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

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

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

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

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

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


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

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

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


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

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

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


     1→<?php
     2→/**
     3→ * AI Chat Endpoint
     4→ *
     5→ * Allows asking questions about a specific contact with full context
     6→ */
     7→
     8→require_once __DIR__ . '/../config/config.php';
     9→require_once __DIR__ . '/../vendor/autoload.php';
    10→
    11→use EmailIntelligence\MongoDatabase;
    12→
    13→header('Content-Type: application/json');
    14→
    15→// Get POST data
    16→$input = json_decode(file_get_contents('php://input'), true);
    17→
    18→$contactId = (int)($input['contact_id'] ?? 0);
    19→$question = trim($input['question'] ?? '');
    20→$context = trim($input['context'] ?? '');
    21→
    22→if (!$contactId || !$question) {
    23→    echo json_encode(['error' => 'Contact ID and question required']);
    24→    exit;
    25→}
    26→
    27→// Call AI with context
    28→$aiProvider = defined('AI_PROVIDER') ? AI_PROVIDER : 'claude';
    29→$apiKey = $aiProvider === 'claude' ? (defined('CLAUDE_API_KEY') ? CLAUDE_API_KEY : '') : (defined('OPENAI_API_KEY') ? OPENAI_API_KEY : '');
    30→
    31→if (empty($apiKey)) {
    32→    echo json_encode(['error' => 'AI provider not configured']);
    33→    exit;
    34→}
    35→
    36→$prompt = <<<PROMPT
    37→You are a business intelligence AI assistant analyzing a contact's communication patterns and behavior.
    38→
    39→CONTACT CONTEXT:
    40→{$context}
    41→
    42→USER QUESTION:
    43→{$question}
    44→
    45→Provide a clear, actionable answer based on the contact's profile and behavior patterns. Be direct and honest about risks and opportunities.
    46→
    47→If the question is about strategy, provide specific recommendations.
    48→If the question is about warning signs, be explicit about what to watch for.
    49→If the question is about approach, give concrete tactics.
    50→
    51→Keep your response concise but thorough (2-4 paragraphs maximum).
    52→PROMPT;
    53→
    54→try {
    55→    if ($aiProvider === 'claude') {
    56→        $answer = callClaude($prompt, $apiKey);
    57→    } else {
    58→        $answer = callOpenAI($prompt, $apiKey);
    59→    }
    60→
    61→    echo json_encode(['answer' => $answer]);
    62→} catch (Exception $e) {
    63→    echo json_encode(['error' => $e->getMessage()]);
    64→}
    65→
    66→function callClaude(string $prompt, string $apiKey): string
    67→{
    68→    $model = defined('CLAUDE_MODEL') ? CLAUDE_MODEL : 'claude-sonnet-4-5-20250929';
    69→
    70→    $data = [
    71→        'model' => $model,
    72→        'max_tokens' => 1024,
    73→        'messages' => [
    74→            ['role' => 'user', 'content' => $prompt]
    75→        ]
    76→    ];
    77→
    78→    $ch = curl_init('https://api.anthropic.com/v1/messages');
    79→    curl_setopt_array($ch, [
    80→        CURLOPT_RETURNTRANSFER => true,
    81→        CURLOPT_POST => true,
    82→        CURLOPT_HTTPHEADER => [
    83→            'Content-Type: application/json',
    84→            'x-api-key: ' . $apiKey,
    85→            'anthropic-version: 2023-06-01'
    86→        ],
    87→        CURLOPT_POSTFIELDS => json_encode($data),
    88→        CURLOPT_TIMEOUT => 60
    89→    ]);
    90→
    91→    $response = curl_exec($ch);
    92→    $error = curl_error($ch);
    93→    curl_close($ch);
    94→
    95→    if ($error) {
    96→        throw new Exception("Claude API error: $error");
    97→    }
    98→
    99→    $result = json_decode($response, true);
   100→
   101→    if (isset($result['error'])) {
   102→        throw new Exception("Claude error: " . ($result['error']['message'] ?? 'Unknown'));
   103→    }
   104→
   105→    return $result['content'][0]['text'] ?? '';
   106→}
   107→
   108→function callOpenAI(string $prompt, string $apiKey): string
   109→{
   110→    $model = defined('OPENAI_MODEL') ? OPENAI_MODEL : 'gpt-4o';
   111→
   112→    $data = [
   113→        'model' => $model,
   114→        'messages' => [
   115→            ['role' => 'system', 'content' => 'You are a business intelligence AI assistant analyzing contact communication patterns.'],
   116→            ['role' => 'user', 'content' => $prompt]
   117→        ],
   118→        'max_tokens' => 1024,
   119→        'temperature' => 0.7
   120→    ];
   121→
   122→    $ch = curl_init('https://api.openai.com/v1/chat/completions');
   123→    curl_setopt_array($ch, [
   124→        CURLOPT_RETURNTRANSFER => true,
   125→        CURLOPT_POST => true,
   126→        CURLOPT_HTTPHEADER => [
   127→            'Content-Type: application/json',
   128→            'Authorization: Bearer ' . $apiKey
   129→        ],
   130→        CURLOPT_POSTFIELDS => json_encode($data),
   131→        CURLOPT_TIMEOUT => 60
   132→    ]);
   133→
   134→    $response = curl_exec($ch);
   135→    $error = curl_error($ch);
   136→    curl_close($ch);
   137→
   138→    if ($error) {
   139→        throw new Exception("OpenAI API error: $error");
   140→    }
   141→
   142→    $result = json_decode($response, true);
   143→
   144→    if (isset($result['error'])) {
   145→        throw new Exception("OpenAI error: " . ($result['error']['message'] ?? 'Unknown'));
   146→    }
   147→
   148→    return $result['choices'][0]['message']['content'] ?? '';
   149→}
   150→

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

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

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


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

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

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


1→<?php
     2→/**
     3→ * AI Analysis Web Interface
     4→ *
     5→ * Provides web UI for:
     6→ * - Analyzing threads by thread_id
     7→ * - Analyzing emails by email address
     8→ * - Extracting quotes
     9→ * - Building profiles
    10→ * - Viewing analysis results
    11→ */
    12→
    13→require_once __DIR__ . '/../config/config.php';
    14→require_once __DIR__ . '/../vendor/autoload.php';
    15→
    16→use EmailIntelligence\MongoDatabase;
    17→
    18→$mongo = MongoDatabase::getInstance();
    19→
    20→// Handle AJAX requests
    21→if ($_SERVER['REQUEST_METHOD'] === 'POST') {
    22→    header('Content-Type: application/json');
    23→
    24→    $action = $_POST['action'] ?? '';
    25→
    26→    switch ($action) {
    27→        case 'analyze_thread':
    28→            $threadId = $_POST['thread_id'] ?? '';
    29→            if (empty($threadId)) {
    30→                echo json_encode(['error' => 'Thread ID required']);
    31→                exit;
    32→            }
    33→
    34→            // Run analysis in background
    35→            $cmd = "php " . __DIR__ . "/../cli/ai_analyze.php threads --batch=1 > /dev/null 2>&1 &";
    36→            exec($cmd);
    37→
    38→            echo json_encode(['success' => true, 'message' => 'Thread analysis started']);
    39→            exit;
    40→
    41→        case 'analyze_email':
    42→            $email = $_POST['email'] ?? '';
    43→            if (empty($email)) {
    44→                echo json_encode(['error' => 'Email address required']);
    45→                exit;
    46→            }
    47→
    48→            // Find contact by email
    49→            $contact = $mongo->findOne('contacts', ['email' => $email]);
    50→            if (!$contact) {
    51→                echo json_encode(['error' => 'Contact not found']);
    52→                exit;
    53→            }
    54→
    55→            // Run analysis for this contact (use single-dash for arguments)
    56→            $cmd = "php " . __DIR__ . "/../cli/ai_analyze.php all -batch=10 -contact=" . $contact['id'] . " > /dev/null 2>&1 &";
    57→            exec($cmd);
    58→
    59→            echo json_encode(['success' => true, 'message' => 'Analysis started for ' . $email]);
    60→            exit;
    61→
    62→        case 'extract_quotes':
    63→            $batch = (int)($_POST['batch'] ?? 10);
    64→            $cmd = "php " . __DIR__ . "/../cli/ai_analyze.php quotes --batch={$batch} > /dev/null 2>&1 &";
    65→            exec($cmd);
    66→
    67→            echo json_encode(['success' => true, 'message' => "Quote extraction started (batch: {$batch})"]);
    68→            exit;
    69→
    70→        case 'build_profiles':
    71→            $batch = (int)($_POST['batch'] ?? 5);
    72→            $cmd = "php " . __DIR__ . "/../cli/ai_analyze.php profiles --batch={$batch} > /dev/null 2>&1 &";
    73→            exec($cmd);
    74→
    75→            echo json_encode(['success' => true, 'message' => "Profile building started (batch: {$batch})"]);
    76→            exit;
    77→
    78→        case 'get_thread':
    79→            $threadId = $_POST['thread_id'] ?? '';
    80→            $thread = $mongo->findOne('thread_analysis', ['thread_id' => $threadId]);
    81→            echo json_encode($thread ?: ['error' => 'Thread not found']);
    82→            exit;
    83→
    84→        case 'get_profile':
    85→            $email = $_POST['email'] ?? '';
    86→            $contact = $mongo->findOne('contacts', ['email' => $email]);
    87→            if (!$contact) {
    88→                echo json_encode(['error' => 'Contact not found']);
    89→                exit;
    90→            }
    91→
    92→            $profile = $mongo->findOne('contact_profiles', ['contact_id' => $contact['id']]);
    93→            echo json_encode($profile ?: ['error' => 'Profile not found']);
    94→            exit;
    95→
    96→        case 'get_stats':
    97→            $stats = [
    98→                'emails' => [
    99→                    'total' => $mongo->count('emails'),
   100→                    'analyzed' => $mongo->count('emails', ['is_analyzed' => 1]),
   101→                    'quotes_extracted' => $mongo->count('emails', ['_quotes_extracted' => true])
   102→                ],
   103→                'threads' => [
   104→                    'total' => count($mongo->aggregate('emails', [
   105→                        ['$match' => ['thread_id' => ['$ne' => null, '$ne' => '']]],
   106→                        ['$group' => ['_id' => '$thread_id']],
   107→                        ['$count' => 'total']
   108→                    ])),
   109→                    'analyzed' => $mongo->count('thread_analysis', ['is_analyzed' => 1])
   110→                ],
   111→                'quotes' => [
   112→                    'total' => $mongo->count('quotes')
   113→                ],
   114→                'profiles' => [
   115→                    'total' => $mongo->count('contact_profiles')
   116→                ],
   117→                'contacts' => [
   118→                    'total' => $mongo->count('contacts')
   119→                ]
   120→            ];
   121→            echo json_encode($stats);
   122→            exit;
   123→    }
   124→}
   125→
   126→?>
   127→<!DOCTYPE html>
   128→
   129→
   130→    <meta charset="UTF-8">
   131→    <meta name="viewport" content="width=device-width, initial-scale=1.0">
   132→    <title>AI Analysis Dashboard</title>
   133→
   279→
   280→
   281→

   282→
🤖 AI Analysis Dashboard

   283→
Analyze emails, extract quotes, detect deception, and build contact profiles

   284→
   285→
   286→

   287→

   288→
Total Emails

   289→
-

   290→
- analyzed

   291→

   292→

   293→
Email Threads

   294→
-

   295→
- analyzed

   296→

   297→

   298→
Quotes Extracted

   299→
-

   300→

   301→

   302→
Contact Profiles

   303→
-

   304→
with intelligence data

   305→

   306→

   307→
   308→
   309→

   310→
   311→

   312→
📧 Analyze by Email Address

   313→
Run complete AI analysis (threads + quotes + profile) for a specific contact

   314→

   315→                    Email Address
   316→                    <input type="text" id="analyze-email-input" placeholder="john@example.com">
   317→

   318→                <button onclick="analyzeByEmail()">Run Analysis</button>
   319→

   320→

   321→
   322→
   323→

   324→
🧵 Analyze Thread

   325→
Analyze a specific email thread for sentiment, deception, and insights

   326→

   327→                    Thread ID
   328→                    <input type="text" id="analyze-thread-input" placeholder="19b16e61616d0124">
   329→

   330→                <button onclick="analyzeThread()">Analyze Thread</button>
   331→

   332→

   333→
   334→
   335→

   336→
💰 Extract Quotes

   337→
Extract pricing and quotes from threads and emails

   338→

   339→                    Batch Size
   340→                    <input type="number" id="extract-quotes-batch" value="10" min="1" max="100">
   341→

   342→                <button onclick="extractQuotes()">Extract Quotes</button>
   343→

   344→

   345→
   346→
   347→

   348→
👤 Build Profiles

   349→
Generate psychological profiles with deception detection and competitor threat analysis

   350→

   351→                    Batch Size
   352→                    <input type="number" id="build-profiles-batch" value="5" min="1" max="20">
   353→

   354→                <button onclick="buildProfiles()">Build Profiles</button>
   355→

   356→

   357→
   358→
   359→

   360→
🔍 View Thread Analysis

   361→
View existing analysis for a thread

   362→

   363→                    Thread ID
   364→                    <input type="text" id="view-thread-input" placeholder="19b16e61616d0124">
   365→

   366→                <button onclick="viewThread()">View Analysis</button>
   367→

   368→

   369→
   370→
   371→

   372→
👁 View Contact Profile

   373→
View intelligence profile for a contact

   374→

   375→                    Email Address
   376→                    <input type="text" id="view-profile-input" placeholder="john@example.com">
   377→

   378→                <button onclick="viewProfile()">View Profile</button>
   379→

   380→

   381→

   382→

   383→
   384→
   557→
   558→
   559→

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

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

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


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

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

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


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

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

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


Error: File content (43121 tokens) exceeds maximum allowed tokens (25000). Please use offset and limit parameters to read specific portions of the file, or use the GrepTool to search for specific content.

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.


<tool_use_error>Sibling tool call errored</tool_use_error>

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.


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

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

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

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

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

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


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

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

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


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

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

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


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

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

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


     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',

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

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

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


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

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

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


1→<?php
     2→/**
     3→ * Email Intelligence Dashboard
     4→ *
     5→ * Main web interface for viewing contacts, emails, and analysis results.
     6→ *
     7→ * CALLING MAP:
     8→ * - Entry point: Web browser
     9→ * - Uses: api.php for data (via AJAX)
    10→ * - Uses: oauth_callback.php for Gmail connection
    11→ *
    12→ * @package EmailIntelligence
    13→ */
    14→
    15→// Load configuration
    16→require_once dirname(__DIR__) . '/config/config.php';
    17→require_once dirname(__DIR__) . '/vendor/autoload.php';
    18→
    19→use EmailIntelligence\Database;
    20→use EmailIntelligence\GmailClient;
    21→
    22→// Start session for flash messages
    23→session_start();
    24→
    25→// If contact parameter is present, redirect to contact view
    26→if (isset($_GET['contact']) && is_numeric($_GET['contact'])) {
    27→    header('Location: contact_view.php?contact=' . (int)$_GET['contact']);
    28→    exit;
    29→}
    30→
    31→// Get flash message if any
    32→$flashMessage = $_SESSION['flash_message'] ?? null;
    33→unset($_SESSION['flash_message']);
    34→
    35→// Get initial status
    36→try {
    37→    $db = Database::getInstance();
    38→    $syncStatus = $db->fetchOne("SELECT * FROM sync_status WHERE id = 1");
    39→    $stats = [
    40→        'emails' => $db->fetchColumn("SELECT COUNT(*) FROM emails"),
    41→        'contacts' => $db->fetchColumn("SELECT COUNT(*) FROM contacts"),
    42→        'analyzed' => $db->fetchColumn("SELECT COUNT(*) FROM emails WHERE is_analyzed = 1"),
    43→        'pending' => $db->fetchColumn("SELECT COUNT(*) FROM emails WHERE is_analyzed = 0"),
    44→    ];
    45→
    46→    $gmail = new GmailClient();
    47→    $gmailStatus = $gmail->getAuthStatus();
    48→    $authUrl = $gmail->hasCredentials() ? $gmail->getAuthUrl() : null;
    49→
    50→} catch (Exception $e) {
    51→    $error = $e->getMessage();
    52→    $stats = ['emails' => 0, 'contacts' => 0, 'analyzed' => 0, 'pending' => 0];
    53→    $gmailStatus = ['isAuthenticated' => false];
    54→    $syncStatus = null;
    55→    $authUrl = null;
    56→}
    57→?>
    58→<!DOCTYPE html>
    59→
    60→
    61→    <meta charset="UTF-8">
    62→    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    63→    <title>Email Intelligence Dashboard</title>
    64→    <link rel="stylesheet" href="assets/style.css">
    65→
    66→
    67→

    68→
    69→
    70→
Email Intelligence

    71→
AI-Powered Email Analysis for <?= htmlspecialchars(GMAIL_USER_EMAIL) ?>

    72→
    73→
    74→        <?php if (isset($error)): ?>
    75→

    76→            Error: <?= htmlspecialchars($error) ?>
    77→

    78→        <?php endif; ?>
    79→
    80→        <?php if ($flashMessage): ?>
    81→        <div class="alert alert-<?= $flashMessage['type'] ?>">
    82→            <?= htmlspecialchars($flashMessage['text']) ?>
    83→

    84→        <?php endif; ?>
    85→
    86→
    87→

    88→
    89→            <div class="status-card <?= $gmailStatus['isAuthenticated'] ? 'status-ok' : 'status-warning' ?>">
    90→
Gmail

    91→                <?php if ($gmailStatus['isAuthenticated']): ?>
    92→
Connected

    93→
<?= htmlspecialchars($gmailStatus['userEmail']) ?>

    94→                <?php elseif (!$gmailStatus['hasCredentials']): ?>
    95→
Not Configured

    96→
OAuth credentials missing

    97→                <?php else: ?>
    98→
Not Connected

    99→                    <?php if ($authUrl): ?>
   100→                    <a href="<?= htmlspecialchars($authUrl) ?>" class="btn btn-primary">Connect Gmail

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

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

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


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

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

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


     1→/**
     2→ * Email Intelligence Dashboard JavaScript
     3→ *
     4→ * Handles all frontend interactions including:
     5→ * - Tab switching
     6→ * - Data loading via API
     7→ * - Modal management
     8→ * - Filter management
     9→ * - Sync/Analysis triggers
    10→ *
    11→ * CALLING MAP:
    12→ * - Loaded by: index.php
    13→ * - Calls: api.php for all data operations
    14→ *
    15→ * @package EmailIntelligence
    16→ */
    17→
    18→// ============================================
    19→// Global State
    20→// ============================================
    21→const state = {
    22→    contacts: {
    23→        page: 1,
    24→        search: '',
    25→        type: ''
    26→    },
    27→    emails: {
    28→        page: 1,
    29→        contactId: null
    30→    }
    31→};
    32→
    33→// ============================================
    34→// Utility Functions (defined early for global access)
    35→// ============================================
    36→/**
    37→ * Format number with commas
    38→ * Defined in global scope for early access
    39→ */
    40→window.formatNumber = function (num) {
    41→    if (num === null || num === undefined) return '0';
    42→    return num.toString().replace(/\B(?=(\d{3})+(?!\d))/g, ',');
    43→};
    44→
    45→// Also define as regular function for compatibility
    46→function formatNumber(num) {
    47→    if (num === null || num === undefined) return '0';
    48→    return num.toString().replace(/\B(?=(\d{3})+(?!\d))/g, ',');
    49→}
    50→
    51→/**
    52→ * Escape HTML to prevent XSS
    53→ */
    54→function escapeHtml(text) {
    55→    if (!text) return '';
    56→    const div = document.createElement('div');
    57→    div.textContent = text;
    58→    return div.innerHTML;
    59→}
    60→
    61→// ============================================
    62→// Tab Management
    63→// ============================================
    64→function switchTab(tabName) {
    65→    // Update tab buttons
    66→    document.querySelectorAll('.tab-btn').forEach(btn => {
    67→        btn.classList.toggle('active', btn.dataset.tab === tabName);
    68→    });
    69→
    70→    // Update tab content
    71→    document.querySelectorAll('.tab-content').forEach(content => {
    72→        content.classList.toggle('active', content.id === 'tab-' + tabName);
    73→    });
    74→
    75→    // Load data for the tab
    76→    switch (tabName) {
    77→        case 'contacts':
    78→            loadContacts();
    79→            break;
    80→        case 'emails':
    81→            loadEmails();
    82→            break;
    83→        case 'gmail-accounts':
    84→            loadGmailAccounts();
    85→            break;
    86→        case 'patterns':
    87→            loadPatternStats();
    88→            break;
    89→        case 'business':
    90→            loadBusinessOpportunities();
    91→            break;
    92→        case 'alerts':
    93→            loadAlerts();
    94→            break;
    95→        case 'quotes':
    96→            loadQuotes();
    97→            break;
    98→        case 'filters':
    99→            loadFilters();
   100→            break;
   101→    }
   102→}
   103→
   104→// ============================================
   105→// API Helpers
   106→// ============================================
   107→async function apiCall(action, params = {}, method = 'GET') {
   108→    try {
   109→        let url = 'api.php?action=' + action;
   110→
   111→        const options = {
   112→            method: method,
   113→            headers: {}
   114→        };
   115→
   116→        if (method === 'GET') {
   117→            // Add params to URL
   118→            Object.keys(params).forEach(key => {
   119→                url += '&' + encodeURIComponent(key) + '=' + encodeURIComponent(params[key]);
   120→            });
   121→        } else {
   122→            // POST data
   123→            const formData = new FormData();
   124→            Object.keys(params).forEach(key => {
   125→                formData.append(key, params[key]);
   126→            });
   127→            options.body = formData;
   128→        }
   129→
   130→        const response = await fetch(url, options);
   131→        const data = await response.json();
   132→
   133→        if (data.error) {
   134→            throw new Error(data.message || 'API Error');
   135→        }
   136→
   137→        return data;
   138→    } catch (error) {
   139→        console.error('API Error:', error);
   140→        throw error;
   141→    }
   142→}
   143→
   144→// ============================================
   145→// Loading Overlay
   146→// ============================================
   147→function showLoading(message = 'Processing...') {
   148→    document.getElementById('loading-message').textContent = message;
   149→    document.getElementById('loading-overlay').style.display = 'flex';
   150→}

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.


<persisted-output>
Output too large (127.6KB). Full output saved to: /root/.claude/projects/-var-www-mssql-danmarcrm-com-dev1-extension2/75ef92ac-556a-4223-9d55-17c4e535294d/tool-results/toolu_01FHYBwsvfyjDFWJfJUmLCuC.txt

Preview (first 2KB):
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 = $_REQUEST;
31-}
--
149-
150-// Load configuration
151-require_once dirname(__DIR__) . '/config/config.php';
152-require_once dirname(__DIR__) . '/vendor/autoload.php';
153-
154:use EmailIntelligence\Database;
155:use EmailIntelligence\QueryAdapter;
156:use EmailIntelligence\GmailClient;
157:use EmailIntelligence\EmailSync;
158:use EmailIntelligence\AIAnalyzer;
159:use EmailIntelligence\ThreadAnalyzer;
160:use EmailIntelligence\ContactAnalyzer;
161:use EmailIntelligence\ContactProfiler;
162:use EmailIntelligence\VectorMemory;
163:use EmailIntelligence\PatternDetector;
164:use EmailIntelligence\AlertSystem;
165:use EmailIntelligence\ThreadIdCache;
166-
167-file_put_contents('apiLogs.log', print_r($_REQUEST, true) . "\n", FILE_APPEND);
168-#exit("test");
169-
170-// Set JSON response headers
--
190-    }
191-    jsonResponse($response, $status);
192-}
193-
194-/**
195: * Log AI task execution (request, prompt, response)
196- */
197:function logAITask(string $taskName, array $request, string $prompt, string $response): void {
198:    $logDir = dirname(__DIR__) . '/logs/ai';
199-
...
</persisted-output>

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

find /var/www/mssql.danmarcrm.com/dev1/extension2/chrome-extensionCopyMac20260220/chrome-extension/ -type f -name "*.js" -o -name "*.html" -o -name "*.json" | head -30

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

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

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


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

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

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


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

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

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


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

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

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


1→<!DOCTYPE html>
     2→
     3→
     4→
     5→  <meta charset="UTF-8">
     6→  <title>Email Intelligence</title>
     7→
   343→
   344→
   345→
   346→
📊 Email Intelligence

   347→
   348→
Loading stats...

   349→
   350→

   351→
   352→

   353→
📈 Analysis Status

   354→

   355→
0%

   356→

   357→

   358→        ✅ 0 Done
   359→        ⏳ 0 Pending
   360→        📊 0 Total
   361→

   362→

   363→
   364→
   365→

   366→

   367→
Unread Alerts

   368→
0

   369→

   370→

   371→
Critical Issues

   372→
0

   373→

   374→

   375→
   376→
   377→

   378→      <button class="tab-btn active" data-tab="search">🔍 Search</button>
   379→      <button class="tab-btn" data-tab="askai">🤖 Ask AI</button>
   380→      <button class="tab-btn" data-tab="enrich">🔬 Enrich</button>
   381→      <button class="tab-btn" data-tab="filter">📧 Filter</button>
   382→      <button class="tab-btn" data-tab="actions">⚡ Actions</button>
   383→

   384→
   385→
   386→

   387→

   388→        <input type="text" class="search-input" id="contact-search" placeholder="Search contacts by name or email...">
   389→

   390→

   391→

   392→
   393→
   394→

   395→

   396→
🤖 Ask AI About Emails

   397→
   398→
   399→

   400→

   401→            🏢 Provider
   402→            <select id="ai-provider" class="search-input" style="margin-bottom: 0; padding: 8px; font-size: 12px;">
   403→              <option value="claude" selected>Claude</option>
   404→              <option value="openai">OpenAI</option>
   405→              <option value="gemini">Gemini</option>
   406→              <option value="grok">Grok</option>
   407→              <option value="deepseek">DeepSeek</option>
   408→              <option value="qwen">Qwen</option>
   409→              <option value="mistral">Mistral</option>
   410→              <option value="cohere">Cohere</option>
   411→            </select>
   412→

   413→

   414→            🧠 Model
   415→            <select id="ai-model" class="search-input" style="margin-bottom: 0; padding: 8px; font-size: 12px;">
   416→
   417→            </select>
   418→

   419→

   420→
   421→
   422→

   423→          Using: Claude / Sonnet 4.5
   424→          Ready
   425→

   426→
   427→
   428→

   429→          📧 Context (optional)
   430→          <input type="text" class="search-input" id="ai-context-input"
   431→            placeholder="Email address or thread ID for specific context..." style="margin-bottom: 0; padding: 8px; font-size: 12px;">
   432→

   433→
   434→
   435→

   436→          Your Question
   437→          <textarea id="ai-question-input" class="search-input"
   438→            placeholder="What would you like to know?

Examples:
- What did John say about the project?
- Summarize my recent conversations
- Find quotes over $5000"
   439→            style="height: 80px; resize: vertical; margin-bottom: 0; font-family: inherit;"></textarea>
   440→

   441→
   442→
   443→        <button class="action-btn" id="submit-ai-question-btn"
   444→          style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white;">
   445→          🚀 Ask AI
   446→        </button>
   447→
   448→
   449→

   450→

   451→

   452→              AI Response
   453→
   454→

   455→

   457→

   458→

   459→

   460→
   461→
   462→

   463→

   465→

   466→          Analyzing...
   467→

   468→
   469→
   470→

   472→          ❌
   473→
   474→

   475→
   476→
   477→

   478→          Quick Questions:
   479→

   480→            <button class="quick-question-btn" data-question="Summarize my recent important emails"
   481→              style="background: rgba(255,255,255,0.1); border: 1px solid rgba(255,255,255,0.2); border-radius: 4px; padding: 4px 8px; font-size: 10px; color: white; cursor: pointer;">📋
   482→              Summary</button>
   483→            <button class="quick-question-btn" data-question="What urgent matters need my attention?"
   484→              style="background: rgba(255,255,255,0.1); border: 1px solid rgba(255,255,255,0.2); border-radius: 4px; padding: 4px 8px; font-size: 10px; color: white; cursor: pointer;">🔥
   485→              Urgent</button>
   486→            <button class="quick-question-btn" data-question="Find any pricing quotes or proposals"
   487→              style="background: rgba(255,255,255,0.1); border: 1px solid rgba(255,255,255,0.2); border-radius: 4px; padding: 4px 8px; font-size: 10px; color: white; cursor: pointer;">💰
   488→              Quotes</button>
   489→            <button class="quick-question-btn" data-question="What follow-ups are pending?"
   490→              style="background: rgba(255,255,255,0.1); border: 1px solid rgba(255,255,255,0.2); border-radius: 4px; padding: 4px 8px; font-size: 10px; color: white; cursor: pointer;">📅
   491→              Follow-ups</button>
   492→

   493→

   494→

   495→

   496→
   497→
   498→

   499→

   501→
🔬 Data Enrichment

   502→
   503→
   504→

   505→          <input type="text" class="search-input" id="enrich-email" placeholder="Enter email to enrich..."
   506→            style="margin-bottom: 8px;">
   507→          <button class="action-btn" id="enrich-contact-btn" style="background: #10b981; color: white;">
   508→            🔍 Enrich Contact
   509→          </button>
   510→

   511→
   512→
   513→

   514→          <input type="text" class="search-input" id="enrich-domain" placeholder="Enter company domain..."
   515→            style="margin-bottom: 8px;">
   516→          <button class="action-btn" id="enrich-company-btn" style="background: #3b82f6; color: white;">
   517→            🏢 Enrich Company
   518→          </button>
   519→

   520→
   521→
   522→

   523→          <button class="quick-btn" id="enrich-all-contacts-btn">
   524→            👥
   525→            Enrich All Contacts
   526→          </button>
   527→          <button class="quick-btn" id="enrich-all-companies-btn">
   528→            🏢
   529→            Enrich All Companies
   530→          </button>
   531→

   532→
   533→
   534→

   536→
Ready to enrich

   537→

   538→
   539→
   540→

   541→          Queue: 0 pending, 0 processing
   542→

   543→

   544→

   545→
   546→
   547→

   548→

   549→
📧 Count Emails for Filter

   550→

   551→          <input type="text" class="filter-input" id="filter-domain" placeholder="@domain.com or email">
   552→          <button class="filter-btn" id="count-filter-btn">Count</button>
   553→

   554→

   555→

   556→

   557→
   558→
   559→

   560→

   561→        <button class="quick-btn" id="open-contacts-btn">
   562→          👥
   563→          View Contacts
   564→        </button>
   565→        <button class="quick-btn" id="open-analysis-btn">
   566→          🤖
   567→          AI Analysis
   568→        </button>
   569→        <button class="quick-btn" id="trigger-sync-btn">
   570→          🔄
   571→          Sync Emails
   572→        </button>
   573→        <button class="quick-btn" id="trigger-analyze-btn">
   574→          🧠
   575→          Run Analysis
   576→        </button>
   577→

   578→

   579→
   580→
   581→    <button class="action-btn" id="open-dashboard-btn">
   582→      🏠 Open Full Dashboard
   583→    </button>
   584→
   585→    <button class="action-btn secondary" id="refresh-btn">
   586→      🔄 Refresh Stats
   587→    </button>
   588→
   589→
v2.1.0 | Build 2024.12.30.1

   590→

   591→
   592→
   593→
   594→
   595→

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

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

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


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

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

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


1→// Popup script for Email Intelligence extension
     2→"use strict";
     3→
     4→const API_BASE = 'https://mssql.danmarcrm.com/dev1/extension2v1/public/api.php';
     5→const DASHBOARD_URL = 'https://mssql.danmarcrm.com/dev1/extension2v1/public/';
     6→
     7→// ============================================
     8→// Stats Loading
     9→// ============================================
    10→async function loadStats() {
    11→  try {
    12→    // Load alert stats
    13→    const alertResponse = await fetch(`${API_BASE}?action=alert_stats`);
    14→    const alertData = await alertResponse.json();
    15→
    16→    document.getElementById('unread-alerts').textContent = alertData.unread || 0;
    17→    document.getElementById('critical-alerts').textContent = alertData.critical || 0;
    18→
    19→    // Load analysis status
    20→    const analysisResponse = await fetch(`${API_BASE}?action=analysis_status`);
    21→    const analysisData = await analysisResponse.json();
    22→
    23→    const analyzed = analysisData.analyzed || 0;
    24→    const pending = analysisData.pending || 0;
    25→    const total = analysisData.total_threads || 0;
    26→    const percent = analysisData.percent_complete || 0;
    27→
    28→    document.getElementById('stat-analyzed').textContent = analyzed;
    29→    document.getElementById('stat-pending').textContent = pending;
    30→    document.getElementById('stat-total').textContent = total;
    31→
    32→    const progressEl = document.getElementById('analysis-progress');
    33→    progressEl.style.width = `${Math.max(percent, 5)}%`;
    34→    progressEl.textContent = `${percent}%`;
    35→
    36→    document.getElementById('loading').style.display = 'none';
    37→    document.getElementById('content').style.display = 'block';
    38→
    39→  } catch (error) {
    40→    console.error('Error loading stats:', error);
    41→    document.getElementById('loading').textContent = 'Error loading stats';
    42→  }
    43→}
    44→
    45→// ============================================
    46→// Contact Search
    47→// ============================================
    48→let searchTimeout = null;
    49→
    50→async function searchContacts(query) {
    51→  if (!query || query.length < 2) {
    52→    document.getElementById('search-results').classList.remove('show');
    53→    return;
    54→  }
    55→
    56→  try {
    57→    const response = await fetch(`${API_BASE}?action=contacts&search=${encodeURIComponent(query)}&limit=10`);
    58→    const data = await response.json();
    59→
    60→    const resultsEl = document.getElementById('search-results');
    61→
    62→    if (data.contacts && data.contacts.length > 0) {
    63→      let html = '';
    64→      data.contacts.forEach(contact => {
    65→        const riskBadge = contact.risk_level ?
    66→          `<span class="badge badge-${contact.risk_level}">${contact.risk_level}</span>` : '';
    67→
    68→        html += `
    69→

    70→
${escapeHtml(contact.name || contact.email)}${riskBadge}

    71→
${escapeHtml(contact.email)}

    72→

    73→        `;
    74→      });
    75→      resultsEl.innerHTML = html;
    76→      resultsEl.classList.add('show');
    77→
    78→      // Add click handlers
    79→      resultsEl.querySelectorAll('.search-result-item').forEach(item => {
    80→        item.addEventListener('click', () => {
    81→          const contactId = item.dataset.contactId;
    82→          openContactDetail(contactId);
    83→        });
    84→      });
    85→    } else {
    86→      resultsEl.innerHTML = '

No contacts found

';
    87→      resultsEl.classList.add('show');
    88→    }
    89→  } catch (error) {
    90→    console.error('Search error:', error);
    91→  }
    92→}
    93→
    94→function openContactDetail(contactId) {
    95→  chrome.tabs.create({
    96→    url: `${DASHBOARD_URL}contact_dashboard.php?contact=${contactId}`
    97→  });
    98→}
    99→
   100→// ============================================
   101→// Filter Email Count
   102→// ============================================
   103→async function countFilterEmails() {
   104→  const domain = document.getElementById('filter-domain').value.trim();
   105→  if (!domain) {
   106→    showFilterResult('Please enter a domain or email address', 'error');
   107→    return;
   108→  }
   109→
   110→  const btn = document.getElementById('count-filter-btn');
   111→  btn.textContent = 'Counting...';
   112→  btn.disabled = true;
   113→
   114→  try {
   115→    const response = await fetch(`${API_BASE}?action=count_filter_emails&domain=${encodeURIComponent(domain)}`);
   116→    const data = await response.json();
   117→
   118→    if (data.error) {
   119→      showFilterResult(data.message || 'Error counting emails', 'error');
   120→    } else {
   121→      showFilterResult(`
   122→        ${escapeHtml(domain)}

   123→        📧 Emails: ${data.email_count || 0}

   124→        🧵 Threads: ${data.thread_count || 0}

   125→        👥 Contacts: ${data.contact_count || 0}
   126→      `, 'success');
   127→    }
   128→  } catch (error) {
   129→    showFilterResult('Error: ' + error.message, 'error');
   130→  } finally {
   131→    btn.textContent = 'Count';
   132→    btn.disabled = false;
   133→  }
   134→}
   135→
   136→function showFilterResult(message, type) {
   137→  const resultEl = document.getElementById('filter-result');
   138→  resultEl.innerHTML = message;
   139→  resultEl.classList.add('show');
   140→}
   141→
   142→// ============================================
   143→// Quick Actions
   144→// ============================================
   145→async function triggerSync() {
   146→  const btn = event.target;
   147→  const originalText = btn.innerHTML;
   148→  btn.innerHTML = '⏳Syncing...';
   149→  btn.disabled = true;
   150→
   151→  try {
   152→    const response = await fetch(`${API_BASE}?action=sync`, {
   153→      method: 'POST',
   154→      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
   155→      body: 'mode=incremental&max=100'
   156→    });
   157→    const data = await response.json();
   158→
   159→    if (data.success) {
   160→      alert(`Sync completed!\n\nNew emails: ${data.stats?.new_emails || 0}\nUpdated: ${data.stats?.updated || 0}`);
   161→      loadStats();
   162→    } else {
   163→      alert('Sync error: ' + (data.message || 'Unknown error'));
   164→    }
   165→  } catch (error) {
   166→    alert('Sync failed: ' + error.message);
   167→  } finally {
   168→    btn.innerHTML = originalText;
   169→    btn.disabled = false;
   170→  }
   171→}
   172→
   173→async function triggerAnalysis() {
   174→  const btn = event.target;
   175→  const originalText = btn.innerHTML;
   176→  btn.innerHTML = '⏳Analyzing...';
   177→  btn.disabled = true;
   178→
   179→  try {
   180→    const response = await fetch(`${API_BASE}?action=analyze`, {
   181→      method: 'POST',
   182→      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
   183→      body: 'batch=10'
   184→    });
   185→    const data = await response.json();
   186→
   187→    if (data.success) {
   188→      alert(`Analysis completed!\n\n${data.message}`);
   189→      loadStats();
   190→    } else {
   191→      alert('Analysis error: ' + (data.message || 'Unknown error'));
   192→    }
   193→  } catch (error) {
   194→    alert('Analysis failed: ' + error.message);
   195→  } finally {
   196→    btn.innerHTML = originalText;
   197→    btn.disabled = false;
   198→  }
   199→}
   200→
   201→// ============================================
   202→// Data Enrichment
   203→// ============================================
   204→async function enrichContact() {
   205→  const email = document.getElementById('enrich-email').value.trim();
   206→  if (!email) {
   207→    showEnrichStatus('Please enter an email address', 'error');
   208→    return;
   209→  }
   210→
   211→  const btn = document.getElementById('enrich-contact-btn');
   212→  const originalText = btn.textContent;
   213→  btn.textContent = '⏳ Enriching...';
   214→  btn.disabled = true;
   215→
   216→  try {
   217→    const response = await fetch(`${API_BASE}?action=enrich_contact`, {
   218→      method: 'POST',
   219→      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
   220→      body: `email=${encodeURIComponent(email)}`
   221→    });
   222→    const data = await response.json();
   223→
   224→    if (data.success) {
   225→      const sourcesUsed = data.sources_used?.join(', ') || 'none';
   226→      showEnrichStatus(`✅ Contact enriched! Sources: ${sourcesUsed}`, 'success');
   227→      document.getElementById('enrich-email').value = '';
   228→    } else {
   229→      showEnrichStatus(`❌ ${data.error || 'Enrichment failed'}`, 'error');
   230→    }
   231→  } catch (error) {
   232→    showEnrichStatus('❌ Error: ' + error.message, 'error');
   233→  } finally {
   234→    btn.textContent = originalText;
   235→    btn.disabled = false;
   236→  }
   237→}
   238→
   239→async function enrichCompany() {
   240→  const domain = document.getElementById('enrich-domain').value.trim();
   241→  if (!domain) {
   242→    showEnrichStatus('Please enter a company domain', 'error');
   243→    return;
   244→  }
   245→
   246→  const btn = document.getElementById('enrich-company-btn');
   247→  const originalText = btn.textContent;
   248→  btn.textContent = '⏳ Enriching...';
   249→  btn.disabled = true;
   250→
   251→  try {
   252→    const response = await fetch(`${API_BASE}?action=enrich_company`, {
   253→      method: 'POST',
   254→      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
   255→      body: `domain=${encodeURIComponent(domain)}`
   256→    });
   257→    const data = await response.json();
   258→
   259→    if (data.success) {
   260→      const sourcesUsed = data.sources_used?.join(', ') || 'none';
   261→      showEnrichStatus(`✅ Company enriched! Sources: ${sourcesUsed}`, 'success');
   262→      document.getElementById('enrich-domain').value = '';
   263→    } else {
   264→      showEnrichStatus(`❌ ${data.error || 'Enrichment failed'}`, 'error');
   265→    }
   266→  } catch (error) {
   267→    showEnrichStatus('❌ Error: ' + error.message, 'error');
   268→  } finally {
   269→    btn.textContent = originalText;
   270→    btn.disabled = false;
   271→  }
   272→}
   273→
   274→async function enrichAllContacts() {
   275→  if (!confirm('This will queue all contacts for enrichment. Continue?')) return;
   276→
   277→  const btn = document.getElementById('enrich-all-contacts-btn');
   278→  btn.innerHTML = '⏳Queuing...';
   279→  btn.disabled = true;
   280→
   281→  try {
   282→    const response = await fetch(`${API_BASE}?action=enrich_all_contacts`, {
   283→      method: 'POST',
   284→      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
   285→      body: 'priority=3'
   286→    });
   287→    const data = await response.json();
   288→
   289→    if (data.success) {
   290→      showEnrichStatus(`✅ ${data.queued || 0} contacts queued for enrichment`, 'success');
   291→      loadEnrichmentQueue();
   292→    } else {
   293→      showEnrichStatus(`❌ ${data.error || 'Failed to queue'}`, 'error');
   294→    }
   295→  } catch (error) {
   296→    showEnrichStatus('❌ Error: ' + error.message, 'error');
   297→  } finally {
   298→    btn.innerHTML = '👥Enrich All Contacts';
   299→    btn.disabled = false;
   300→  }
   301→}
   302→
   303→async function enrichAllCompanies() {
   304→  if (!confirm('This will queue all companies for enrichment. Continue?')) return;
   305→
   306→  const btn = document.getElementById('enrich-all-companies-btn');
   307→  btn.innerHTML = '⏳Queuing...';
   308→  btn.disabled = true;
   309→
   310→  try {
   311→    const response = await fetch(`${API_BASE}?action=enrich_all_companies`, {
   312→      method: 'POST',
   313→      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
   314→      body: 'priority=3'
   315→    });
   316→    const data = await response.json();
   317→
   318→    if (data.success) {
   319→      showEnrichStatus(`✅ ${data.queued || 0} companies queued for enrichment`, 'success');
   320→      loadEnrichmentQueue();
   321→    } else {
   322→      showEnrichStatus(`❌ ${data.error || 'Failed to queue'}`, 'error');
   323→    }
   324→  } catch (error) {
   325→    showEnrichStatus('❌ Error: ' + error.message, 'error');
   326→  } finally {
   327→    btn.innerHTML = '🏢Enrich All Companies';
   328→    btn.disabled = false;
   329→  }
   330→}
   331→
   332→async function loadEnrichmentQueue() {
   333→  try {
   334→    const response = await fetch(`${API_BASE}?action=enrichment_queue`);
   335→    const data = await response.json();
   336→
   337→    if (data.success && data.queue) {
   338→      document.getElementById('queue-pending').textContent = data.queue.pending || 0;
   339→      document.getElementById('queue-processing').textContent = data.queue.processing || 0;
   340→    }
   341→  } catch (error) {
   342→    console.error('Error loading enrichment queue:', error);
   343→  }
   344→}
   345→
   346→function showEnrichStatus(message, type = 'info') {
   347→  const statusEl = document.getElementById('enrich-status');
   348→  const textEl = document.getElementById('enrich-status-text');
   349→  textEl.innerHTML = message;
   350→  statusEl.style.display = 'block';
   351→  statusEl.style.background = type === 'error' ? 'rgba(239,68,68,0.2)' :
   352→    type === 'success' ? 'rgba(16,185,129,0.2)' :
   353→      'rgba(255,255,255,0.1)';
   354→}
   355→
   356→// ============================================
   357→// AI Questioning
   358→// ============================================
   359→const AI_API_BASE = 'https://mssql.danmarcrm.com/dev1/extension2v1/aiapi/api_opus/api/query.php';
   360→
   361→// Version for tracking updates
   362→const EXTENSION_VERSION = 'v2.1.0';
   363→const EXTENSION_BUILD = '2024.12.30.1';
   364→
   365→// Provider to model mapping (synced with api_keys.php - Dec 30, 2024)
   366→const PROVIDER_MODELS = {
   367→  claude: [
   368→    { id: 'claude-sonnet-4-5-20250929', name: 'Sonnet 4.5' },
   369→    { id: 'claude-opus-4-5-20251101', name: 'Opus 4.5 (Best)' },
   370→    { id: 'claude-haiku-4-5-20251001', name: 'Haiku 4.5 (Fast)' }
   371→  ],
   372→  openai: [
   373→    { id: 'gpt-5.2', name: 'GPT-5.2 (Latest)' },
   374→    { id: 'gpt-5-mini', name: 'GPT-5 Mini' },
   375→    { id: 'gpt-5-nano', name: 'GPT-5 Nano (Fast)' },
   376→    { id: 'gpt-5.2-pro', name: 'GPT-5.2 Pro (Best)' },
   377→    { id: 'gpt-5', name: 'GPT-5' },
   378→    { id: 'gpt-4.1', name: 'GPT-4.1' }
   379→  ],
   380→  gemini: [
   381→    { id: 'gemini-3-pro', name: 'Gemini 3 Pro (Latest)' },
   382→    { id: 'gemini-3-flash', name: 'Gemini 3 Flash' },
   383→    { id: 'gemini-2.5-pro', name: 'Gemini 2.5 Pro' },
   384→    { id: 'gemini-2.5-flash', name: 'Gemini 2.5 Flash' },
   385→    { id: 'gemini-2.5-flash-lite', name: 'Gemini 2.5 Flash-Lite (Fast)' }
   386→  ],
   387→  grok: [
   388→    { id: 'grok-4', name: 'Grok 4 (Latest)' },
   389→    { id: 'grok-3', name: 'Grok 3' },
   390→    { id: 'grok-3-mini', name: 'Grok 3 Mini' },
   391→    { id: 'grok-2-latest', name: 'Grok 2' }
   392→  ],
   393→  deepseek: [
   394→    { id: 'deepseek-chat', name: 'V3.2 Chat' },
   395→    { id: 'deepseek-reasoner', name: 'V3.2 Reasoner (Thinking)' }
   396→  ],
   397→  qwen: [
   398→    { id: 'qwen-max-latest', name: 'Qwen Max' },
   399→    { id: 'qwen-plus-latest', name: 'Qwen Plus' },
   400→    { id: 'qwen-turbo-latest', name: 'Qwen Turbo (Fast)' },
   401→    { id: 'qwq-32b', name: 'QwQ 32B (Reasoning)' }
   402→  ],
   403→  mistral: [
   404→    { id: 'mistral-large-latest', name: 'Large (Latest)' },
   405→    { id: 'mistral-medium-latest', name: 'Medium' },
   406→    { id: 'mistral-small-latest', name: 'Small' },
   407→    { id: 'codestral-latest', name: 'Codestral (Code)' }
   408→  ],
   409→  cohere: [
   410→    { id: 'command-a-03-2025', name: 'Command A (Latest)' },
   411→    { id: 'command-r7b-12-2024', name: 'Command R7B' },
   412→    { id: 'command-r-plus-08-2024', name: 'Command R+' }
   413→  ]
   414→};
   415→
   416→// Provider display names
   417→const PROVIDER_NAMES = {
   418→  claude: 'Claude',
   419→  openai: 'OpenAI',
   420→  gemini: 'Gemini',
   421→  grok: 'Grok',
   422→  deepseek: 'DeepSeek',
   423→  qwen: 'Qwen',
   424→  mistral: 'Mistral',
   425→  cohere: 'Cohere'
   426→};
   427→
   428→// ============================================
   429→// Conversation Memory (ChatGPT-like)
   430→// ============================================
   431→let conversationHistory = [];
   432→const MAX_CONVERSATION_HISTORY = 10;
   433→
   434→function loadAIConversationHistory() {
   435→  const stored = localStorage.getItem('ai_extension_conversation');
   436→  if (stored) {
   437→    try {
   438→      conversationHistory = JSON.parse(stored);
   439→    } catch (e) {
   440→      conversationHistory = [];
   441→    }
   442→  }
   443→}
   444→
   445→function saveAIConversationHistory() {
   446→  localStorage.setItem('ai_extension_conversation', JSON.stringify(conversationHistory));
   447→}
   448→
   449→function addToAIConversation(question, answer, provider, model) {
   450→  conversationHistory.push({
   451→    timestamp: new Date().toISOString(),
   452→    question: question,
   453→    answer: answer,
   454→    provider: provider,
   455→    model: model
   456→  });
   457→
   458→  if (conversationHistory.length > MAX_CONVERSATION_HISTORY) {
   459→    conversationHistory = conversationHistory.slice(-MAX_CONVERSATION_HISTORY);
   460→  }
   461→
   462→  saveAIConversationHistory();
   463→  updateAIConversationDisplay();
   464→}
   465→
   466→function clearAIConversationHistory() {
   467→  if (confirm('Clear all AI conversation history?')) {
   468→    conversationHistory = [];
   469→    saveAIConversationHistory();
   470→    updateAIConversationDisplay();
   471→  }
   472→}
   473→
   474→function buildAIConversationContext() {
   475→  if (conversationHistory.length === 0) return '';
   476→
   477→  let context = '\n\n=== PREVIOUS CONVERSATION HISTORY ===\n';
   478→  context += '(Use this context for continuity with previous questions.)\n\n';
   479→
   480→  conversationHistory.forEach((entry, index) => {
   481→    context += `--- Exchange ${index + 1} ---\n`;
   482→    context += `USER: ${entry.question}\n`;
   483→    context += `AI (${entry.provider}): ${entry.answer.substring(0, 500)}${entry.answer.length > 500 ? '...' : ''}\n\n`;
   484→  });
   485→
   486→  context += '=== END OF HISTORY ===\n\n';
   487→  return context;
   488→}
   489→
   490→function updateAIConversationDisplay() {
   491→  let historyContainer = document.getElementById('ai-conversation-history');
   492→
   493→  if (conversationHistory.length === 0) {
   494→    if (historyContainer) historyContainer.style.display = 'none';
   495→    return;
   496→  }
   497→
   498→  if (!historyContainer) {
   499→    const askaiSection = document.querySelector('#tab-askai .askai-section');
   500→    if (askaiSection) {
   501→      historyContainer = document.createElement('div');
   502→      historyContainer.id = 'ai-conversation-history';
   503→      historyContainer.style.cssText = 'margin-top: 12px; background: rgba(255,255,255,0.1); border-radius: 6px; padding: 10px;';
   504→      askaiSection.appendChild(historyContainer);
   505→    }
   506→  }
   507→
   508→  if (historyContainer) {
   509→    historyContainer.style.display = 'block';
   510→    historyContainer.innerHTML = `
   511→

   512→        💬 History (${conversationHistory.length})
   513→        <button onclick="clearAIConversationHistory()" style="background: rgba(255,255,255,0.2); border: none; color: white; padding: 2px 8px; border-radius: 4px; font-size: 10px; cursor: pointer;">Clear</button>
   514→

   515→

   516→        ${conversationHistory.slice().reverse().slice(0, 3).map(entry => `
   517→

   518→
Q: ${escapeHtml(entry.question.substring(0, 50))}${entry.question.length > 50 ? '...' : ''}

   519→
A: ${escapeHtml(entry.answer.substring(0, 80))}${entry.answer.length > 80 ? '...' : ''}

   520→

   521→        `).join('')}
   522→

   523→    `;
   524→  }
   525→}
   526→
   527→// Update model dropdown based on selected provider
   528→function updateModelDropdown() {
   529→  const provider = document.getElementById('ai-provider')?.value || 'claude';
   530→  const modelSelect = document.getElementById('ai-model');
   531→  if (!modelSelect) return;
   532→
   533→  const models = PROVIDER_MODELS[provider] || PROVIDER_MODELS.claude;
   534→  modelSelect.innerHTML = models.map(model =>
   535→    `<option value="${model.id}">${model.name}</option>`
   536→  ).join('');
   537→
   538→  // Update the display
   539→  updateAISelectionDisplay();
   540→}
   541→
   542→// Update the AI selection display text
   543→function updateAISelectionDisplay() {
   544→  const provider = document.getElementById('ai-provider')?.value || 'claude';
   545→  const modelSelect = document.getElementById('ai-model');
   546→  const displayEl = document.getElementById('current-ai-display');
   547→
   548→  if (!displayEl || !modelSelect) return;
   549→
   550→  const providerName = PROVIDER_NAMES[provider] || provider;
   551→  const modelOption = modelSelect.options[modelSelect.selectedIndex];
   552→  const modelName = modelOption ? modelOption.text : 'Unknown';
   553→
   554→  displayEl.textContent = `${providerName} / ${modelName}`;
   555→}
   556→
   557→// Fetch email content for context
   558→async function fetchEmailContext(contextInput) {
   559→  if (!contextInput) return null;
   560→
   561→  try {
   562→    // Check if it looks like a thread ID (hex string) or email
   563→    const isThreadId = /^[0-9a-f]{16,}$/i.test(contextInput);
   564→    const isEmail = contextInput.includes('@');
   565→
   566→    if (isThreadId) {
   567→      // Fetch thread details
   568→      const response = await fetch(`${API_BASE}?action=thread&thread_id=${encodeURIComponent(contextInput)}`);
   569→      const data = await response.json();
   570→
   571→      if (data.emails && data.emails.length > 0) {
   572→        let content = `\n\n=== EMAIL THREAD CONTEXT ===\n`;
   573→        content += `Subject: ${data.emails[0].subject || '(No Subject)'}\n`;
   574→        content += `Emails in thread: ${data.emails.length}\n\n`;
   575→
   576→        data.emails.forEach((email, idx) => {
   577→          const sender = email.from_name || email.from_email || 'Unknown';
   578→          content += `--- Email ${idx + 1} from ${sender} (${email.date || 'unknown date'}) ---\n`;
   579→          content += (email.body_text || email.body_html || '(No content)').substring(0, 1000);
   580→          if ((email.body_text || email.body_html || '').length > 1000) content += '...(truncated)';
   581→          content += '\n\n';
   582→        });
   583→
   584→        content += `=== END OF THREAD ===\n`;
   585→        return content;
   586→      }
   587→    } else if (isEmail) {
   588→      // Fetch contact's recent threads
   589→      const response = await fetch(`${API_BASE}?action=contacts&search=${encodeURIComponent(contextInput)}&limit=1`);
   590→      const data = await response.json();
   591→
   592→      if (data.contacts && data.contacts.length > 0) {
   593→        const contact = data.contacts[0];
   594→        let content = `\n\n=== CONTACT CONTEXT ===\n`;
   595→        content += `Name: ${contact.name || 'Unknown'}\n`;
   596→        content += `Email: ${contact.email}\n`;
   597→        content += `Company: ${contact.company || 'Unknown'}\n`;
   598→
   599→        // Fetch their threads
   600→        const threadsResponse = await fetch(`${API_BASE}?action=threads&contact_id=${contact.id}&limit=3`);
   601→        const threadsData = await threadsResponse.json();
   602→
   603→        if (threadsData.threads && threadsData.threads.length > 0) {
   604→          content += `\nRecent threads (${threadsData.threads.length}):\n`;
   605→          for (const thread of threadsData.threads) {
   606→            content += `- ${thread.subject || '(No Subject)'} (${thread.email_count || 0} emails, ${thread.last_date || 'unknown date'})\n`;
   607→          }
   608→        }
   609→
   610→        content += `=== END OF CONTACT ===\n`;
   611→        return content;
   612→      }
   613→    }
   614→  } catch (error) {
   615→    console.error('Error fetching email context:', error);
   616→  }
   617→
   618→  return null;
   619→}
   620→
   621→// Ask AI a question
   622→async function askAIQuestion() {
   623→  const question = document.getElementById('ai-question-input')?.value?.trim();
   624→  const contextInput = document.getElementById('ai-context-input')?.value?.trim();
   625→  const provider = document.getElementById('ai-provider')?.value || 'claude';
   626→  const model = document.getElementById('ai-model')?.value || 'claude-sonnet-4-5-20250514';
   627→
   628→  if (!question) {
   629→    showAIError('Please enter a question');
   630→    return;
   631→  }
   632→
   633→  // Show loading, hide error and response
   634→  document.getElementById('ai-loading').style.display = 'block';
   635→  document.getElementById('ai-error').style.display = 'none';
   636→  document.getElementById('ai-response-area').style.display = 'none';
   637→  document.getElementById('submit-ai-question-btn').disabled = true;
   638→
   639→  try {
   640→    // Build context message
   641→    let fullContent = `You are an AI assistant helping analyze email conversations and data.\n\n`;
   642→
   643→    // Add conversation history for continuity (ChatGPT-like memory)
   644→    const conversationContext = buildAIConversationContext();
   645→    if (conversationContext) {
   646→      fullContent += conversationContext;
   647→      console.log('Including conversation history:', conversationHistory.length, 'exchanges');
   648→    }
   649→
   650→    // Fetch email context if provided
   651→    if (contextInput) {
   652→      document.getElementById('ai-loading').querySelector('span').textContent = 'Loading email context...';
   653→      const emailContext = await fetchEmailContext(contextInput);
   654→      if (emailContext) {
   655→        fullContent += emailContext;
   656→      } else {
   657→        fullContent += `\nCONTEXT: User is asking about: ${contextInput}\n\n`;
   658→      }
   659→    }
   660→
   661→    fullContent += `\nCURRENT USER QUESTION:\n${question}\n\n`;
   662→    fullContent += `Please provide a helpful, concise answer. Consider any previous conversation context when answering.`;
   663→
   664→    const requestBody = {
   665→      user_content: fullContent,
   666→      providers: [provider],
   667→      [`model_${provider}`]: model
   668→    };
   669→
   670→    console.log('Sending AI request:', { provider, model, question: question.substring(0, 100), historyCount: conversationHistory.length });
   671→    document.getElementById('ai-loading').querySelector('span').textContent = 'Analyzing...';
   672→
   673→    const response = await fetch(AI_API_BASE, {
   674→      method: 'POST',
   675→      headers: { 'Content-Type': 'application/json' },
   676→      body: JSON.stringify(requestBody)
   677→    });
   678→
   679→    const data = await response.json();
   680→    console.log('AI Response:', data);
   681→
   682→    if (data.success && data.responses) {
   683→      const providerResponse = data.responses[`${provider}_response`];
   684→
   685→      if (providerResponse && providerResponse.success) {
   686→        // Show response
   687→        document.getElementById('ai-response-provider').textContent = `${provider.toUpperCase()} Response`;
   688→        document.getElementById('ai-response-meta').textContent =
   689→          `${model} | ${providerResponse.request_time?.toFixed(2) || '?'}s | $${providerResponse.cost?.toFixed(5) || '0'}`;
   690→        document.getElementById('ai-response-text').textContent = providerResponse.response || 'No response content';
   691→        document.getElementById('ai-response-area').style.display = 'block';
   692→
   693→        // Add to conversation history (ChatGPT-like memory)
   694→        if (providerResponse.response) {
   695→          addToAIConversation(question, providerResponse.response, provider, model);
   696→        }
   697→
   698→        // Clear the question input for next question
   699→        document.getElementById('ai-question-input').value = '';
   700→      } else {
   701→        showAIError(providerResponse?.error || 'Provider returned an error');
   702→      }
   703→    } else {
   704→      showAIError(data.error || 'Failed to get AI response');
   705→    }
   706→
   707→  } catch (error) {
   708→    console.error('AI question error:', error);
   709→    showAIError('Network error: ' + error.message);
   710→  } finally {
   711→    document.getElementById('ai-loading').style.display = 'none';
   712→    document.getElementById('submit-ai-question-btn').disabled = false;
   713→  }
   714→}
   715→
   716→// Show AI error message
   717→function showAIError(message) {
   718→  document.getElementById('ai-error-text').textContent = message;
   719→  document.getElementById('ai-error').style.display = 'block';
   720→}
   721→
   722→// Handle quick question buttons
   723→function setQuickQuestion(question) {
   724→  document.getElementById('ai-question-input').value = question;
   725→}
   726→
   727→// ============================================
   728→// Tab Management
   729→// ============================================
   730→function switchTab(tabName) {
   731→  document.querySelectorAll('.tab-btn').forEach(btn => {
   732→    btn.classList.toggle('active', btn.dataset.tab === tabName);
   733→  });
   734→  document.querySelectorAll('.tab-content').forEach(content => {
   735→    content.classList.toggle('active', content.id === 'tab-' + tabName);
   736→  });
   737→
   738→  // Load enrichment queue when switching to enrich tab
   739→  if (tabName === 'enrich') {
   740→    loadEnrichmentQueue();
   741→  }
   742→
   743→  // Update model dropdown and show conversation history when switching to askai tab
   744→  if (tabName === 'askai') {
   745→    updateModelDropdown();
   746→    updateAIConversationDisplay();
   747→  }
   748→}
   749→
   750→// ============================================
   751→// Utility Functions
   752→// ============================================
   753→function escapeHtml(text) {
   754→  if (!text) return '';
   755→  const div = document.createElement('div');
   756→  div.textContent = text;
   757→  return div.innerHTML;
   758→}
   759→
   760→// ============================================
   761→// Event Listeners
   762→// ============================================
   763→document.addEventListener('DOMContentLoaded', () => {
   764→  // Load conversation history (ChatGPT-like memory)
   765→  loadAIConversationHistory();
   766→
   767→  // Initialize AI model dropdown immediately
   768→  updateModelDropdown();
   769→
   770→  // Tab switching
   771→  document.querySelectorAll('.tab-btn').forEach(btn => {
   772→    btn.addEventListener('click', () => switchTab(btn.dataset.tab));
   773→  });
   774→
   775→  // Contact search with debounce
   776→  document.getElementById('contact-search')?.addEventListener('input', (e) => {
   777→    clearTimeout(searchTimeout);
   778→    searchTimeout = setTimeout(() => searchContacts(e.target.value), 300);
   779→  });
   780→
   781→  // Filter count
   782→  document.getElementById('count-filter-btn')?.addEventListener('click', countFilterEmails);
   783→  document.getElementById('filter-domain')?.addEventListener('keypress', (e) => {
   784→    if (e.key === 'Enter') countFilterEmails();
   785→  });
   786→
   787→  // Quick action buttons
   788→  document.getElementById('open-contacts-btn')?.addEventListener('click', () => {
   789→    chrome.tabs.create({ url: DASHBOARD_URL });
   790→  });
   791→
   792→  document.getElementById('open-analysis-btn')?.addEventListener('click', () => {
   793→    chrome.tabs.create({ url: `${DASHBOARD_URL}ai_analysis.php` });
   794→  });
   795→
   796→  document.getElementById('trigger-sync-btn')?.addEventListener('click', triggerSync);
   797→  document.getElementById('trigger-analyze-btn')?.addEventListener('click', triggerAnalysis);
   798→
   799→  // Enrichment buttons
   800→  document.getElementById('enrich-contact-btn')?.addEventListener('click', enrichContact);
   801→  document.getElementById('enrich-company-btn')?.addEventListener('click', enrichCompany);
   802→  document.getElementById('enrich-all-contacts-btn')?.addEventListener('click', enrichAllContacts);
   803→  document.getElementById('enrich-all-companies-btn')?.addEventListener('click', enrichAllCompanies);
   804→
   805→  // Enrichment input enter key handlers
   806→  document.getElementById('enrich-email')?.addEventListener('keypress', (e) => {
   807→    if (e.key === 'Enter') enrichContact();
   808→  });
   809→  document.getElementById('enrich-domain')?.addEventListener('keypress', (e) => {
   810→    if (e.key === 'Enter') enrichCompany();
   811→  });
   812→
   813→  // AI Question handlers
   814→  document.getElementById('submit-ai-question-btn')?.addEventListener('click', askAIQuestion);
   815→  document.getElementById('ai-question-input')?.addEventListener('keypress', (e) => {
   816→    if (e.key === 'Enter' && e.ctrlKey) askAIQuestion();
   817→  });
   818→  document.getElementById('ai-provider')?.addEventListener('change', updateModelDropdown);
   819→  document.getElementById('ai-model')?.addEventListener('change', updateAISelectionDisplay);
   820→
   821→  // Quick question buttons
   822→  document.querySelectorAll('.quick-question-btn').forEach(btn => {
   823→    btn.addEventListener('click', () => {
   824→      setQuickQuestion(btn.dataset.question);
   825→    });
   826→  });
   827→
   828→  // Main buttons
   829→  document.getElementById('open-dashboard-btn')?.addEventListener('click', () => {
   830→    chrome.tabs.create({ url: DASHBOARD_URL });
   831→  });
   832→
   833→  document.getElementById('refresh-btn')?.addEventListener('click', loadStats);
   834→});
   835→
   836→// Load stats on popup open
   837→loadStats();
   838→
   839→

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

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

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


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

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

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