread_id: currentThreadId,
  3478→        contact_id: currentContactId
  3479→      });
  3480→
  3481→      loadingDiv.remove();
  3482→
  3483→      if (response.success && response.data.answer) {
  3484→        const answerDiv = document.createElement('div');
  3485→        answerDiv.style.cssText = "background: #f9fafb; border: 1px solid #e0e0e0; padding: 12px; border-radius: 8px; margin-bottom: 12px; font-size: 12px; line-height: 1.6; color: #333;";
  3486→        // Use formatted HTML instead of plain text
  3487→        answerDiv.innerHTML = formatAIResponse(response.data.answer);
  3488→        chatHistory.appendChild(answerDiv);
  3489→        chatHistory.scrollTop = chatHistory.scrollHeight;
  3490→      } else {
  3491→        const errorDiv = document.createElement('div');
  3492→        errorDiv.style.cssText = "background: #fef2f2; border: 1px solid #fecaca; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px; color: #dc2626;";
  3493→        errorDiv.textContent = "Sorry, I couldn't process that question.";
  3494→        chatHistory.appendChild(errorDiv);
  3495→      }
  3496→    } catch (error) {
  3497→      const errorDiv = document.createElement('div');
  3498→      errorDiv.style.cssText = "background: #fef2f2; border: 1px solid #fecaca; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px; color: #dc2626;";
  3499→      errorDiv.textContent = `Error: ${error.message}`;
  3500→      chatHistory.appendChild(errorDiv);
  3501→    }
  3502→  }
  3503→
  3504→  /**
  3505→   * Load reply options with thread context
  3506→   */
  3507→  async function loadReplyOptions() {
  3508→    if (!currentThreadId) {
  3509→      replyContent.innerHTML = '
No thread selected
';
  3510→      return;
  3511→    }
  3512→
  3513→    replyContent.innerHTML = '
Loading...
';
  3514→

Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


find /var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/ -type f | sort

Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


grep -n "apiapi_codex51\|proxyUrl\|askClaude\|ThreadAnalyzer\|resolveThreadId" /var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php | head -20

Find AI provider integration details

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


159:use EmailIntelligence\ThreadAnalyzer;
241:function resolveThreadId(?string $threadId): ?string {
422:            $threadId = resolveThreadId($threadId);
522:            $threadId = resolveThreadId($threadId);
602:                $threadId = resolveThreadId($threadId);
918:            $analyzer = new ThreadAnalyzer();
994:            $threadId = resolveThreadId($threadId);
996:            $analyzer = new ThreadAnalyzer();
1716:            $analyzer = new ThreadAnalyzer();
2140:            $threadId = resolveThreadId($threadId);
2244:                $threadId = resolveThreadId($threadId);
2294:            $analyzer = new ThreadAnalyzer();
2297:                $response = $analyzer->askClaude($prompt);
2323:            if ($chatThreadId) $chatThreadId = resolveThreadId($chatThreadId);
2426:            $proxyUrl = 'https://mssql.danmarcrm.com/dev1/extension2/aiapi/api_codex51/api/index.php';
2436:            $ch = curl_init($proxyUrl);
2449:                // Fallback to direct ThreadAnalyzer if proxy fails
2451:                    $analyzer = new ThreadAnalyzer($chatProvider === 'openai' ? 'openai' : 'claude', $chatModel);
2453:                    $answer = $analyzer->askClaude($fullPrompt);
2521:            $threadId = resolveThreadId($threadId);

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


See directory structure to understand the application layout

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


total 218176
drwxrwxrwx 21 root      root           4096 Feb 20 15:49 .
drwxrwxrwx 16 root      root           4096 Feb 19 23:27 ..
-rwxrwxrwx  1 root      root          53544 Dec 14 16:13 2025-12-14-this-session-is-being-continued-from-a-previous-co.txt
-rwxrwxrwx  1 root      root           8708 Dec 18 12:13 AI_ANALYSIS_IMPROVEMENTS.md
drwxrwxrwx  8 root      root           4096 Jan 15 12:05 aiapi
drwxrwxrwx  5 root      root           4096 Dec 17 00:58 backup_20251217_005857
drwxrwxrwx  3 root      root           4096 Dec 17 14:03 cache
drwxrwxrwx  3 root      root           4096 Dec 24 15:27 __changes
-rwxrwxrwx  1 root      root            386 Dec 29 09:20 check_schema.php
drwxr-xr-x  3 root      root           4096 Feb 20 15:49 chrome-extensionCopyMac20260220
drwxrwxrwx  5 root      root           4096 Dec 21 14:44 chrome-extensionTill20251221
drwxrwxrwx  2 root      root           4096 Dec 24 16:09 .claude
-rwxrwxrwx  1 root      root              0 Dec 14 16:11 CLAUDE.md
drwxrwxrwx  2 root      root           4096 Dec 17 20:18 cli
-rwxrwxrwx  1 root      root            486 Dec 17 01:02 composer.json
-rwxrwxrwx  1 root      root          56069 Dec 17 01:02 composer.lock
drwxrwxrwx  2 root      root           4096 Dec 21 01:28 config
-rwxrwxrwx  1 root      root       23457916 Dec 23 19:05 __daily_scraper.log
drwxrwxrwx  2 root      root           4096 Dec 15 23:57 database
-rwxrwxrwx  1 root      root        4107330 Dec 23 19:05 __ddbgHotelRun.log
-rwxrwxrwx  1 root      root      177487961 Dec 23 19:01 __ddbg_room_props.log
-rwxrwxrwx  1 root      root         411160 Dec 23 19:05 __ddbgServerLoadVals.log
-rwxrwxrwx  1 root      root        5307672 Feb 17 12:51 __ddbgSQ.log
-rwxrwxrwx  1 root      root           1326 Dec 29 09:20 delete_old_files.sh
drwxrwxrwx  2 root      root           4096 Dec 15 16:53 docs
-rwxr--r--  1 danbogdan danbogdan      6148 Jan 15 12:05 .DS_Store
drwxrwxrwx  4 root      root           4096 Dec 13 18:42 existingExtension
-rwxrwxrwx  1 root      root           3196 Dec 29 09:20 find_december_quote.php
-rwxrwxrwx  1 root      root           4352 Dec 29 09:20 find_similar_quotes.php
-rwxrwxrwx  1 root      root           1785 Dec 29 09:20 get_specific_email.php
-rwxrwxrwx  1 root      root           1174 Dec 29 09:20 get_tacpay_quote.php
-rwxrwxrwx  1 root      root           1395 Dec 17 12:26 .htaccess
-rwxrwxrwx  1 root      root        7826122 Dec 23 19:05 __load_balancing.log
drwxrwxrwx  3 root      root           4096 Feb  3 14:09 logs
drwxrwxrwx  3 root      root           4096 Dec 20 22:25 memory-service
-rwxrwxrwx  1 root      root        4421450 Dec 23 19:05 nohup.out
-rw-r--r--  1 root      root           3420 Feb 20 15:42 PROJECT_OVERVIEW.md
drwxrwxrwx  3 root      root           4096 Dec 24 15:58 public
drwxrwxrwx  4 root      root           4096 Dec  7 18:35 .qodo
-rwxrwxrwx  1 root      root          10732 Dec 12 18:21 README.md
drwxrwxrwx  2 root      root           4096 Dec 23 09:31 responses
-rwxrwxrwx  1 root      root           4587 Dec 29 09:20 search_chroma_finserv.php
-rwxrwxrwx  1 root      root           2686 Dec 29 09:20 search_email.php
-rwxrwxrwx  1 root      root           3119 Dec 29 09:20 search_heather_quote.php
-rwxrwxrwx  1 root      root           2853 Dec 29 09:20 search_pricing_quote.php
drwxrwxrwx  2 root      root           4096 Dec 24 16:18 src
-rwxrwxrwx  1 root      root           3599 Dec 29 09:20 sync_sql_database_emails.php
-rwxrwxrwx  1 root      root              0 Dec  7 18:36 test.php
drwxrwxrwx 13 root      root           4096 Dec 17 01:02 vendor

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


     1→/* Email Intelligence Panel Styles */
     2→
     3→:host {
     4→  all: initial;
     5→}
     6→
     7→* {
     8→  box-sizing: border-box;
     9→}
    10→
    11→/* Scrollbar styling */
    12→::-webkit-scrollbar {
    13→  width: 8px;
    14→}
    15→
    16→::-webkit-scrollbar-track {
    17→  background: #f1f1f1;
    18→}
    19→
    20→::-webkit-scrollbar-thumb {
    21→  background: #888;
    22→  border-radius: 4px;
    23→}
    24→
    25→::-webkit-scrollbar-thumb:hover {
    26→  background: #555;
    27→}
    28→
    29→/* Button hover effects */
    30→button {
    31→  transition: all 0.2s ease;
    32→}
    33→
    34→button:hover {
    35→  transform: translateY(-1px);
    36→  box-shadow: 0 2px 8px rgba(0,0,0,0.15);
    37→}
    38→
    39→button:active {
    40→  transform: translateY(0);
    41→}
    42→
    43→/* Tab animations */
    44→.intel-tab {
    45→  transition: all 0.2s ease;
    46→}
    47→
    48→.tab-content {
    49→  animation: fadeIn 0.3s ease;
    50→}
    51→
    52→@keyframes fadeIn {
    53→  from {
    54→    opacity: 0;
    55→    transform: translateY(10px);
    56→  }
    57→  to {
    58→    opacity: 1;
    59→    transform: translateY(0);
    60→  }
    61→}
    62→
    63→/* Loading spinner */
    64→@keyframes spin {
    65→  to {
    66→    transform: rotate(360deg);
    67→  }
    68→}
    69→
    70→.spinner {
    71→  width: 20px;
    72→  height: 20px;
    73→  border: 3px solid #f3f3f3;
    74→  border-top: 3px solid #667eea;
    75→  border-radius: 50%;
    76→  animation: spin 1s linear infinite;
    77→  display: inline-block;
    78→}
    79→
    80→/* Badge styles */
    81→.badge {
    82→  display: inline-block;
    83→  padding: 4px 8px;
    84→  border-radius: 12px;
    85→  font-size: 11px;
    86→  font-weight: 600;
    87→}
    88→
    89→.badge-success {
    90→  background: #dcfce7;
    91→  color: #15803d;
    92→}
    93→
    94→.badge-warning {
    95→  background: #fef3c7;
    96→  color: #92400e;
    97→}
    98→
    99→.badge-danger {
   100→  background: #fee2e2;
   101→  color: #991b1b;
   102→}
   103→
   104→.badge-info {
   105→  background: #dbeafe;
   106→  color: #1e40af;
   107→}
   108→
   109→/* Card styles */
   110→.card {
   111→  background: white;
   112→  border: 1px solid #e0e0e0;
   113→  border-radius: 8px;
   114→  padding: 12px;
   115→  margin-bottom: 12px;
   116→  box-shadow: 0 1px 3px rgba(0,0,0,0.05);
   117→}
   118→
   119→.card:hover {
   120→  box-shadow: 0 2px 6px rgba(0,0,0,0.1);
   121→}
   122→
   123→/* Alert styles */
   124→.alert {
   125→  padding: 12px;
   126→  border-radius: 6px;
   127→  margin-bottom: 12px;
   128→  border-left: 4px solid;
   129→}
   130→
   131→.alert-info {
   132→  background: #eff6ff;
   133→  border-color: #3b82f6;
   134→  color: #1e40af;
   135→}
   136→
   137→.alert-success {
   138→  background: #f0fdf4;
   139→  border-color: #22c55e;
   140→  color: #15803d;
   141→}
   142→
   143→.alert-warning {
   144→  background: #fef3c7;
   145→  border-color: #f59e0b;
   146→  color: #92400e;
   147→}
   148→
   149→.alert-danger {
   150→  background: #fee2e2;
   151→  border-color: #ef4444;
   152→  color: #991b1b;
   153→}
   154→
   155→/* Form inputs */
   156→input[type="text"],
   157→input[type="email"],
   158→textarea,
   159→select {
   160→  font-family: inherit;
   161→  outline: none;
   162→}
   163→
   164→input:focus,
   165→textarea:focus,
   166→select:focus {
   167→  border-color: #667eea;
   168→  box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1);
   169→}
   170→
   171→/* Utility classes */
   172→.text-center {
   173→  text-align: center;
   174→}
   175→
   176→.text-muted {
   177→  color: #999;
   178→}
   179→
   180→.mb-8 {
   181→  margin-bottom: 8px;
   182→}
   183→
   184→.mb-12 {
   185→  margin-bottom: 12px;
   186→}
   187→
   188→.mb-16 {
   189→  margin-bottom: 16px;
   190→}
   191→
   192→.p-12 {
   193→  padding: 12px;
   194→}
   195→
   196→.p-16 {
   197→  padding: 16px;
   198→}
   199→
   200→/* Responsive adjustments */
   201→@media (max-width: 1400px) {
   202→  #email-intel-sidebar {
   203→    width: 360px !important;
   204→  }
   205→}
   206→

Prompt:
Explore the Chrome extension's "Ask AI" tab functionality thoroughly. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/` - explore the full directory structure
2. Look at popup.html and popup.js for the "Ask AI" tab UI
3. Look at any JS files that handle AI chat, model selection dropdown, thread context sending
4. Look at background.js for API calls to the server
5. Look at contentScript.js for how it grabs email thread data from Gmail

I need to understand: how does the chrome extension's "Ask AI" tab work? What models are available in the dropdown? How does it send thread context to the AI? What's the UI layout?


find /var/www/mssql.danmarcrm.com/dev1/extension2/aiapi -type f -name "*.php" | head -20

Find PHP files in aiapi directory

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Error: EISDIR: illegal operation on a directory, read '/var/www/mssql.danmarcrm.com/dev1/extension2/aiapi'

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


     1→<?php
     2→
     3→header('Content-Type: application/json');
     4→
     5→require_once __DIR__ . '/../src/AIOrchestrator.php';
     6→
     7→function respond(array $data, int $code = 200): void
     8→{
     9→    http_response_code($code);
    10→    echo json_encode($data);
    11→    exit;
    12→}
    13→
    14→function readInput(): array
    15→{
    16→    $body = file_get_contents('php://input');
    17→    $json = json_decode($body, true);
    18→    if (is_array($json)) {
    19→        return array_merge($_REQUEST, $json);
    20→    }
    21→    return $_REQUEST;
    22→}
    23→
    24→$input = readInput();
    25→$action = $input['action'] ?? 'ask';
    26→
    27→$orchestrator = new AIOrchestrator();
    28→
    29→if ($action === 'history') {
    30→    respond([
    31→        'success' => true,
    32→        'history' => $orchestrator->history(),
    33→    ]);
    34→}
    35→
    36→if ($action === 'reload') {
    37→    $id = $input['id'] ?? '';
    38→    if (!$id) {
    39→        respond(['success' => false, 'error' => 'Missing id'], 400);
    40→    }
    41→    $entry = $orchestrator->reload($id);
    42→    if (!$entry) {
    43→        respond(['success' => false, 'error' => 'Not found'], 404);
    44→    }
    45→    respond(['success' => true, 'entry' => $entry]);
    46→}
    47→
    48→if ($action === 'export') {
    49→    if (!(AI_FEATURE_FLAGS['response_export'] ?? true)) {
    50→        respond(['success' => false, 'error' => 'Export disabled'], 403);
    51→    }
    52→    $id = $input['id'] ?? '';
    53→    if (!$id) {
    54→        respond(['success' => false, 'error' => 'Missing id'], 400);
    55→    }
    56→    $entry = $orchestrator->reload($id);
    57→    if (!$entry) {
    58→        respond(['success' => false, 'error' => 'Not found'], 404);
    59→    }
    60→    header('Content-Disposition: attachment; filename="ai-response-' . $id . '.json"');
    61→    respond(['success' => true, 'entry' => $entry]);
    62→}
    63→
    64→if ($action === 'ask') {
    65→    $prompt = trim($input['user_content'] ?? '');
    66→    if ($prompt === '') {
    67→        respond(['success' => false, 'error' => 'user_content is required'], 400);
    68→    }
    69→
    70→    $models = $input['models'] ?? [];
    71→    $providers = $input['providers'] ?? [];
    72→    $system = trim($input['system'] ?? '');
    73→    $history = $input['history'] ?? [];
    74→
    75→    $entry = $orchestrator->ask($prompt, $models, $providers, $system, $history);
    76→
    77→    respond([
    78→        'success' => true,
    79→        'id' => $entry['id'],
    80→        'responses' => $entry['responses'],
    81→        'models' => $entry['models'],
    82→        'total_cost' => $entry['total_cost'],
    83→        'created_at' => $entry['created_at'],
    84→    ]);
    85→}
    86→
    87→respond(['success' => false, 'error' => 'Unknown action'], 400);
    88→
    89→
    90→

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


grep -n "class ThreadAnalyzer\|function askClaude\|function ask" /var/www/mssql.danmarcrm.com/dev1/extension2/src/*.php 2>/dev/null | head -20

Find ThreadAnalyzer class

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


/var/www/mssql.danmarcrm.com/dev1/extension2/src/DataEnrichment.php:870:    private function askAI(string $prompt): string
/var/www/mssql.danmarcrm.com/dev1/extension2/src/DataEnrichment.php:887:    private function askClaude(string $prompt): string
/var/www/mssql.danmarcrm.com/dev1/extension2/src/DataEnrichment.php:916:    private function askOpenAI(string $prompt): string
/var/www/mssql.danmarcrm.com/dev1/extension2/src/QuoteAssistant.php:49:    public function ask(string $query, array $context = []): array
/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php:31:class ThreadAnalyzer
/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php:1015:    public function askClaude(string $prompt): string

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


grep -n "Contact Context\|Build context\|ctxParts\|system_instructions\|mode.*thread\|mode.*contact" /var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php | head -40

Find context building in AI chat

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


2247:            // Build context
2316:            $chatMode     = $jsonData['mode'] ?? 'general';   // thread|contact|quote|reply|general
2325:            // --- Build context block ---
2326:            $ctxParts = [];
2344:                    $ctxParts[] = "=== EMAIL THREAD (" . count($ctxEmails) . " emails) ===";
2348:                        $ctxParts[] = "Email #".($i+1)." {$dir} ({$em['date']})\nSubject: {$em['subject']}\n{$body}";
2361:                        $ctxParts[] = "=== EXISTING AI ANALYSIS ===\nSummary: " . $ctxAnalysis['summary'];
2376:                    $ctxParts[] = "=== CONTACT: {$ctxContact['name']} ({$ctxContact['email']}) ===";
2378:                        $ctxParts[] = "Trust score: " . ($ctxProfile['overall_trust_score'] ?? 'N/A') .
2392:                    $ctxParts[] = "=== SPECIFIC EMAIL TO REPLY TO ===\nFrom: {$ctxEmail['from_email']}\nSubject: {$ctxEmail['subject']}\n{$ctxEmail['body_text']}";
2405:            $contextBlock = implode("\n\n", $ctxParts);

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


grep -n "contacts\|contact_view.php" /var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php

Find contact view and thread selection in UI

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


5: * Main web interface for viewing contacts, emails, and analysis results.
27:    header('Location: contact_view.php?contact=' . (int)$_GET['contact']);
41:        'contacts' => $db->fetchColumn("SELECT COUNT(*) FROM contacts"),
52:    $stats = ['emails' => 0, 'contacts' => 0, 'analyzed' => 0, 'pending' => 0];
130:
<?= number_format($stats['contacts']) ?>

165:            <button class="tab-btn active" data-tab="contacts">Contacts</button>
178:

180:                <input type="text" id="contact-search" placeholder="Search contacts..." class="search-input">
189:

190:
Loading contacts...

192:

270:
Enrich contacts and companies with data from Apollo.io and web scraping

577:
Ask me anything about your threads, contacts, quotes, or compose replies.

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


     1→<?php
     2→/**
     3→ * Thread Analyzer - Analyzes Complete Email Threads
     4→ *
     5→ * Unlike AIAnalyzer which processes individual emails,
     6→ * this analyzes ENTIRE email threads (conversations) together.
     7→ *
     8→ * WHY THREADS?
     9→ * - Detects inconsistencies across multiple emails
    10→ * - Understands negotiation flow (quote → counter → agreement)
    11→ * - Sees how tone/sentiment changes through conversation
    12→ * - Better psychological profiling with full context
    13→ *
    14→ * CALLING MAP:
    15→ * - Called by: cli/analyze_threads.php (main entry)
    16→ * - Called by: cli/cron_hybrid.php (scheduled)
    17→ * - Uses: Database.php, calls Claude API
    18→ * - Reads from: emails table (grouped by thread_id)
    19→ * - Writes to: thread_analysis, email_analysis tables
    20→ *
    21→ * @package EmailIntelligence
    22→ */
    23→
    24→namespace EmailIntelligence;
    25→
    26→use Exception;
    27→use GuzzleHttp\Client as HttpClient;
    28→use GuzzleHttp\HandlerStack;
    29→use GuzzleHttp\Handler\CurlHandler;
    30→
    31→class ThreadAnalyzer
    32→{
    33→    private Database $db;
    34→    private HttpClient $http;
    35→    private array $config;
    36→    private $progressCallback = null;
    37→
    38→    private array $stats = [
    39→        'threads_analyzed' => 0,
    40→        'threads_failed' => 0,
    41→        'emails_processed' => 0,
    42→        'quotes_extracted' => 0,
    43→        'inconsistencies_found' => 0,
    44→        'tokens_used' => 0,
    45→        'start_time' => null
    46→    ];
    47→
    48→    public function __construct(?string $provider = null, ?string $model = null)
    49→    {
    50→        $this->db = Database::getInstance();
    51→
    52→        // Determine which AI provider to use
    53→        // Use passed parameter, fall back to constant, then default to 'claude'
    54→        if ($provider === null) {
    55→            $provider = defined('AI_PROVIDER') ? AI_PROVIDER : 'claude';
    56→        }
    57→
    58→        if ($provider === 'openai' && defined('OPENAI_API_KEY') && !empty(OPENAI_API_KEY)) {
    59→            // Determine OpenAI model
    60→            // If model is passed, use it; otherwise use OPENAI_MODEL constant or default
    61→            $selectedModel = $model ?? (defined('OPENAI_MODEL') ? OPENAI_MODEL : 'gpt-4o');
    62→
    63→            $this->config = [
    64→                'provider' => 'openai',
    65→                'api_key' => OPENAI_API_KEY,
    66→                'model' => $selectedModel,
    67→                'max_tokens' => defined('OPENAI_MAX_TOKENS') ? OPENAI_MAX_TOKENS : 16000,
    68→                'endpoint' => 'https://api.openai.com/v1/chat/completions'
    69→            ];
    70→
    71→            // Create clean handler stack to avoid New Relic Guzzle infinite loop
    72→            $stack = HandlerStack::create(new CurlHandler());
    73→
    74→            $this->http = new HttpClient([
    75→                'timeout' => 180,
    76→                'handler' => $stack,
    77→                'headers' => [
    78→                    'Content-Type' => 'application/json',
    79→                    'Authorization' => 'Bearer ' . $this->config['api_key']
    80→                ]

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


  1015→    public function askClaude(string $prompt): string
  1016→    {
  1017→        $response = $this->callClaudeAPI($prompt);
  1018→        return $response['content'] ?? '';
  1019→    }
  1020→
  1021→    /**
  1022→     * Call AI API (supports both Claude and OpenAI)
  1023→     */
  1024→    private function callClaudeAPI(string $prompt, ?string $threadId = null): array
  1025→    {
  1026→        try {
  1027→            // Clean UTF-8 in prompt to avoid json_encode errors
  1028→            $cleanPrompt = $this->cleanUtf8($prompt);
  1029→
  1030→            $provider = $this->config['provider'] ?? 'claude';
  1031→            // Generate unique request ID to track duplicate calls
  1032→            $ddbg = debug_backtrace(2);
  1033→            $requestId = uniqid('req_', true);
  1034→            file_put_contents(__DIR__ . '/../logs/prompt.log', "\n\nDate: " . date('Y-m-d H:i:s') . " [RequestID: {$requestId}] [ThreadID: " . ($threadId ?? 'N/A') . "] - Prompt: " . $cleanPrompt . "\n", FILE_APPEND);
  1035→            file_put_contents(__DIR__ . '/../logs/prompt.log', "\n\nDebug Backtrace: " . print_r($ddbg, true) . "\n", FILE_APPEND);
  1036→            // Log the request
  1037→            $this->logToDb('info', 'AI-Request', "Sending request to {$provider} ({$this->config['model']})", [
  1038→                'provider' => $provider,
  1039→                'model' => $this->config['model'],
  1040→                'max_tokens' => $this->config['max_tokens'],
  1041→                'prompt_length' => strlen($cleanPrompt),
  1042→                'prompt_preview' => substr($cleanPrompt, 0, 500) . '...',
  1043→                'prompt' => $cleanPrompt  // Full prompt sent to AI
  1044→            ], $threadId);
  1045→
  1046→            if ($provider === 'openai') {
  1047→                // OpenAI request format
  1048→                $requestBody = [
  1049→                    'model' => $this->config['model'],
  1050→                    'max_tokens' => $this->config['max_tokens'],
  1051→                    'messages' => [
  1052→                        ['role' => 'user', 'content' => $cleanPrompt]
  1053→                    ]
  1054→                ];
  1055→            } else {
  1056→                // Claude request format
  1057→                $requestBody = [
  1058→                    'model' => $this->config['model'],
  1059→                    'max_tokens' => $this->config['max_tokens'],
  1060→                    'messages' => [
  1061→                        ['role' => 'user', 'content' => $cleanPrompt]
  1062→                    ]
  1063→                ];
  1064→            }
  1065→
  1066→            $jsonBody = $this->safeJsonEncode($requestBody);
  1067→            $startTime = microtime(true);
  1068→
  1069→            $response = $this->http->post($this->config['endpoint'], [
  1070→                'headers' => [
  1071→                    'Content-Type' => 'application/json'
  1072→                ],
  1073→                'body' => $jsonBody
  1074→            ]);

Prompt:
Explore the web app's AI-related features thoroughly. I need to understand:

1. How the current AI chat works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_chat.php`
2. How AI analysis works in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/ai_analysis.php`
3. The AI-related API endpoints in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for functions like "analyze", "chat", "ai", "ask"
4. How threads are fetched and displayed in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php`
5. The frontend JS in `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - search for AI chat, analysis, thread selection features

Focus on understanding: what AI chat UI exists, how threads are selected, how context is sent to AI, and what API endpoints handle AI requests.


Design an implementation plan for adding a "context builder + AI chat" feature to the Email Intelligence web app. Here's all the context:

## What the user wants:
The user wants to replicate the Chrome extension's "Ask AI" functionality in the web app, with ENHANCED capabilities:
1. Search for contacts by email/name
2. Select a single thread, multiple threads, or ALL threads for a contact as AI context
3. Choose an AI model from a dropdown (multi-provider: Claude, GPT, Gemini, Grok, DeepSeek, etc.)
4. Ask questions about the selected context - e.g. "how much should I quote?", "what's the deception level?"

Example use cases:
- "Grab all emails for stephanie.k***@asendia.com and check how much we quoted, her profile, and ask how much to quote for task X"
- "Grab multiple threads of david.zolanz@digitalj2.com and ask the level of deception from david"

## Current web app AI chat (what already exists):
- File: `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` (lines 2672-2882)
- Has modes: general, thread (single), contact, quote, reply
- Sends to `api.php?action=ai_chat` which builds context from ONE thread_id or ONE contact_id
- Has model dropdown but only basic models
- Draggable panel with chat history, quick prompts

## Current backend:
- `api.php?action=ai_chat` (lines 2310-2491) - builds context from single thread or contact
- `api.php?action=threads` - lists threads, filterable by contact_id and search
- `QueryAdapter::getThreads($contactId, $search, $limit, $offset)` - fetches threads
- MongoDB + SQL dual support throughout
- Thread emails stored with thread_id grouping
- Contact profiles with trust scores, communication style

## Chrome extension (what to draw inspiration from):
- Has provider dropdown + model dropdown with ALL providers (Claude, OpenAI, Gemini, Grok, DeepSeek, Qwen, Mistral, Cohere)
- Model list defined in JS (lines 18-56 of contentScript.js)
- `fetchEmailContext()` can fetch by thread ID or by email (returns contact + recent threads)
- Conversation history (last 10 exchanges)
- Quick question buttons

## The enhancement needed:
The current web chat can only load ONE thread or ONE contact as context. We need:

1. A **contact/thread search** UI in the AI chat panel (or a new dedicated panel)
2. Ability to **add multiple threads to context** - like a "shopping cart" for context
3. Ability to **"Add all threads for contact X"** with one click
4. The **multi-provider model dropdown** from the chrome extension
5. A **visible context summary** showing what's loaded (e.g. "3 threads, 15 emails from stephanie@...")
6. Backend API changes to accept multiple thread_ids and build combined context

## Key files to modify:
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - Frontend JS
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - Backend API
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php` - HTML for new UI elements

## Constraints:
- Keep using the existing draggable AI chat panel (enhance it, don't replace it)
- Must work with both MongoDB and SQL backends
- Keep the existing modes (thread, contact, quote, reply, general) but enhance them
- Reuse existing QueryAdapter and MongoDatabase classes
- Use the same AI proxy at `aiapi/api_codex51/api/index.php`

Design a detailed, step-by-step implementation plan.

Prompt:
Design an implementation plan for adding a "context builder + AI chat" feature to the Email Intelligence web app. Here's all the context:

## What the user wants:
The user wants to replicate the Chrome extension's "Ask AI" functionality in the web app, with ENHANCED capabilities:
1. Search for contacts by email/name
2. Select a single thread, multiple threads, or ALL threads for a contact as AI context
3. Choose an AI model from a dropdown (multi-provider: Claude, GPT, Gemini, Grok, DeepSeek, etc.)
4. Ask questions about the selected context - e.g. "how much should I quote?", "what's the deception level?"

Example use cases:
- "Grab all emails for stephanie.k***@asendia.com and check how much we quoted, her profile, and ask how much to quote for task X"
- "Grab multiple threads of david.zolanz@digitalj2.com and ask the level of deception from david"

## Current web app AI chat (what already exists):
- File: `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` (lines 2672-2882)
- Has modes: general, thread (single), contact, quote, reply
- Sends to `api.php?action=ai_chat` which builds context from ONE thread_id or ONE contact_id
- Has model dropdown but only basic models
- Draggable panel with chat history, quick prompts

## Current backend:
- `api.php?action=ai_chat` (lines 2310-2491) - builds context from single thread or contact
- `api.php?action=threads` - lists threads, filterable by contact_id and search
- `QueryAdapter::getThreads($contactId, $search, $limit, $offset)` - fetches threads
- MongoDB + SQL dual support throughout
- Thread emails stored with thread_id grouping
- Contact profiles with trust scores, communication style

## Chrome extension (what to draw inspiration from):
- Has provider dropdown + model dropdown with ALL providers (Claude, OpenAI, Gemini, Grok, DeepSeek, Qwen, Mistral, Cohere)
- Model list defined in JS (lines 18-56 of contentScript.js)
- `fetchEmailContext()` can fetch by thread ID or by email (returns contact + recent threads)
- Conversation history (last 10 exchanges)
- Quick question buttons

## The enhancement needed:
The current web chat can only load ONE thread or ONE contact as context. We need:

1. A **contact/thread search** UI in the AI chat panel (or a new dedicated panel)
2. Ability to **add multiple threads to context** - like a "shopping cart" for context
3. Ability to **"Add all threads for contact X"** with one click
4. The **multi-provider model dropdown** from the chrome extension
5. A **visible context summary** showing what's loaded (e.g. "3 threads, 15 emails from stephanie@...")
6. Backend API changes to accept multiple thread_ids and build combined context

## Key files to modify:
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - Frontend JS
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - Backend API
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php` - HTML for new UI elements

## Constraints:
- Keep using the existing draggable AI chat panel (enhance it, don't replace it)
- Must work with both MongoDB and SQL backends
- Keep the existing modes (thread, contact, quote, reply, general) but enhance them
- Reuse existing QueryAdapter and MongoDatabase classes
- Use the same AI proxy at `aiapi/api_codex51/api/index.php`

Design a detailed, step-by-step implementation plan.


List top-level directory structure

Prompt:
Design an implementation plan for adding a "context builder + AI chat" feature to the Email Intelligence web app. Here's all the context:

## What the user wants:
The user wants to replicate the Chrome extension's "Ask AI" functionality in the web app, with ENHANCED capabilities:
1. Search for contacts by email/name
2. Select a single thread, multiple threads, or ALL threads for a contact as AI context
3. Choose an AI model from a dropdown (multi-provider: Claude, GPT, Gemini, Grok, DeepSeek, etc.)
4. Ask questions about the selected context - e.g. "how much should I quote?", "what's the deception level?"

Example use cases:
- "Grab all emails for stephanie.k***@asendia.com and check how much we quoted, her profile, and ask how much to quote for task X"
- "Grab multiple threads of david.zolanz@digitalj2.com and ask the level of deception from david"

## Current web app AI chat (what already exists):
- File: `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` (lines 2672-2882)
- Has modes: general, thread (single), contact, quote, reply
- Sends to `api.php?action=ai_chat` which builds context from ONE thread_id or ONE contact_id
- Has model dropdown but only basic models
- Draggable panel with chat history, quick prompts

## Current backend:
- `api.php?action=ai_chat` (lines 2310-2491) - builds context from single thread or contact
- `api.php?action=threads` - lists threads, filterable by contact_id and search
- `QueryAdapter::getThreads($contactId, $search, $limit, $offset)` - fetches threads
- MongoDB + SQL dual support throughout
- Thread emails stored with thread_id grouping
- Contact profiles with trust scores, communication style

## Chrome extension (what to draw inspiration from):
- Has provider dropdown + model dropdown with ALL providers (Claude, OpenAI, Gemini, Grok, DeepSeek, Qwen, Mistral, Cohere)
- Model list defined in JS (lines 18-56 of contentScript.js)
- `fetchEmailContext()` can fetch by thread ID or by email (returns contact + recent threads)
- Conversation history (last 10 exchanges)
- Quick question buttons

## The enhancement needed:
The current web chat can only load ONE thread or ONE contact as context. We need:

1. A **contact/thread search** UI in the AI chat panel (or a new dedicated panel)
2. Ability to **add multiple threads to context** - like a "shopping cart" for context
3. Ability to **"Add all threads for contact X"** with one click
4. The **multi-provider model dropdown** from the chrome extension
5. A **visible context summary** showing what's loaded (e.g. "3 threads, 15 emails from stephanie@...")
6. Backend API changes to accept multiple thread_ids and build combined context

## Key files to modify:
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - Frontend JS
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - Backend API
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php` - HTML for new UI elements

## Constraints:
- Keep using the existing draggable AI chat panel (enhance it, don't replace it)
- Must work with both MongoDB and SQL backends
- Keep the existing modes (thread, contact, quote, reply, general) but enhance them
- Reuse existing QueryAdapter and MongoDatabase classes
- Use the same AI proxy at `aiapi/api_codex51/api/index.php`

Design a detailed, step-by-step implementation plan.


Prompt:
Design an implementation plan for adding a "context builder + AI chat" feature to the Email Intelligence web app. Here's all the context:

## What the user wants:
The user wants to replicate the Chrome extension's "Ask AI" functionality in the web app, with ENHANCED capabilities:
1. Search for contacts by email/name
2. Select a single thread, multiple threads, or ALL threads for a contact as AI context
3. Choose an AI model from a dropdown (multi-provider: Claude, GPT, Gemini, Grok, DeepSeek, etc.)
4. Ask questions about the selected context - e.g. "how much should I quote?", "what's the deception level?"

Example use cases:
- "Grab all emails for stephanie.k***@asendia.com and check how much we quoted, her profile, and ask how much to quote for task X"
- "Grab multiple threads of david.zolanz@digitalj2.com and ask the level of deception from david"

## Current web app AI chat (what already exists):
- File: `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` (lines 2672-2882)
- Has modes: general, thread (single), contact, quote, reply
- Sends to `api.php?action=ai_chat` which builds context from ONE thread_id or ONE contact_id
- Has model dropdown but only basic models
- Draggable panel with chat history, quick prompts

## Current backend:
- `api.php?action=ai_chat` (lines 2310-2491) - builds context from single thread or contact
- `api.php?action=threads` - lists threads, filterable by contact_id and search
- `QueryAdapter::getThreads($contactId, $search, $limit, $offset)` - fetches threads
- MongoDB + SQL dual support throughout
- Thread emails stored with thread_id grouping
- Contact profiles with trust scores, communication style

## Chrome extension (what to draw inspiration from):
- Has provider dropdown + model dropdown with ALL providers (Claude, OpenAI, Gemini, Grok, DeepSeek, Qwen, Mistral, Cohere)
- Model list defined in JS (lines 18-56 of contentScript.js)
- `fetchEmailContext()` can fetch by thread ID or by email (returns contact + recent threads)
- Conversation history (last 10 exchanges)
- Quick question buttons

## The enhancement needed:
The current web chat can only load ONE thread or ONE contact as context. We need:

1. A **contact/thread search** UI in the AI chat panel (or a new dedicated panel)
2. Ability to **add multiple threads to context** - like a "shopping cart" for context
3. Ability to **"Add all threads for contact X"** with one click
4. The **multi-provider model dropdown** from the chrome extension
5. A **visible context summary** showing what's loaded (e.g. "3 threads, 15 emails from stephanie@...")
6. Backend API changes to accept multiple thread_ids and build combined context

## Key files to modify:
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - Frontend JS
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - Backend API
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php` - HTML for new UI elements

## Constraints:
- Keep using the existing draggable AI chat panel (enhance it, don't replace it)
- Must work with both MongoDB and SQL backends
- Keep the existing modes (thread, contact, quote, reply, general) but enhance them
- Reuse existing QueryAdapter and MongoDatabase classes
- Use the same AI proxy at `aiapi/api_codex51/api/index.php`

Design a detailed, step-by-step implementation plan.


List public directory structure

Prompt:
Design an implementation plan for adding a "context builder + AI chat" feature to the Email Intelligence web app. Here's all the context:

## What the user wants:
The user wants to replicate the Chrome extension's "Ask AI" functionality in the web app, with ENHANCED capabilities:
1. Search for contacts by email/name
2. Select a single thread, multiple threads, or ALL threads for a contact as AI context
3. Choose an AI model from a dropdown (multi-provider: Claude, GPT, Gemini, Grok, DeepSeek, etc.)
4. Ask questions about the selected context - e.g. "how much should I quote?", "what's the deception level?"

Example use cases:
- "Grab all emails for stephanie.k***@asendia.com and check how much we quoted, her profile, and ask how much to quote for task X"
- "Grab multiple threads of david.zolanz@digitalj2.com and ask the level of deception from david"

## Current web app AI chat (what already exists):
- File: `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` (lines 2672-2882)
- Has modes: general, thread (single), contact, quote, reply
- Sends to `api.php?action=ai_chat` which builds context from ONE thread_id or ONE contact_id
- Has model dropdown but only basic models
- Draggable panel with chat history, quick prompts

## Current backend:
- `api.php?action=ai_chat` (lines 2310-2491) - builds context from single thread or contact
- `api.php?action=threads` - lists threads, filterable by contact_id and search
- `QueryAdapter::getThreads($contactId, $search, $limit, $offset)` - fetches threads
- MongoDB + SQL dual support throughout
- Thread emails stored with thread_id grouping
- Contact profiles with trust scores, communication style

## Chrome extension (what to draw inspiration from):
- Has provider dropdown + model dropdown with ALL providers (Claude, OpenAI, Gemini, Grok, DeepSeek, Qwen, Mistral, Cohere)
- Model list defined in JS (lines 18-56 of contentScript.js)
- `fetchEmailContext()` can fetch by thread ID or by email (returns contact + recent threads)
- Conversation history (last 10 exchanges)
- Quick question buttons

## The enhancement needed:
The current web chat can only load ONE thread or ONE contact as context. We need:

1. A **contact/thread search** UI in the AI chat panel (or a new dedicated panel)
2. Ability to **add multiple threads to context** - like a "shopping cart" for context
3. Ability to **"Add all threads for contact X"** with one click
4. The **multi-provider model dropdown** from the chrome extension
5. A **visible context summary** showing what's loaded (e.g. "3 threads, 15 emails from stephanie@...")
6. Backend API changes to accept multiple thread_ids and build combined context

## Key files to modify:
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js` - Frontend JS
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - Backend API
- `/var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php` - HTML for new UI elements

## Constraints:
- Keep using the existing draggable AI chat panel (enhance it, don't replace it)
- Must work with both MongoDB and SQL backends
- Keep the existing modes (thread, contact, quote, reply, general) but enhance them
- Reuse existing QueryAdapter and MongoDatabase classes
- Use the same AI proxy at `aiapi/api_codex51/api/index.php`

Design a detailed, step-by-step implementation plan.