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: ${error.message}`;
  3500→      chatHistory.appendChild(errorDiv);
  3501→    }
  3502→  }
  3503→
  3504→  /**
  3505→   * Load reply options with thread context
  3506→   */
  3507→  async function loadReplyOptions() {
  3508→    if (!currentThreadId) {
  3509→      replyContent.innerHTML = '
No thread selected
';
  3510→      return;
  3511→    }
  3512→
  3513→    replyContent.innerHTML = '
Loading...
';
  3514→
  3515→    // Resolve thread ID first if it's a URL-style ID (FMfcgz...)
  3516→    if (currentMessageId && !isRealGmailThreadId(currentThreadId)) {
  3517→      await resolveRealThreadId();
  3518→    }
  3519→
  3520→    // Fetch thread participants for context
  3521→    let participants = [];
  3522→    let threadSubject = currentSubject || '';
  3523→    if (currentThreadId) {
  3524→      try {
  3525→        const resp = await sendMessage('getThreadParticipants', {thread_id: currentThreadId});
  3526→        if (resp.success && resp.data) {
  3527→          participants = resp.data.participants?.filter(p => p.participant_type === 'external') || [];
  3528→          threadSubject = resp.data.subject || threadSubject;
  3529→        }
  3530→      } catch (e) {
  3531→        console.log("[Email Intelligence] Could not load participants for Reply context");
  3532→      }
  3533→    }
  3534→
  3535→    const participantNames = participants.map(p => p.name || p.email.split('@')[0]).join(', ');
  3536→    const hasContext = currentThreadId && participants.length > 0;
  3537→
  3538→    // Load saved templates from storage
  3539→    let templates = [];
  3540→    try {
  3541→      const storage = await chrome.storage.local.get('replyTemplates');
  3542→      templates = storage.replyTemplates || [];
  3543→    } catch (e) {
  3544→      console.log("[Email Intelligence] Could not load templates:", e);
  3545→    }
  3546→
  3547→    const templateOptions = templates.length > 0
  3548→      ? templates.map((t, i) => `<option value="${i}">${escapeHtml(t.name)}</option>`).join('')
  3549→      : '';
  3550→
  3551→    replyContent.innerHTML = `
  3552→      ${hasContext ? `
  3553→

  3554→
REPLYING TO

  3555→
${escapeHtml(threadSubject)}

  3556→
Recipients: ${escapeHtml(participantNames)}

  3557→

  3558→      ` : ''}
  3559→
  3560→
  3561→

  3562→

  3563→

  3564→            ✨ AI Reply Suggestions
  3565→

  3566→          <button id="load-suggestions-btn" style="
  3567→            background: #0ea5e9;
  3568→            color: white;
  3569→            border: none;
  3570→            padding: 6px 12px;
  3571→            border-radius: 4px;
  3572→            cursor: pointer;
  3573→            font-size: 11px;
  3574→            font-weight: 500;
  3575→          ">Generate 5 Options</button>
  3576→

  3577→

  3578→          Click "Generate 5 Options" to get AI-suggested replies based on the conversation.
  3579→

  3580→

  3581→
  3582→

  3583→
OR CUSTOMIZE YOUR OWN:

  3584→
  3585→

  3586→          Tone:
  3587→          <select id="reply-tone-select" style="
  3588→            width: 100%;
  3589→            padding: 8px;
  3590→            border: 1px solid #e0e0e0;
  3591→            border-radius: 6px;
  3592→            font-size: 12px;
  3593→          ">
  3594→            <option value="professional">Professional</option>
  3595→            <option value="friendly">Friendly</option>
  3596→            <option value="firm">Firm</option>
  3597→            <option value="casual">Casual</option>
  3598→          </select>
  3599→

  3600→
  3601→

  3602→          Instructions:
  3603→          <textarea id="reply-custom-instructions" placeholder="E.g., 'Ask for a meeting', 'Politely decline'..." style="
  3604→            width: 100%;
  3605→            padding: 8px;
  3606→            border: 1px solid #e0e0e0;
  3607→            border-radius: 6px;
  3608→            font-size: 12px;
  3609→            min-height: 60px;
  3610→            resize: vertical;
  3611→            box-sizing: border-box;
  3612→            font-family: inherit;
  3613→          "></textarea>
  3614→

  3615→
  3616→        ${templates.length > 0 ? `
  3617→

  3618→            Templates:
  3619→

  3620→              <select id="template-select" style="
  3621→                flex: 1;
  3622→                padding: 6px;
  3623→                border: 1px solid #e0e0e0;
  3624→                border-radius: 4px;
  3625→                font-size: 11px;
  3626→              ">
  3627→                <option value="">-- Select --</option>
  3628→                ${templateOptions}
  3629→              </select>
  3630→              <button id="load-template-btn" style="
  3631→                background: #f3f4f6;
  3632→                border: 1px solid #e0e0e0;
  3633→                color: #374151;
  3634→                padding: 6px 10px;
  3635→                border-radius: 4px;
  3636→                cursor: pointer;
  3637→                font-size: 11px;
  3638→              ">Load</button>
  3639→              <button id="delete-template-btn" style="
  3640→                background: #fef2f2;
  3641→                border: 1px solid #fecaca;
  3642→                color: #dc2626;
  3643→                padding: 6px 8px;
  3644→                border-radius: 4px;
  3645→                cursor: pointer;
  3646→                font-size: 11px;
  3647→              ">✕</button>
  3648→

  3649→

  3650→        ` : ''}
  3651→
  3652→

  3653→          <button id="generate-replies-btn" style="
  3654→            flex: 1;
  3655→            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
  3656→            color: white;
  3657→            border: none;
  3658→            padding: 10px;
  3659→            border-radius: 6px;
  3660→            cursor: pointer;
  3661→            font-weight: 600;
  3662→            font-size: 12px;
  3663→          ">Generate Custom Reply</button>
  3664→          <button id="save-template-btn" style="
  3665→            background: white;
  3666→            border: 1px solid #667eea;
  3667→            color: #667eea;
  3668→            padding: 10px;
  3669→            border-radius: 6px;
  3670→            cursor: pointer;
  3671→            font-weight: 500;
  3672→            font-size: 11px;
  3673→          ">Save Template</button>
  3674→

  3675→

  3676→
  3677→

  3678→
  3679→
  3680→      ${currentContactId ? `
  3681→

  3682→

  3683→
✉ COMPOSE NEW EMAIL

  3684→
Write a new email to this contact

  3685→
Uses AI + past conversation context

  3686→

  3687→
  3688→

  3689→            Email Type:
  3690→            <select id="compose-email-type" style="
  3691→              width: 100%;
  3692→              padding: 8px;
  3693→              border: 1px solid #e0e0e0;
  3694→              border-radius: 6px;
  3695→              font-size: 12px;
  3696→            ">
  3697→              <option value="winback">🔙 Win-back Email</option>
  3698→              <option value="followup">📋 Follow-up</option>
  3699→              <option value="proposal">💼 Proposal/Pitch</option>
  3700→              <option value="checkin">👋 Check-in</option>
  3701→              <option value="custom">✏ Custom</option>
  3702→            </select>
  3703→

  3704→
  3705→

  3706→            Additional Context/Instructions:
  3707→            <textarea id="compose-context" placeholder="E.g., 'Mention our new pricing', 'Offer a discount', 'Ask about their project'..." style="
  3708→              width: 100%;
  3709→              padding: 8px;
  3710→              border: 1px solid #e0e0e0;
  3711→              border-radius: 6px;
  3712→              font-size: 12px;
  3713→              min-height: 60px;
  3714→              resize: vertical;
  3715→              box-sizing: border-box;
  3716→              font-family: inherit;
  3717→            "></textarea>
  3718→

  3719→
  3720→          <button id="generate-compose-btn" style="
  3721→            width: 100%;
  3722→            background: linear-gradient(135deg, #10b981 0%, #059669 100%);
  3723→            color: white;
  3724→            border: none;
  3725→            padding: 12px;
  3726→            border-radius: 6px;
  3727→            cursor: pointer;
  3728→            font-weight: 600;
  3729→            font-size: 12px;
  3730→          ">✨ Generate Email with AI</button>
  3731→
  3732→

  3733→

  3734→      ` : `
  3735→

  3736→

  3737→

  3738→              ✉ To compose a new email, view a thread from a known contact first.
  3739→

  3740→

  3741→

  3742→      `}
  3743→    `;
  3744→
  3745→    // Event listeners
  3746→    shadowRoot.getElementById('load-suggestions-btn').addEventListener('click', loadAISuggestions);
  3747→    shadowRoot.getElementById('generate-replies-btn').addEventListener('click', generateReplies);
  3748→    shadowRoot.getElementById('save-template-btn').addEventListener('click', saveReplyTemplate);
  3749→

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 how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


     1→<?php
     2→/**
     3→ * REST API Endpoint
     4→ *
     5→ * Provides JSON API for the web dashboard and external integrations.
     6→ *
     7→ * CALLING MAP:
     8→ * - Entry point: AJAX requests from index.php
     9→ * - Uses: All src/ classes depending on action
    10→ * - Returns: JSON responses
    11→ *
    12→ * ENDPOINTS:
    13→ *   GET  ?action=status           - System status and statistics
    14→ *   GET  ?action=contacts         - List contacts with profiles
    15→ *   GET  ?action=contact&id=X     - Single contact with full profile
    16→ *   GET  ?action=emails&contact=X - Emails for a contact
    17→ *   GET  ?action=email&id=X       - Single email with analysis
    18→ *   GET  ?action=quotes           - All quotes
    19→ *   GET  ?action=filters          - Email filters
    20→ *   POST ?action=add_filter       - Add email filter
    21→ *   POST ?action=remove_filter    - Remove email filter
    22→ *   POST ?action=sync             - Trigger sync
    23→ *   POST ?action=analyze          - Trigger analysis
    24→ *   POST ?action=build_profile    - Build profile for contact
    25→ *
    26→ * @package EmailIntelligence
    27→ */
    28→
    29→if (!isset($_GET) and isset($_REQUEST)){
    30→    $_GET = $_REQUEST;
    31→}
    32→ini_set("error_log", "error_logs.log");
    33→file_put_contents('apiLogs.log', print_r($_REQUEST, true) . "\n", FILE_APPEND); /// DAN DO NOT REMOVE
    34→
    35→// Error logging file path
    36→define('PHP_ERROR_LOG_FILE', dirname(__DIR__) . '/logs/__php_error.log');
    37→
    38→// Custom error handler for non-fatal errors
    39→set_error_handler(function($errno, $errstr, $errfile, $errline) {
    40→    $errorTypes = [
    41→        E_ERROR => 'ERROR',
    42→        E_WARNING => 'WARNING',
    43→        E_PARSE => 'PARSE',
    44→        E_NOTICE => 'NOTICE',
    45→        E_CORE_ERROR => 'CORE_ERROR',
    46→        E_CORE_WARNING => 'CORE_WARNING',
    47→        E_COMPILE_ERROR => 'COMPILE_ERROR',
    48→        E_COMPILE_WARNING => 'COMPILE_WARNING',
    49→        E_USER_ERROR => 'USER_ERROR',
    50→        E_USER_WARNING => 'USER_WARNING',
    51→        E_USER_NOTICE => 'USER_NOTICE',
    52→        E_STRICT => 'STRICT',
    53→        E_RECOVERABLE_ERROR => 'RECOVERABLE_ERROR',
    54→        E_DEPRECATED => 'DEPRECATED',
    55→        E_USER_DEPRECATED => 'USER_DEPRECATED',
    56→    ];
    57→
    58→    $type = $errorTypes[$errno] ?? 'UNKNOWN';
    59→    $timestamp = date('Y-m-d H:i:s');
    60→    $logMessage = "[{$timestamp}] PHP {$type}: {$errstr} in {$errfile} on line {$errline}\n";
    61→
    62→    file_put_contents(PHP_ERROR_LOG_FILE, $logMessage, FILE_APPEND | LOCK_EX);
    63→
    64→    // For fatal-level errors, also output JSON
    65→    if (in_array($errno, [E_ERROR, E_USER_ERROR, E_RECOVERABLE_ERROR])) {
    66→        if (!headers_sent()) {
    67→            header('Content-Type: application/json');
    68→            http_response_code(500);
    69→        }
    70→        echo json_encode([
    71→            'error' => true,
    72→            'message' => 'Internal server error',
    73→            'debug' => [
    74→                'type' => $type,
    75→                'message' => $errstr,
    76→                'file' => basename($errfile),
    77→                'line' => $errline
    78→            ]
    79→        ]);
    80→        exit(1);
    81→    }
    82→
    83→    return false; // Let PHP handle the error as well
    84→});
    85→
    86→// Custom exception handler for uncaught exceptions
    87→set_exception_handler(function($exception) {
    88→    $timestamp = date('Y-m-d H:i:s');
    89→    $logMessage = "[{$timestamp}] UNCAUGHT EXCEPTION: " . get_class($exception) . ": {$exception->getMessage()} in {$exception->getFile()} on line {$exception->getLine()}\n";
    90→    $logMessage .= "Stack trace:\n{$exception->getTraceAsString()}\n\n";
    91→
    92→    file_put_contents(PHP_ERROR_LOG_FILE, $logMessage, FILE_APPEND | LOCK_EX);
    93→
    94→    if (!headers_sent()) {
    95→        header('Content-Type: application/json');
    96→        http_response_code(500);
    97→    }
    98→    echo json_encode([
    99→        'error' => true,
   100→        'message' => 'Internal server error',
   101→        'debug' => [
   102→            'type' => get_class($exception),
   103→            'message' => $exception->getMessage(),
   104→            'file' => basename($exception->getFile()),
   105→            'line' => $exception->getLine()
   106→        ]
   107→    ]);
   108→    exit(1);
   109→});
   110→
   111→// Shutdown function to catch fatal errors
   112→register_shutdown_function(function() {
   113→    $error = error_get_last();
   114→    if ($error !== null && in_array($error['type'], [E_ERROR, E_PARSE, E_CORE_ERROR, E_COMPILE_ERROR])) {
   115→        $errorTypes = [
   116→            E_ERROR => 'FATAL ERROR',
   117→            E_PARSE => 'PARSE ERROR',
   118→            E_CORE_ERROR => 'CORE ERROR',
   119→            E_COMPILE_ERROR => 'COMPILE ERROR',
   120→        ];
   121→
   122→        $type = $errorTypes[$error['type']] ?? 'FATAL';
   123→        $timestamp = date('Y-m-d H:i:s');
   124→        $logMessage = "[{$timestamp}] {$type}: {$error['message']} in {$error['file']} on line {$error['line']}\n";
   125→
   126→        file_put_contents(PHP_ERROR_LOG_FILE, $logMessage, FILE_APPEND | LOCK_EX);
   127→
   128→        // Clear any previous output
   129→        if (ob_get_level()) {
   130→            ob_end_clean();
   131→        }
   132→
   133→        if (!headers_sent()) {
   134→            header('Content-Type: application/json');
   135→            http_response_code(500);
   136→        }
   137→        echo json_encode([
   138→            'error' => true,
   139→            'message' => 'Internal server error',
   140→            'debug' => [
   141→                'type' => $type,
   142→                'message' => $error['message'],
   143→                'file' => basename($error['file']),
   144→                'line' => $error['line']
   145→            ]
   146→        ]);
   147→    }
   148→});
   149→
   150→// Load configuration

Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


   380→        // ==========================================
   381→        // Email Threads (grouped by thread_id)
   382→        // ==========================================
   383→        case 'threads':
   384→            $contactId = (int)($_GET['contact'] ?? 0);
   385→            $search = trim($_GET['search'] ?? '');
   386→            $page = max(1, (int)($_GET['page'] ?? 1));
   387→            $limit = min(100, max(1, (int)($_GET['limit'] ?? 20)));
   388→            $offset = ($page - 1) * $limit;
   389→            $hasBusiness = isset($_GET['has_business']) && $_GET['has_business'];
   390→
   391→            // Use QueryAdapter for automatic MySQL/MongoDB routing
   392→            $adapter = QueryAdapter::getInstance();
   393→            $result = $adapter->getThreads(
   394→                $contactId ?: null,
   395→                $search,
   396→                $limit,
   397→                $offset
   398→            );
   399→
   400→            // Note: has_business filtering is handled by frontend due to raw_analysis being stored as JSON string
   401→            // Future: migrate raw_analysis to proper BSON objects for better querying
   402→
   403→            jsonResponse([
   404→                'threads' => $result['threads'],
   405→                'pagination' => [
   406→                    'page' => $page,
   407→                    'limit' => $limit,
   408→                    'total' => $result['total'],
   409→                    'pages' => ceil($result['total'] / $limit)
   410→                ]
   411→            ]);
   412→            break;
   413→
   414→        // ==========================================
   415→        // Single Thread with All Emails
   416→        // ==========================================
   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→                }

Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


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?


  2310→        case 'ai_chat':
  2311→            if ($_SERVER['REQUEST_METHOD'] !== 'POST') jsonError('POST required', 405);
  2312→
  2313→            $jsonData = json_decode(file_get_contents('php://input'), true) ?? [];
  2314→            $chatMessage  = trim($jsonData['message'] ?? '');
  2315→            $chatModel    = $jsonData['model'] ?? 'gpt-4o';
  2316→            $chatMode     = $jsonData['mode'] ?? 'general';   // thread|contact|quote|reply|general
  2317→            $chatThreadId = $jsonData['thread_id'] ?? null;
  2318→            $chatContactId= (int)($jsonData['contact_id'] ?? 0);
  2319→            $chatHistory  = $jsonData['history'] ?? [];       // [{role,content}]
  2320→            $chatEmailId  = (int)($jsonData['email_id'] ?? 0);
  2321→
  2322→            if (!$chatMessage) jsonError('message required');
  2323→            if ($chatThreadId) $chatThreadId = resolveThreadId($chatThreadId);
  2324→
  2325→            // --- Build context block ---
  2326→            $ctxParts = [];
  2327→            $ctxAdapter = QueryAdapter::getInstance();
  2328→            $ctxMongo = \EmailIntelligence\MongoDatabase::getInstance();
  2329→            $useMongoDB = $ctxAdapter->getActiveDatabase() === 'mongodb';
  2330→
  2331→            // Thread context - use MongoDB-aware queries
  2332→            if ($chatThreadId) {
  2333→                if ($useMongoDB) {
  2334→                    $ctxEmails = $ctxMongo->findAll('emails', ['thread_id' => $chatThreadId], [
  2335→                        'sort' => ['date' => 1]
  2336→                    ]);
  2337→                } else {
  2338→                    $ctxEmails = $db->fetchAll(
  2339→                        "SELECT direction, date, from_email, to_email, subject, body_text FROM emails WHERE thread_id = ? ORDER BY date ASC",
  2340→                        [$chatThreadId]
  2341→                    );
  2342→                }
  2343→                if ($ctxEmails) {
  2344→                    $ctxParts[] = "=== EMAIL THREAD (" . count($ctxEmails) . " emails) ===";
  2345→                    foreach ($ctxEmails as $i => $em) {
  2346→                        $dir = ($em['direction'] ?? '') === 'inbound' ? 'FROM THEM' : 'FROM US';
  2347→                        $body = substr($em['body_text'] ?? '', 0, 800);
  2348→                        $ctxParts[] = "Email #".($i+1)." {$dir} ({$em['date']})\nSubject: {$em['subject']}\n{$body}";
  2349→                    }
  2350→                    // Include existing analysis if available
  2351→                    if ($useMongoDB) {
  2352→                        $ctxAnalysis = $ctxMongo->findOne('thread_analysis', ['thread_id' => $chatThreadId, 'is_analyzed' => 1]);
  2353→                        if (!$ctxAnalysis) {
  2354→                            // Try without is_analyzed filter (MongoDB may store as bool or int)
  2355→                            $ctxAnalysis = $ctxMongo->findOne('thread_analysis', ['thread_id' => $chatThreadId]);
  2356→                        }
  2357→                    } else {
  2358→                        $ctxAnalysis = $db->fetchOne("SELECT summary, raw_analysis FROM thread_analysis WHERE thread_id = ? AND is_analyzed=1", [$chatThreadId]);
  2359→                    }
  2360→                    if ($ctxAnalysis && !empty($ctxAnalysis['summary'])) {
  2361→                        $ctxParts[] = "=== EXISTING AI ANALYSIS ===\nSummary: " . $ctxAnalysis['summary'];
  2362→                    }
  2363→                }
  2364→            }
  2365→
  2366→            // Contact context - use MongoDB-aware queries
  2367→            if ($chatContactId) {
  2368→                if ($useMongoDB) {
  2369→                    $ctxContact = $ctxMongo->findOne('contacts', ['id' => $chatContactId]);
  2370→                    $ctxProfile = $ctxMongo->findOne('contact_profiles', ['contact_id' => $chatContactId]);
  2371→                } else {
  2372→                    $ctxContact = $db->fetchOne("SELECT name, email, type, company FROM contacts WHERE id = ?", [$chatContactId]);
  2373→                    $ctxProfile = $db->fetchOne("SELECT * FROM contact_profiles WHERE contact_id = ?", [$chatContactId]);
  2374→                }
  2375→                if ($ctxContact) {
  2376→                    $ctxParts[] = "=== CONTACT: {$ctxContact['name']} ({$ctxContact['email']}) ===";
  2377→                    if ($ctxProfile) {
  2378→                        $ctxParts[] = "Trust score: " . ($ctxProfile['overall_trust_score'] ?? 'N/A') .
  2379→                            " | Communication style: " . ($ctxProfile['communication_style'] ?? 'N/A');
  2380→                    }
  2381→                }
  2382→            }
  2383→
  2384→            // Single email context (for reply mode) - use MongoDB-aware queries
  2385→            if ($chatEmailId) {
  2386→                if ($useMongoDB) {
  2387→                    $ctxEmail = $ctxMongo->findOne('emails', ['id' => $chatEmailId]);
  2388→                } else {
  2389→                    $ctxEmail = $db->fetchOne("SELECT * FROM emails WHERE id = ?", [$chatEmailId]);
  2390→                }
  2391→                if ($ctxEmail) {
  2392→                    $ctxParts[] = "=== SPECIFIC EMAIL TO REPLY TO ===\nFrom: {$ctxEmail['from_email']}\nSubject: {$ctxEmail['subject']}\n{$ctxEmail['body_text']}";
  2393→                }
  2394→            }
  2395→
  2396→            // Mode-specific system instructions
  2397→            $systemInstructions = [
  2398→                'thread'  => "You are a business intelligence assistant analyzing an email thread. Provide insights about the conversation, relationships, risks, and opportunities. Be direct and specific.",
  2399→                'contact' => "You are a CRM intelligence assistant analyzing a contact's profile and history. Help understand their behavior, communication patterns, and how best to work with them.",
  2400→                'quote'   => "You are a business consultant helping estimate project costs and create quotes. Based on the email context, suggest realistic pricing, scope, and approach for software/CRM projects.",
  2401→                'reply'   => "You are an email writing assistant. Compose professional, ready-to-send email replies based on the thread context. Write only the reply text with greeting and sign-off.",
  2402→                'general' => "You are a business intelligence assistant with access to email and contact data. Answer questions, provide analysis, and help with business decisions.",
  2403→            ];
  2404→            $sysMsg = $systemInstructions[$chatMode] ?? $systemInstructions['general'];
  2405→            $contextBlock = implode("\n\n", $ctxParts);
  2406→            if ($contextBlock) {
  2407→                $sysMsg .= "\n\nCONTEXT:\n" . $contextBlock;
  2408→            }
  2409→
  2410→            // Build messages array with history
  2411→            $messages = [];
  2412→            foreach ($chatHistory as $h) {
  2413→                if (isset($h['role'], $h['content'])) {
  2414→                    $messages[] = ['role' => $h['role'], 'content' => $h['content']];
  2415→                }
  2416→            }
  2417→            $messages[] = ['role' => 'user', 'content' => $chatMessage];
  2418→
  2419→            // Determine provider from model name
  2420→            $chatProvider = 'openai';
  2421→            if (strpos($chatModel, 'claude') !== false) $chatProvider = 'claude';
  2422→            elseif (strpos($chatModel, 'gemini') !== false) $chatProvider = 'gemini';
  2423→            elseif (strpos($chatModel, 'grok') !== false) $chatProvider = 'grok';
  2424→
  2425→            // Route through proxy for multi-model support
  2426→            $proxyUrl = 'https://mssql.danmarcrm.com/dev1/extension2/aiapi/api_codex51/api/index.php';
  2427→            $proxyPayload = json_encode([
  2428→                'action'       => 'ask',
  2429→                'user_content' => $chatMessage,
  2430→                'system'       => $sysMsg,
  2431→                'models'       => [$chatModel],
  2432→                'providers'    => [$chatProvider],
  2433→                'history'      => array_slice($chatHistory, -10), // last 10 turns
  2434→            ]);
  2435→
  2436→            $ch = curl_init($proxyUrl);
  2437→            curl_setopt_array($ch, [
  2438→                CURLOPT_RETURNTRANSFER => true,
  2439→                CURLOPT_POST => true,
  2440→                CURLOPT_HTTPHEADER => ['Content-Type: application/json'],
  2441→                CURLOPT_POSTFIELDS => $proxyPayload,
  2442→                CURLOPT_TIMEOUT => 120,
  2443→            ]);
  2444→            $proxyResponse = curl_exec($ch);
  2445→            $curlError = curl_error($ch);
  2446→            curl_close($ch);
  2447→
  2448→            if ($curlError) {
  2449→                // Fallback to direct ThreadAnalyzer if proxy fails
  2450→                try {
  2451→                    $analyzer = new ThreadAnalyzer($chatProvider === 'openai' ? 'openai' : 'claude', $chatModel);
  2452→                    $fullPrompt = $sysMsg . "\n\nUser: " . $chatMessage;
  2453→                    $answer = $analyzer->askClaude($fullPrompt);
  2454→                    jsonResponse(['success' => true, 'answer' => $answer, 'model' => $chatModel, 'via' => 'direct']);
  2455→                } catch (Exception $e) {
  2456→                    jsonError('AI request failed: ' . $e->getMessage());
  2457→                }
  2458→                break;
  2459→            }

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.


Bash

grep -n "showThread\|threadId.*=" /var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js | head -30

Find thread selection and display implementation

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.


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}`;

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?


682:

705:async function showThread(threadId) {
722:                <button onclick="openAiChatForThread('${escapeHtml(threadId)}', '${escapeHtml((data.emails[0].subject || '').replace(/'/g, "\\'"))}', ${data.emails[0].contact_id || 0})" style="background:linear-gradient(135deg,#6366f1,#8b5cf6);color:#fff;border:none;border-radius:8px;padding:8px 16px;cursor:pointer;font-size:0.85em;font-weight:600;">💬 Ask AI About This Thread</button>
723:                <button onclick="openAiChatForReply('${escapeHtml(threadId)}', ${data.emails[data.email_count - 1].id || 0}, '${escapeHtml((data.emails[0].subject || '').replace(/'/g, "\\'"))}')" style="background:linear-gradient(135deg,#10b981,#059669);color:#fff;border:none;border-radius:8px;padding:8px 16px;cursor:pointer;font-size:0.85em;font-weight:600;">✍ Compose Reply</button>
943:                    <button class="btn btn-small" onclick="analyzeThread('${escapeHtml(threadId)}')" style="background: #10b981; color: white;">🔄 Re-analyze Thread</button>
971:            showThread(threadId);
1196:
1546:

1682:                            <button class="btn btn-small" onclick="showThread('${escapeHtml(meta.thread_id)}')">View Thread</button>
1910:                        <button class="btn btn-small" onclick="showThread('${meta.thread_id}')">View Thread</button>
2032:                    ${alert.thread_id ? `<button class="btn btn-small" onclick="showThread('${alert.thread_id}')">View Thread</button>` : ''}
2702:    aiChat.threadId = threadId; aiChat.contactId = contactId || null;
2703:    aiChat.threadSubject = subject || threadId; aiChat.emailId = null;
2710:    aiChat.threadId = null; aiChat.emailId = null;
2716:    aiChat.threadId = threadId; aiChat.emailId = emailId; aiChat.threadSubject = subject || threadId;
2771:        if (aiChat.threadId) payload.thread_id = aiChat.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.


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 -name "*.sql" -type f 2>/dev/null | head -20

Find SQL schema files

Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


Grep

CREATE TABLE.*email|CREATE TABLE.*thread|CREATE TABLE.*contact

Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


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)
--
747-    businessContent = createTabContent('business');
748-    protectContent = createTabContent('protect');
749-    replyContent = createTabContent('reply');
750:    askContactAIContent = createTabContent('ask-ai');
751-    logsContent = createTabContent('logs');
752-
753-    contentContainer.appendChild(insightsContent);
--
756-    contentContainer.appendChild(businessContent);
757-    contentContainer.appendChild(protectContent);
758-    contentContainer.appendChild(replyContent);
759:    contentContainer.appendChild(askContactAIContent);
760-    contentContainer.appendChild(logsContent);
761-
762-    // Debug Panel (at top of content)
--
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-
2693-    if (!currentContactId) {
2694:      askContactAIContent.innerHTML = `
2695-

2696-
🤖

2697-
No contact selected

--
2746-      `<option value="${p.email}" ${p.email === currentContactEmail ? 'selected' : ''}>${escapeHtml(p.name ? `${p.name} (${p.email})` : p.email)}</option>`
2747-    ).join('');
2748-
2749:    askContactAIContent.innerHTML = `
2750-
2751-

2752-

--
2984-    });
2985-
2986-    // Event listeners for template questions
2987:    askContactAIContent.querySelectorAll('.template-question-btn').forEach(btn => {
2988-      btn.addEventListener('click', () => {
2989-        const question = btn.dataset.question;
2990-        shadowRoot.getElementById('ask-contact-question-input').value = question;

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 how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


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.


database/schema.sql:30:CREATE TABLE IF NOT EXISTS contacts (
database/schema.sql:57:CREATE TABLE IF NOT EXISTS emails (
database/schema.sql:98:CREATE TABLE IF NOT EXISTS email_analysis (
database/schema.sql:152:CREATE TABLE IF NOT EXISTS contact_profiles (
database/schema.sql:308:CREATE TABLE IF NOT EXISTS email_filters (
database/thread_analysis.sql:6:CREATE TABLE IF NOT EXISTS thread_analysis (

Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


705→async function showThread(threadId) {
   706→    showLoading('Loading thread...');
   707→
   708→    try {
   709→        const data = await apiCall('thread', { thread_id: threadId });
   710→
   711→        let html = `
   712→

   713→
Thread: ${escapeHtml(data.emails[0].subject || '(No Subject)')}

   714→

   715→                    Thread ID: ${escapeHtml(threadId)}
   716→                    Total Emails: ${data.email_count}
   717→                    Date Range: ${formatDate(data.emails[0].date)} → ${formatDate(data.emails[data.email_count - 1].date)}
   718→                    Status: ${data.status.is_analyzed ? '✓ Analyzed' : '⏳ Not analyzed'}
   719→

   720→

   721→

   722→                <button onclick="openAiChatForThread('${escapeHtml(threadId)}', '${escapeHtml((data.emails[0].subject || '').replace(/'/g, "\\'"))}', ${data.emails[0].contact_id || 0})" style="background:linear-gradient(135deg,#6366f1,#8b5cf6);color:#fff;border:none;border-radius:8px;padding:8px 16px;cursor:pointer;font-size:0.85em;font-weight:600;">💬 Ask AI About This Thread</button>
   723→                <button onclick="openAiChatForReply('${escapeHtml(threadId)}', ${data.emails[data.email_count - 1].id || 0}, '${escapeHtml((data.emails[0].subject || '').replace(/'/g, "\\'"))}')" style="background:linear-gradient(135deg,#10b981,#059669);color:#fff;border:none;border-radius:8px;padding:8px 16px;cursor:pointer;font-size:0.85em;font-weight:600;">✍ Compose Reply</button>
   724→

   725→        `;
   726→
   727→        // Show what Claude will see
   728→        html += `
   729→

   730→
🤖 What Claude AI Will Analyze:

   731→
Claude will receive ALL ${data.email_count} emails below in chronological order to analyze the complete conversation.

   732→

   733→        `;
   734→
   735→        // Thread timeline
   736→        html += '
';
   737→        html += '
Email Timeline (as sent to Claude)
';
   738→
   739→        data.emails.forEach((email, index) => {
   740→            const num = index + 1;
   741→            const directionLabel = email.direction === 'inbound' ? 'FROM THEM' : 'FROM US';
   742→            const directionClass = email.direction === 'inbound' ? 'badge-inbound' : 'badge-outbound';
   743→
   744→            // Truncate body for display
   745→            let body = email.body_text || email.body_html || '(No content)';
   746→            const isLong = body.length > 500;
   747→            const displayBody = isLong ? body.substring(0, 500) + '...' : body;
   748→
   749→            html += `
   750→

   751→

   752→                        Email #${num}
   753→                        ${directionLabel}
   754→                        ${formatDateTime(email.date)}
   755→

   756→

   757→${escapeHtml(displayBody)}

   758→                    ${isLong ? '
... (email truncated for display, Claude sees full content)
' : ''}
   759→

   760→            `;
   761→        });
   762→
   763→        html += '
';
   764→
   765→        // Analysis results if available (only show if thread is fully analyzed)
   766→        if (data.analysis && data.analysis.summary && data.status.is_analyzed) {
   767→            const analysis = data.analysis;
   768→            // raw_analysis might be already parsed by PHP or still a string
   769→            let rawAnalysis = {};
   770→            if (analysis.raw_analysis) {
   771→                rawAnalysis = typeof analysis.raw_analysis === 'string'
   772→                    ? JSON.parse(analysis.raw_analysis)
   773→                    : analysis.raw_analysis;
   774→            }
   775→
   776→            html += `
   777→

   778→
AI Analysis Results

   779→
   780→
${escapeHtml(analysis.summary || '')}

   781→
   782→

   783→

   784→                            Sentiment
   785→                            ${(typeof analysis.sentiment === 'object' ? (analysis.sentiment?.overall_sentiment || 'unknown') : analysis.sentiment) || 'unknown'}
   786→

   787→

   788→                            Trust Score
   789→                            = 0.7 ? '#22c55e' : (analysis.trust_score || 0) >= 0.4 ? '#f59e0b' : '#ef4444'}">
   790→                                ${Math.round((analysis.trust_score || 0) * 100)}%
   791→
   792→

   793→

   794→                            Deception Score
   795→                            <span style="font-size: 1.3em; font-weight: bold; color: ${(analysis.deception_score || 0) <= 0.3 ? '#22c55e' : (analysis.deception_score || 0) <= 0.6 ? '#f59e0b' : '#ef4444'}">
   796→                                ${Math.round((analysis.deception_score || 0) * 100)}%
   797→
   798→

   799→

   800→            `;
   801→
   802→            // Business Risks
   803→            if (rawAnalysis.business_risks) {
   804→                const risks = rawAnalysis.business_risks;

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.


Bash

grep -n "tab-emails\|ai-chat\|tab-content" /var/www/mssql.danmarcrm.com/dev1/extension2/public/assets/app.js | head -30

Find HTML structure for tabs and AI chat 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.


71:    document.querySelectorAll('.tab-content').forEach(content => {
2695:    const panel = document.getElementById('ai-chat-panel');
2698:    if (aiChat.isOpen) { document.getElementById('ai-chat-input').focus(); renderQuickPrompts(); }
2705:    if (!aiChat.isOpen) toggleAiChat(); else document.getElementById('ai-chat-input').focus();
2712:    if (!aiChat.isOpen) toggleAiChat(); else document.getElementById('ai-chat-input').focus();
2718:    if (!aiChat.isOpen) toggleAiChat(); else document.getElementById('ai-chat-input').focus();
2729:    const label = document.getElementById('ai-chat-context-label');
2748:    document.getElementById('ai-chat-input').value = prompt;
2757:    const input = document.getElementById('ai-chat-input');
2760:    const model = document.getElementById('ai-chat-model').value;
2761:    const sendBtn = document.getElementById('ai-chat-send-btn');
2796:    const container = document.getElementById('ai-chat-messages');
2827:    const container = document.getElementById('ai-chat-messages');
2832:    if (!document.getElementById('ai-chat-style')) {
2833:        const s = document.createElement('style'); s.id = 'ai-chat-style';
2858:    document.getElementById('ai-chat-messages').innerHTML = `<div style="text-align:center;color:#4a4a6a;font-size:0.8em;padding:20px 0;"><div style="font-size:2em;margin-bottom:8px;">🤖</div><div>Chat cleared. Ask me anything!</div></div>`;
2863:    const header = document.getElementById('ai-chat-header');
2864:    const panel = document.getElementById('ai-chat-panel');

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 how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


     1→-- ============================================================================
     2→-- Email Intelligence System - Database Schema
     3→-- MySQL 5.7 Compatible
     4→-- ============================================================================
     5→--
     6→-- CALLING MAP:
     7→-- - Executed by: cli/install.php, manual MySQL import
     8→-- - Tables used by:
     9→--   * contacts       -> Database.php, EmailSync.php, ContactProfiler.php
    10→--   * emails         -> Database.php, EmailSync.php, AIAnalyzer.php
    11→--   * email_analysis -> AIAnalyzer.php, ContactProfiler.php
    12→--   * contact_profiles -> ContactProfiler.php, public/api.php
    13→--   * quotes         -> AIAnalyzer.php (extraction), public/api.php
    14→--   * sync_status    -> EmailSync.php, cli/sync_emails.php
    15→--   * email_filters  -> EmailSync.php, GmailClient.php
    16→--
    17→-- ============================================================================
    18→
    19→-- Create database if not exists
    20→CREATE DATABASE IF NOT EXISTS email_intelligence
    21→    CHARACTER SET utf8mb4
    22→    COLLATE utf8mb4_unicode_ci;
    23→
    24→USE email_intelligence;
    25→
    26→-- ============================================================================
    27→-- Table: contacts
    28→-- Stores client/supplier contact information
    29→-- ============================================================================
    30→CREATE TABLE IF NOT EXISTS contacts (
    31→    id INT AUTO_INCREMENT PRIMARY KEY COMMENT 'Unique contact identifier',
    32→    email VARCHAR(255) NOT NULL COMMENT 'Primary email address',
    33→    name VARCHAR(255) DEFAULT NULL COMMENT 'Contact full name (extracted from emails)',
    34→    company VARCHAR(255) DEFAULT NULL COMMENT 'Company name (extracted or manual)',
    35→    type ENUM('client', 'supplier', 'other') DEFAULT 'other' COMMENT 'Contact classification',
    36→    first_contact DATETIME DEFAULT NULL COMMENT 'Date of first email exchange',
    37→    last_contact DATETIME DEFAULT NULL COMMENT 'Date of most recent email',
    38→    total_emails INT DEFAULT 0 COMMENT 'Total email count with this contact',
    39→    total_inbound INT DEFAULT 0 COMMENT 'Emails received from contact',
    40→    total_outbound INT DEFAULT 0 COMMENT 'Emails sent to contact',
    41→    notes TEXT DEFAULT NULL COMMENT 'Manual notes about contact',
    42→    is_active TINYINT(1) DEFAULT 1 COMMENT 'Whether contact is active',
    43→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
    44→    updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
    45→
    46→    UNIQUE KEY uk_email (email),
    47→    INDEX idx_type (type),
    48→    INDEX idx_last_contact (last_contact),
    49→    INDEX idx_is_active (is_active)
    50→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
    51→COMMENT='Client and supplier contacts';
    52→
    53→-- ============================================================================
    54→-- Table: emails
    55→-- Stores all synced emails from Gmail
    56→-- ============================================================================
    57→CREATE TABLE IF NOT EXISTS emails (
    58→    id INT AUTO_INCREMENT PRIMARY KEY COMMENT 'Unique email identifier',
    59→    gmail_id VARCHAR(255) NOT NULL COMMENT 'Gmail message ID (unique per account)',
    60→    thread_id VARCHAR(255) DEFAULT NULL COMMENT 'Gmail thread/conversation ID',
    61→    contact_id INT DEFAULT NULL COMMENT 'Link to contacts table',
    62→    direction ENUM('inbound', 'outbound') NOT NULL COMMENT 'Email direction relative to us',
    63→    from_email VARCHAR(255) NOT NULL COMMENT 'Sender email address',
    64→    from_name VARCHAR(255) DEFAULT NULL COMMENT 'Sender display name',
    65→    to_email VARCHAR(500) DEFAULT NULL COMMENT 'Recipient email(s)',
    66→    cc_email VARCHAR(500) DEFAULT NULL COMMENT 'CC recipients',
    67→    subject VARCHAR(500) DEFAULT NULL COMMENT 'Email subject line',
    68→    body_text LONGTEXT DEFAULT NULL COMMENT 'Plain text body',
    69→    body_html LONGTEXT DEFAULT NULL COMMENT 'HTML body (if available)',
    70→    snippet VARCHAR(500) DEFAULT NULL COMMENT 'Gmail snippet/preview',
    71→    date DATETIME NOT NULL COMMENT 'Email sent/received date',
    72→    has_attachments TINYINT(1) DEFAULT 0 COMMENT 'Whether email has attachments',
    73→    attachment_names TEXT DEFAULT NULL COMMENT 'JSON array of attachment filenames',
    74→    labels JSON DEFAULT NULL COMMENT 'Gmail labels as JSON array',
    75→    raw_headers TEXT DEFAULT NULL COMMENT 'Important headers as JSON',
    76→    is_analyzed TINYINT(1) DEFAULT 0 COMMENT 'Whether AI analysis completed',
    77→    is_starred TINYINT(1) DEFAULT 0 COMMENT 'Manually starred/flagged',
    78→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
    79→
    80→    UNIQUE KEY uk_gmail_id (gmail_id),
    81→    INDEX idx_thread_id (thread_id),
    82→    INDEX idx_contact_id (contact_id),
    83→    INDEX idx_direction (direction),
    84→    INDEX idx_date (date),
    85→    INDEX idx_is_analyzed (is_analyzed),
    86→    INDEX idx_from_email (from_email(191)),
    87→
    88→    CONSTRAINT fk_emails_contact
    89→        FOREIGN KEY (contact_id) REFERENCES contacts(id)
    90→        ON DELETE SET NULL ON UPDATE CASCADE
    91→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
    92→COMMENT='Synced emails from Gmail';
    93→
    94→-- ============================================================================
    95→-- Table: email_analysis
    96→-- Stores AI analysis results for each email
    97→-- ============================================================================
    98→CREATE TABLE IF NOT EXISTS email_analysis (
    99→    id INT AUTO_INCREMENT PRIMARY KEY,
   100→    email_id INT NOT NULL COMMENT 'Link to emails table',
   101→
   102→    -- Sentiment Analysis
   103→    sentiment_score DECIMAL(4,3) DEFAULT NULL COMMENT 'Sentiment score -1.000 to 1.000',
   104→    sentiment_label ENUM('very_negative', 'negative', 'neutral', 'positive', 'very_positive') DEFAULT NULL,
   105→
   106→    -- Tone and Style
   107→    tone VARCHAR(50) DEFAULT NULL COMMENT 'Detected tone: formal, friendly, aggressive, etc',
   108→    formality_level TINYINT DEFAULT NULL COMMENT 'Formality 1-5 (1=casual, 5=very formal)',
   109→    urgency_level TINYINT DEFAULT NULL COMMENT 'Urgency 1-5 (1=low, 5=critical)',
   110→
   111→    -- Extracted Entities (JSON)
   112→    key_entities JSON DEFAULT NULL COMMENT 'Amounts, dates, products, companies mentioned',
   113→    commitments JSON DEFAULT NULL COMMENT 'Promises/commitments made by sender',
   114→    requests JSON DEFAULT NULL COMMENT 'Requests/asks from sender',
   115→    action_items JSON DEFAULT NULL COMMENT 'Action items identified',
   116→
   117→    -- Deception/Inconsistency Detection
   118→    deception_flags JSON DEFAULT NULL COMMENT 'Potential inconsistencies or red flags',
   119→    deception_score DECIMAL(3,2) DEFAULT NULL COMMENT 'Likelihood of deception 0.00-1.00',
   120→
   121→    -- Quote/Price Detection
   122→    contains_quote TINYINT(1) DEFAULT 0 COMMENT 'Whether email contains price quote',
   123→    quote_amounts JSON DEFAULT NULL COMMENT 'Extracted quote amounts',
   124→
   125→    -- Summary
   126→    summary TEXT DEFAULT NULL COMMENT 'AI-generated email summary',
   127→    key_points JSON DEFAULT NULL COMMENT 'Main points as JSON array',
   128→
   129→    -- Raw AI Response
   130→    raw_analysis JSON DEFAULT NULL COMMENT 'Complete AI response for debugging',
   131→    model_used VARCHAR(50) DEFAULT NULL COMMENT 'AI model version used',
   132→    tokens_used INT DEFAULT NULL COMMENT 'API tokens consumed',
   133→
   134→    analyzed_at DATETIME DEFAULT CURRENT_TIMESTAMP,
   135→
   136→    UNIQUE KEY uk_email_id (email_id),
   137→    INDEX idx_sentiment (sentiment_label),
   138→    INDEX idx_urgency (urgency_level),
   139→    INDEX idx_contains_quote (contains_quote),
   140→    INDEX idx_deception_score (deception_score),
   141→
   142→    CONSTRAINT fk_analysis_email
   143→        FOREIGN KEY (email_id) REFERENCES emails(id)
   144→        ON DELETE CASCADE ON UPDATE CASCADE
   145→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
   146→COMMENT='AI analysis results for emails';
   147→
   148→-- ============================================================================
   149→-- Table: contact_profiles
   150→-- Aggregated intelligence profiles for each contact
   151→-- ============================================================================
   152→CREATE TABLE IF NOT EXISTS contact_profiles (
   153→    id INT AUTO_INCREMENT PRIMARY KEY,
   154→    contact_id INT NOT NULL COMMENT 'Link to contacts table',
   155→
   156→    -- Psychological Profile
   157→    psychological_profile TEXT DEFAULT NULL COMMENT 'AI-generated personality assessment',
   158→    communication_style VARCHAR(100) DEFAULT NULL COMMENT 'How they communicate',
   159→    personality_traits JSON DEFAULT NULL COMMENT 'Identified personality traits',
   160→
   161→    -- Business Patterns
   162→    negotiation_patterns VARCHAR(100) DEFAULT NULL COMMENT 'Negotiation style: aggressive, collaborative, etc',
   163→    decision_making_speed VARCHAR(50) DEFAULT NULL COMMENT 'fast, moderate, slow',
   164→
   165→    -- Reliability Metrics
   166→    reliability_score DECIMAL(5,2) DEFAULT NULL COMMENT 'Overall reliability 0-100',
   167→    commitment_follow_through DECIMAL(5,2) DEFAULT NULL COMMENT 'How often they keep promises 0-100',
   168→    response_reliability DECIMAL(5,2) DEFAULT NULL COMMENT 'Consistency in responding 0-100',
   169→
   170→    -- Pricing Intelligence
   171→    pricing_sensitivity ENUM('very_high', 'high', 'medium', 'low', 'very_low') DEFAULT NULL,
   172→    typical_discount_request DECIMAL(5,2) DEFAULT NULL COMMENT 'Average discount % requested',
   173→    price_objection_frequency DECIMAL(5,2) DEFAULT NULL COMMENT 'How often they object to prices 0-100',
   174→
   175→    -- Response Patterns
   176→    avg_response_time_hours DECIMAL(10,2) DEFAULT NULL COMMENT 'Average time to respond',
   177→    preferred_contact_times JSON DEFAULT NULL COMMENT 'When they typically respond',
   178→    response_rate DECIMAL(5,2) DEFAULT NULL COMMENT 'Percentage of emails responded to',
   179→
   180→    -- Risk Assessment
   181→    detected_inconsistencies JSON DEFAULT NULL COMMENT 'Historical inconsistencies found',
   182→    inconsistency_count INT DEFAULT 0 COMMENT 'Total inconsistencies detected',
   183→    risk_level ENUM('low', 'medium', 'high') DEFAULT 'low',
   184→    risk_factors JSON DEFAULT NULL COMMENT 'Specific risk factors identified',
   185→
   186→    -- Relationship Status
   187→    relationship_health ENUM('excellent', 'strong', 'stable', 'at-risk', 'poor', 'new') DEFAULT 'new',
   188→    relationship_trend ENUM('improving', 'stable', 'declining') DEFAULT 'stable',
   189→    last_positive_interaction DATETIME DEFAULT NULL,
   190→    last_negative_interaction DATETIME DEFAULT NULL,
   191→
   192→    -- AI Recommendations
   193→    ai_recommendations TEXT DEFAULT NULL COMMENT 'Strategic recommendations',
   194→    best_approach JSON DEFAULT NULL COMMENT 'Recommended communication approach',
   195→    topics_to_avoid JSON DEFAULT NULL COMMENT 'Sensitive topics identified',
   196→
   197→    -- Statistics
   198→    emails_analyzed INT DEFAULT 0 COMMENT 'Number of emails used for profile',
   199→    profile_confidence DECIMAL(3,2) DEFAULT NULL COMMENT 'Confidence in profile 0-1',
   200→
   201→    last_updated DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
   202→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
   203→
   204→    UNIQUE KEY uk_contact_id (contact_id),
   205→    INDEX idx_reliability (reliability_score),
   206→    INDEX idx_risk_level (risk_level),
   207→    INDEX idx_relationship_health (relationship_health),
   208→
   209→    CONSTRAINT fk_profile_contact
   210→        FOREIGN KEY (contact_id) REFERENCES contacts(id)
   211→        ON DELETE CASCADE ON UPDATE CASCADE
   212→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
   213→COMMENT='Aggregated intelligence profiles';
   214→
   215→-- ============================================================================
   216→-- Table: quotes
   217→-- Price quotes extracted from emails (AI auto-extracted)
   218→-- ============================================================================
   219→CREATE TABLE IF NOT EXISTS quotes (
   220→    id INT AUTO_INCREMENT PRIMARY KEY,
   221→    contact_id INT DEFAULT NULL COMMENT 'Link to contacts table',
   222→    email_id INT DEFAULT NULL COMMENT 'Source email',
   223→
   224→    -- Quote Details
   225→    amount DECIMAL(15,2) NOT NULL COMMENT 'Quote amount',
   226→    currency VARCHAR(3) DEFAULT 'EUR' COMMENT 'Currency code',
   227→    description TEXT DEFAULT NULL COMMENT 'What the quote is for',
   228→
   229→    -- Context
   230→    direction ENUM('sent', 'received') NOT NULL COMMENT 'Quote direction',
   231→    quote_type ENUM('initial', 'counter', 'final', 'discount_request') DEFAULT 'initial',
   232→
   233→    -- Outcome Tracking
   234→    outcome ENUM('accepted', 'rejected', 'negotiated', 'pending', 'expired', 'unknown') DEFAULT 'pending',
   235→    final_amount DECIMAL(15,2) DEFAULT NULL COMMENT 'Final agreed amount if different',
   236→    discount_given DECIMAL(5,2) DEFAULT NULL COMMENT 'Discount percentage if any',
   237→
   238→    -- AI Assessment
   239→    margin_assessment ENUM('too_high', 'slightly_high', 'optimal', 'slightly_low', 'too_low') DEFAULT NULL,
   240→    competitive_assessment TEXT DEFAULT NULL COMMENT 'AI assessment vs market',
   241→    confidence_score DECIMAL(3,2) DEFAULT NULL COMMENT 'AI confidence in extraction 0-1',
   242→
   243→    -- Dates
   244→    quote_date DATETIME DEFAULT NULL COMMENT 'When quote was given',
   245→    response_date DATETIME DEFAULT NULL COMMENT 'When response received',
   246→    expiry_date DATETIME DEFAULT NULL COMMENT 'Quote expiration if mentioned',
   247→
   248→    extracted_at DATETIME DEFAULT CURRENT_TIMESTAMP,
   249→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
   250→    updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
   251→
   252→    INDEX idx_contact_id (contact_id),
   253→    INDEX idx_email_id (email_id),
   254→    INDEX idx_outcome (outcome),
   255→    INDEX idx_quote_date (quote_date),
   256→    INDEX idx_direction (direction),
   257→
   258→    CONSTRAINT fk_quotes_contact
   259→        FOREIGN KEY (contact_id) REFERENCES contacts(id)
   260→        ON DELETE SET NULL ON UPDATE CASCADE,
   261→    CONSTRAINT fk_quotes_email
   262→        FOREIGN KEY (email_id) REFERENCES emails(id)
   263→        ON DELETE SET NULL ON UPDATE CASCADE
   264→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
   265→COMMENT='Extracted price quotes';
   266→
   267→-- ============================================================================
   268→-- Table: sync_status
   269→-- Tracks Gmail sync progress and status
   270→-- ============================================================================
   271→CREATE TABLE IF NOT EXISTS sync_status (
   272→    id INT AUTO_INCREMENT PRIMARY KEY,
   273→
   274→    -- Sync State
   275→    last_sync_at DATETIME DEFAULT NULL COMMENT 'Last successful sync time',
   276→    last_history_id VARCHAR(255) DEFAULT NULL COMMENT 'Gmail history ID for incremental sync',
   277→
   278→    -- Statistics
   279→    total_emails_synced INT DEFAULT 0 COMMENT 'Total emails in database',
   280→    last_batch_count INT DEFAULT 0 COMMENT 'Emails synced in last run',
   281→
   282→    -- Status
   283→    status ENUM('idle', 'running', 'error', 'needs_auth') DEFAULT 'idle',
   284→    progress_message VARCHAR(255) DEFAULT NULL COMMENT 'Current operation description',
   285→    progress_percent TINYINT DEFAULT NULL COMMENT 'Progress 0-100',
   286→
   287→    -- Error Tracking
   288→    last_error TEXT DEFAULT NULL COMMENT 'Last error message',
   289→    error_count INT DEFAULT 0 COMMENT 'Consecutive error count',
   290→    last_error_at DATETIME DEFAULT NULL,
   291→
   292→    -- OAuth Status
   293→    oauth_valid TINYINT(1) DEFAULT 0 COMMENT 'Whether OAuth token is valid',
   294→    oauth_expires_at DATETIME DEFAULT NULL COMMENT 'Token expiration time',
   295→
   296→    updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
   297→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
   298→COMMENT='Sync status and progress tracking';
   299→
   300→-- Insert initial sync status record
   301→INSERT INTO sync_status (id, status) VALUES (1, 'needs_auth')
   302→ON DUPLICATE KEY UPDATE status = status;
   303→
   304→-- ============================================================================
   305→-- Table: email_filters
   306→-- Configurable email address filters for sync
   307→-- ============================================================================
   308→CREATE TABLE IF NOT EXISTS email_filters (
   309→    id INT AUTO_INCREMENT PRIMARY KEY,
   310→    email_pattern VARCHAR(255) NOT NULL COMMENT 'Email or pattern to match',
   311→    filter_type ENUM('include', 'exclude') DEFAULT 'include' COMMENT 'Include or exclude matching emails',
   312→    is_domain TINYINT(1) DEFAULT 0 COMMENT 'Whether pattern is domain wildcard',
   313→    description VARCHAR(255) DEFAULT NULL COMMENT 'Why this filter exists',
   314→    is_active TINYINT(1) DEFAULT 1,
   315→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
   316→
   317→    UNIQUE KEY uk_pattern (email_pattern),
   318→    INDEX idx_active (is_active),
   319→    INDEX idx_type (filter_type)
   320→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
   321→COMMENT='Email address filters for sync';
   322→
   323→-- ============================================================================
   324→-- Table: analysis_queue
   325→-- Queue for batch AI analysis
   326→-- ============================================================================
   327→CREATE TABLE IF NOT EXISTS analysis_queue (
   328→    id INT AUTO_INCREMENT PRIMARY KEY,
   329→    email_id INT NOT NULL COMMENT 'Email to analyze',
   330→    priority TINYINT DEFAULT 5 COMMENT 'Priority 1-10 (1=highest)',
   331→    status ENUM('pending', 'processing', 'completed', 'failed') DEFAULT 'pending',
   332→    attempts INT DEFAULT 0 COMMENT 'Processing attempts',
   333→    last_attempt_at DATETIME DEFAULT NULL,
   334→    error_message TEXT DEFAULT NULL,
   335→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
   336→
   337→    UNIQUE KEY uk_email_id (email_id),
   338→    INDEX idx_status_priority (status, priority),
   339→
   340→    CONSTRAINT fk_queue_email
   341→        FOREIGN KEY (email_id) REFERENCES emails(id)
   342→        ON DELETE CASCADE ON UPDATE CASCADE
   343→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
   344→COMMENT='Queue for AI analysis processing';
   345→
   346→-- ============================================================================
   347→-- Table: activity_log
   348→-- System activity and audit log
   349→-- ============================================================================
   350→CREATE TABLE IF NOT EXISTS activity_log (
   351→    id INT AUTO_INCREMENT PRIMARY KEY,
   352→    action VARCHAR(50) NOT NULL COMMENT 'Action type: sync, analyze, profile_update, etc',
   353→    entity_type VARCHAR(50) DEFAULT NULL COMMENT 'contacts, emails, quotes, etc',
   354→    entity_id INT DEFAULT NULL COMMENT 'ID of affected entity',
   355→    details JSON DEFAULT NULL COMMENT 'Action details',
   356→    status ENUM('success', 'failure', 'warning') DEFAULT 'success',
   357→    error_message TEXT DEFAULT NULL,
   358→    duration_ms INT DEFAULT NULL COMMENT 'Operation duration',
   359→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
   360→
   361→    INDEX idx_action (action),
   362→    INDEX idx_entity (entity_type, entity_id),
   363→    INDEX idx_created (created_at),
   364→    INDEX idx_status (status)
   365→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
   366→COMMENT='System activity log';
   367→
   368→-- ============================================================================
   369→-- Views for common queries
   370→-- ============================================================================
   371→
   372→-- View: Contact summary with latest analysis
   373→CREATE OR REPLACE VIEW v_contact_summary AS
   374→SELECT
   375→    c.id,
   376→    c.email,
   377→    c.name,
   378→    c.company,
   379→    c.type,
   380→    c.total_emails,
   381→    c.first_contact,
   382→    c.last_contact,
   383→    cp.relationship_health,
   384→    cp.reliability_score,
   385→    cp.risk_level,
   386→    cp.pricing_sensitivity,
   387→    cp.avg_response_time_hours,
   388→    (SELECT COUNT(*) FROM quotes q WHERE q.contact_id = c.id AND q.outcome = 'pending') as pending_quotes
   389→FROM contacts c
   390→LEFT JOIN contact_profiles cp ON c.id = cp.contact_id
   391→WHERE c.is_active = 1;
   392→
   393→-- View: Emails pending analysis
   394→CREATE OR REPLACE VIEW v_pending_analysis AS
   395→SELECT
   396→    e.id,
   397→    e.gmail_id,
   398→    e.subject,
   399→    e.date,
   400→    e.from_email,
   401→    c.name as contact_name
   402→FROM emails e
   403→LEFT JOIN contacts c ON e.contact_id = c.id
   404→WHERE e.is_analyzed = 0
   405→ORDER BY e.date DESC;
   406→
   407→-- View: Recent quotes with contact info
   408→CREATE OR REPLACE VIEW v_recent_quotes AS
   409→SELECT
   410→    q.id,
   411→    q.amount,
   412→    q.currency,
   413→    q.direction,
   414→    q.outcome,
   415→    q.margin_assessment,
   416→    q.quote_date,
   417→    c.email as contact_email,
   418→    c.name as contact_name,
   419→    c.company as contact_company
   420→FROM quotes q
   421→LEFT JOIN contacts c ON q.contact_id = c.id
   422→ORDER BY q.quote_date DESC;
   423→

Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


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→-- ============================================================================
     2→-- Thread Analysis Tracking Table
     3→-- Tracks which email threads have been analyzed and need re-analysis
     4→-- ============================================================================
     5→
     6→CREATE TABLE IF NOT EXISTS thread_analysis (
     7→    id INT AUTO_INCREMENT PRIMARY KEY,
     8→    thread_id VARCHAR(255) UNIQUE NOT NULL COMMENT 'Gmail thread ID',
     9→    contact_id INT DEFAULT NULL COMMENT 'Primary contact in thread',
    10→
    11→    -- Thread status
    12→    email_count INT DEFAULT 0 COMMENT 'Number of emails in this thread',
    13→    last_email_date DATETIME DEFAULT NULL COMMENT 'Date of most recent email',
    14→    is_analyzed TINYINT(1) DEFAULT 0 COMMENT 'Whether thread has been analyzed',
    15→    needs_reanalysis TINYINT(1) DEFAULT 0 COMMENT 'New emails added, needs re-analysis',
    16→
    17→    -- Analysis results stored in email_analysis table (using last_email_id)
    18→    last_email_id INT DEFAULT NULL COMMENT 'Most recent email (stores analysis)',
    19→
    20→    analyzed_at DATETIME DEFAULT NULL,
    21→    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
    22→    updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
    23→
    24→    INDEX idx_thread_id (thread_id),
    25→    INDEX idx_contact_id (contact_id),
    26→    INDEX idx_needs_reanalysis (is_analyzed, needs_reanalysis),
    27→
    28→    CONSTRAINT fk_thread_contact
    29→        FOREIGN KEY (contact_id) REFERENCES contacts(id)
    30→        ON DELETE SET NULL ON UPDATE CASCADE
    31→) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
    32→COMMENT='Tracks email thread analysis status';
    33→

Prompt:
Explore how contacts and threads are searched/queried in the backend. Look at:

1. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/QueryAdapter.php` - how threads are queried, filtered by contact
2. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ThreadAnalyzer.php` - how thread analysis works
3. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/ContactProfiler.php` - how contact profiles are built
4. `/var/www/mssql.danmarcrm.com/dev1/extension2/src/MongoDatabase.php` and `MongoRepository.php` - how email threads are stored/queried in MongoDB
5. `/var/www/mssql.danmarcrm.com/dev1/extension2/public/api.php` - search for endpoints related to search, contacts, threads, filtering

I need to understand: how can we query all threads for a specific contact email? How are threads stored? What data structure do they have? How does the existing search work?


grep -n "ai-chat\|ai_chat_panel\|Quick Prompts" /var/www/mssql.danmarcrm.com/dev1/extension2/public/index.php

Find AI chat panel HTML structure in index.php

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.


521:

523:

528:
General Chat

541:                    <select id="ai-chat-model" style="flex:1; background:#1e1e2e; color:#e2e8f0; border:1px solid #3d3d5c; border-radius:6px; padding:4px 8px; font-size:0.78em; cursor:pointer;">
574:

588:                    <textarea id="ai-chat-input" placeholder="Ask anything... (Enter to send, Shift+Enter for newline)" style="flex:1; background:#1e1e2e; color:#e2e8f0; border:1px solid #3d3d5c; border-radius:8px; padding:8px 10px; font-size:0.82em; resize:none; height:60px; font-family:inherit; outline:none;" onkeydown="handleAiChatKey(event)"></textarea>
589:                    <button onclick="sendAiChat()" id="ai-chat-send-btn" style="background:linear-gradient(135deg,#6366f1,#8b5cf6); color:#fff; border:none; border-radius:8px; padding:8px 14px; cursor:pointer; font-size:1.1em; height:60px; min-width:44px; transition:opacity 0.2s;">➤</button>
595:        <button id="ai-chat-fab" onclick="toggleAiChat()" title="AI Assistant" style="position:fixed; bottom:20px; right:20px; width:56px; height:56px; background:linear-gradient(135deg,#6366f1,#8b5cf6); color:#fff; border:none; border-radius:50%; font-size:1.5em; cursor:pointer; box-shadow:0 4px 20px rgba(99,102,241,0.5); z-index:9998; transition:transform 0.2s; display:flex; align-items:center; justify-content:center;" onmouseover="this.style.transform='scale(1.1)'" onmouseout="this.style.transform='scale(1)'">🤖</button>

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.