515→                ×
   516→

   517→

   518→

   519→
   520→
   521→

   522→
   523→

   524→

   525→                    🤖
   526→

   527→
AI Assistant

   528→
General Chat

   529→

   530→

   531→

   532→                    <button onclick="clearAiChat()" title="Clear chat" style="background:rgba(255,255,255,0.15); border:none; color:#fff; border-radius:6px; padding:4px 8px; cursor:pointer; font-size:0.75em;">🗑 Clear</button>
   533→                    <button onclick="toggleAiChat()" style="background:rgba(255,255,255,0.15); border:none; color:#fff; border-radius:6px; padding:4px 8px; cursor:pointer; font-size:1em;">✕</button>
   534→

   535→

   536→
   537→
   538→

   539→

   540→                    MODEL
   541→                    <select id="ai-chat-model" style="flex:1; background:#1e1e2e; color:#e2e8f0; border:1px solid #3d3d5c; border-radius:6px; padding:4px 8px; font-size:0.78em; cursor:pointer;">
   542→                        <optgroup label="OpenAI">
   543→                            <option value="gpt-4o">GPT-4o (Latest)</option>
   544→                            <option value="gpt-4o-mini">GPT-4o Mini (Fast)</option>
   545→                            <option value="o1">o1 (Reasoning)</option>
   546→                            <option value="o1-mini">o1-mini</option>
   547→                        </optgroup>
   548→                        <optgroup label="Anthropic Claude">
   549→                            <option value="claude-3-5-sonnet-20241022">Claude 3.5 Sonnet</option>
   550→                            <option value="claude-3-5-haiku-20241022">Claude 3.5 Haiku (Fast)</option>
   551→                            <option value="claude-3-opus-20240229">Claude 3 Opus</option>
   552→                        </optgroup>
   553→                        <optgroup label="Google Gemini">
   554→                            <option value="gemini-2.0-flash-exp">Gemini 2.0 Flash</option>
   555→                            <option value="gemini-1.5-pro">Gemini 1.5 Pro</option>
   556→                            <option value="gemini-1.5-flash">Gemini 1.5 Flash</option>
   557→                        </optgroup>
   558→                        <optgroup label="xAI">
   559→                            <option value="grok-2-latest">Grok 2</option>
   560→                        </optgroup>
   561→                    </select>
   562→

   563→
   564→

   565→                    <button class="ai-mode-btn active" data-mode="general" onclick="setAiChatMode('general',this)" style="background:#6366f1; color:#fff; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">💬 General</button>
   566→                    <button class="ai-mode-btn" data-mode="thread" onclick="setAiChatMode('thread',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">📧 Thread</button>
   567→                    <button class="ai-mode-btn" data-mode="contact" onclick="setAiChatMode('contact',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">👤 Contact</button>
   568→                    <button class="ai-mode-btn" data-mode="quote" onclick="setAiChatMode('quote',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">💰 Quote</button>
   569→                    <button class="ai-mode-btn" data-mode="reply" onclick="setAiChatMode('reply',this)" style="background:#2d2d4e; color:#94a3b8; border:none; border-radius:5px; padding:3px 9px; font-size:0.7em; cursor:pointer;">✍ Reply</button>
   570→

   571→

   572→
   573→
   574→

   575→

   576→
🤖

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

   578→
Open a thread or contact first to use context modes.

   579→

   580→

   581→
   582→
   583→

   584→
   585→
   586→

   587→

   588→                    <textarea id="ai-chat-input" placeholder="Ask anything... (Enter to send, Shift+Enter for newline)" style="flex:1; background:#1e1e2e; color:#e2e8f0; border:1px solid #3d3d5c; border-radius:8px; padding:8px 10px; font-size:0.82em; resize:none; height:60px; font-family:inherit; outline:none;" onkeydown="handleAiChatKey(event)"></textarea>
   589→                    <button onclick="sendAiChat()" id="ai-chat-send-btn" style="background:linear-gradient(135deg,#6366f1,#8b5cf6); color:#fff; border:none; border-radius:8px; padding:8px 14px; cursor:pointer; font-size:1.1em; height:60px; min-width:44px; transition:opacity 0.2s;">➤</button>
   590→

   591→

   592→

   593→
   594→
   595→        <button id="ai-chat-fab" onclick="toggleAiChat()" title="AI Assistant" style="position:fixed; bottom:20px; right:20px; width:56px; height:56px; background:linear-gradient(135deg,#6366f1,#8b5cf6); color:#fff; border:none; border-radius:50%; font-size:1.5em; cursor:pointer; box-shadow:0 4px 20px rgba(99,102,241,0.5); z-index:9998; transition:transform 0.2s; display:flex; align-items:center; justify-content:center;" onmouseover="this.style.transform='scale(1.1)'" onmouseout="this.style.transform='scale(1)'">🤖</button>
   596→
   597→
   598→

   599→

   600→
Processing...

   601→

   602→

   603→
   604→
   605→

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


     1→"use strict";
     2→
     3→/**
     4→ * Email Intelligence Content Script
     5→ *
     6→ * Integrates with Gmail to provide AI-powered email analysis
     7→ * Pattern detection matches existing extension: polls every 2s for expanded emails
     8→ */
     9→
    10→(function() {
    11→  console.log("[Email Intelligence] Content script loaded");
    12→
    13→  // Version info
    14→  const EXTENSION_VERSION = "2.1.1";
    15→  const BUILD_DATE = "2024.12.30.2";
    16→
    17→  // Provider/Model Configuration
    18→  const PROVIDER_MODELS = {
    19→    claude: [
    20→      { id: 'claude-sonnet-4-5-20250929', name: 'Sonnet 4.5' },
    21→      { id: 'claude-opus-4-5-20251101', name: 'Opus 4.5 (Best)' },
    22→      { id: 'claude-haiku-4-5-20251001', name: 'Haiku 4.5 (Fast)' }
    23→    ],
    24→    openai: [
    25→      { id: 'gpt-5.2', name: 'GPT-5.2 (Latest)' },
    26→      { id: 'gpt-5.2-pro', name: 'GPT-5.2 Pro (Best)' },
    27→      { id: 'gpt-5-mini', name: 'GPT-5 Mini' },
    28→      { id: 'gpt-5-nano', name: 'GPT-5 Nano (Fast)' }
    29→    ],
    30→    gemini: [
    31→      { id: 'gemini-2.5-flash', name: 'Gemini 2.5 Flash' },
    32→      { id: 'gemini-3-pro', name: 'Gemini 3 Pro' },
    33→      { id: 'gemini-2.5-flash-lite', name: 'Flash-Lite (Fast)' }
    34→    ],
    35→    grok: [
    36→      { id: 'grok-4', name: 'Grok 4 (Latest)' },
    37→      { id: 'grok-3', name: 'Grok 3' },
    38→      { id: 'grok-3-mini', name: 'Grok 3 Mini (Fast)' }
    39→    ],
    40→    deepseek: [
    41→      { id: 'deepseek-chat', name: 'DeepSeek V3.2' },
    42→      { id: 'deepseek-reasoner', name: 'Reasoner (Thinking)' }
    43→    ],
    44→    qwen: [
    45→      { id: 'qwen-max-latest', name: 'Qwen Max' },
    46→      { id: 'qwen-turbo-latest', name: 'Qwen Turbo (Fast)' }
    47→    ],
    48→    mistral: [
    49→      { id: 'mistral-large-latest', name: 'Mistral Large' },
    50→      { id: 'mistral-small-latest', name: 'Mistral Small (Fast)' }
    51→    ],
    52→    cohere: [
    53→      { id: 'command-a-03-2025', name: 'Command A' },
    54→      { id: 'command-r7b-12-2024', name: 'Command R7B (Fast)' }
    55→    ]
    56→  };
    57→
    58→  const PROVIDER_NAMES = {
    59→    claude: 'Claude',
    60→    openai: 'OpenAI',
    61→    gemini: 'Gemini',
    62→    grok: 'Grok',
    63→    deepseek: 'DeepSeek',
    64→    qwen: 'Qwen',
    65→    mistral: 'Mistral',
    66→    cohere: 'Cohere'
    67→  };
    68→
    69→  // Current AI selection (persisted to storage)
    70→  let selectedProvider = 'claude';
    71→  let selectedModel = 'claude-sonnet-4-5-20250929';
    72→
    73→  // Conversation memory (ChatGPT-like)
    74→  let aiConversationHistory = [];
    75→  const MAX_AI_CONVERSATION_HISTORY = 10;
    76→
    77→  // Saved context (always included in AI requests)
    78→  let savedAIContext = [];
    79→
    80→  // Last question/answer for save functionality

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


     1→<?php
     2→
     3→namespace EmailIntelligence;
     4→
     5→/**
     6→ * QueryAdapter - Automatically routes queries to MySQL or MongoDB
     7→ *
     8→ * This class provides a unified interface that works with both databases.
     9→ * When MySQL is enabled, it uses SQL queries.
    10→ * When MySQL is disabled, it routes to MongoRepository equivalents.
    11→ *
    12→ * Usage:
    13→ *   $adapter = QueryAdapter::getInstance();
    14→ *   $contacts = $adapter->getContactsWithProfiles($search, $limit, $offset, $sort);
    15→ */
    16→class QueryAdapter
    17→{
    18→    private static ?QueryAdapter $instance = null;
    19→    private Database $db;
    20→    private ?MongoRepository $mongoRepo = null;
    21→    private bool $useMongo = true;
    22→
    23→    private function __construct()
    24→    {
    25→        $this->db = Database::getInstance();
    26→
    27→        // Use MongoDB if MySQL is disabled
    28→        $this->useMongo = !defined('MYSQL_ENABLED') || !MYSQL_ENABLED;
    29→
    30→        if ($this->useMongo) {
    31→            $this->mongoRepo = new MongoRepository();
    32→        }
    33→    }
    34→
    35→    public static function getInstance(): QueryAdapter
    36→    {
    37→        if (self::$instance === null) {
    38→            self::$instance = new self();
    39→        }
    40→        return self::$instance;
    41→    }
    42→
    43→    /**
    44→     * Check which database is being used
    45→     */
    46→    public function getActiveDatabase(): string
    47→    {
    48→        return $this->useMongo ? 'mongodb' : 'mysql';
    49→    }
    50→
    51→    // =========================================================================
    52→    // CONTACTS
    53→    // =========================================================================
    54→
    55→    /**
    56→     * Get contacts with profiles (paginated)
    57→     *
    58→     * @param string $search Search term (name, email, company)
    59→     * @param int $limit Results per page
    60→     * @param int $offset Pagination offset
    61→     * @param string $sortColumn Column to sort by
    62→     * @param string $sortOrder ASC or DESC
    63→     * @return array ['contacts' => [...], 'total' => int]
    64→     */
    65→    public function getContactsWithProfiles(
    66→        string $search = '',
    67→        int $limit = 50,
    68→        int $offset = 0,
    69→        string $sortColumn = 'name',
    70→        string $sortOrder = 'ASC'
    71→    ): array {
    72→        if ($this->useMongo) {
    73→            return $this->getContactsWithProfilesMongo($search, $limit, $offset, $sortColumn, $sortOrder);
    74→        }
    75→
    76→        return $this->getContactsWithProfilesSQL($search, $limit, $offset, $sortColumn, $sortOrder);
    77→    }
    78→
    79→    private function getContactsWithProfilesSQL(
    80→        string $search,
    81→        int $limit,
    82→        int $offset,
    83→        string $sortColumn,
    84→        string $sortOrder
    85→    ): array {
    86→        $whereClause = '1=1';
    87→        $params = [];
    88→
    89→        if ($search) {
    90→            $whereClause = "(c.name LIKE ? OR c.email LIKE ? OR c.company LIKE ?)";
    91→            $searchParam = "%{$search}%";
    92→            $params = [$searchParam, $searchParam, $searchParam];
    93→        }
    94→
    95→        // Validate sort column
    96→        $allowedColumns = ['name', 'email', 'company', 'created_at', 'reliability_score', 'risk_level'];
    97→        if (!in_array($sortColumn, $allowedColumns)) {
    98→            $sortColumn = 'name';
    99→        }
   100→        $sortOrder = strtoupper($sortOrder) === 'DESC' ? 'DESC' : 'ASC';

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

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

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

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

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

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

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

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

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

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

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


TodoWrite

Explore existing QueryAdapter methods for threads

Exploring existing QueryAdapter methods for threads

Explore Chrome extension's fetchEmailContext and Ask AI flow

Exploring Chrome extension's Ask AI flow

Explore the AI proxy API endpoint structure

Explore existing search/contacts API actions

Exploring existing search/contacts API actions

Design the complete implementation plan

Designing the complete implementation plan

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

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

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

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

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

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

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

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

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

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

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


Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


472:    public function getThreadsWithContact(
505:    public function getThreads(?int $contactId = null, string $search = '', int $limit = 20, int $offset = 0): array
514:    private function getThreadsSQL(?int $contactId, string $search, int $limit, int $offset): array
569:    private function getThreadsMongo(?int $contactId, string $search, int $limit, int $offset): array

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

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

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

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

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

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

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

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

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

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

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


383:        case 'threads':

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

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

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

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

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

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

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

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

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

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

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


290:        case 'contacts':

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

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

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

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

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

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

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

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

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

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

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


No matches found

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


   472→    public function getThreadsWithContact(
   473→        ?int $contactId = null,
   474→        int $limit = 50
   475→    ): array {
   476→        if ($this->useMongo) {
   477→            $filter = $contactId ? ['contact_id' => $contactId] : [];
   478→            $repo = new MongoRepository();
   479→            return $repo->getThreadsWithContact($filter, ['limit' => $limit]);
   480→        }
   481→
   482→        $whereClause = $contactId ? "ta.contact_id = ?" : "1=1";
   483→        $params = $contactId ? [$contactId, $limit] : [$limit];
   484→
   485→        return $this->db->fetchAll(
   486→            "SELECT ta.*, c.name as contact_name, c.email as contact_email
   487→             FROM thread_analysis ta
   488→             LEFT JOIN contacts c ON ta.contact_id = c.id
   489→             WHERE {$whereClause}
   490→             ORDER BY ta.analyzed_at DESC
   491→             LIMIT ?",
   492→            $params
   493→        );
   494→    }
   495→
   496→    /**
   497→     * Get list of threads with summary information (paginated)
   498→     *
   499→     * @param int|null $contactId Filter by contact ID
   500→     * @param string $search Search term for subject
   501→     * @param int $limit Results per page
   502→     * @param int $offset Pagination offset
   503→     * @return array ['threads' => [...], 'total' => int]
   504→     */
   505→    public function getThreads(?int $contactId = null, string $search = '', int $limit = 20, int $offset = 0): array
   506→    {
   507→        if ($this->useMongo) {
   508→            return $this->getThreadsMongo($contactId, $search, $limit, $offset);
   509→        }
   510→
   511→        return $this->getThreadsSQL($contactId, $search, $limit, $offset);
   512→    }
   513→
   514→    private function getThreadsSQL(?int $contactId, string $search, int $limit, int $offset): array
   515→    {
   516→        $where = 'e.thread_id IS NOT NULL AND e.thread_id != ""';
   517→        $params = [];
   518→
   519→        if ($contactId) {
   520→            $where .= ' AND e.contact_id = ?';
   521→            $params[] = $contactId;
   522→        }
   523→
   524→        if ($search) {
   525→            $where .= ' AND e.subject LIKE ?';
   526→            $params[] = '%' . $search . '%';
   527→        }
   528→
   529→        // Get total thread count
   530→        $total = $this->db->fetchColumn(
   531→            "SELECT COUNT(DISTINCT e.thread_id)
   532→             FROM emails e
   533→             WHERE {$where}",
   534→            $params
   535→        );
   536→
   537→        // Get threads with summary info
   538→        $threads = $this->db->fetchAll(
   539→            "SELECT
   540→                e.thread_id,
   541→                MIN(e.id) as first_email_id,
   542→                MAX(e.id) as last_email_id,
   543→                MIN(e.subject) as subject,
   544→                MIN(e.date) as first_date,
   545→                MAX(e.date) as last_date,
   546→                COUNT(*) as email_count,
   547→                SUM(CASE WHEN e.direction = 'inbound' THEN 1 ELSE 0 END) as inbound_count,
   548→                SUM(CASE WHEN e.direction = 'outbound' THEN 1 ELSE 0 END) as outbound_count,
   549→                MAX(e.contact_id) as contact_id,
   550→                MAX(c.name) as contact_name,
   551→                ta.is_analyzed,
   552→                ta.needs_reanalysis
   553→             FROM emails e
   554→             LEFT JOIN contacts c ON e.contact_id = c.id
   555→             LEFT JOIN thread_analysis ta ON e.thread_id = ta.thread_id
   556→             WHERE {$where}
   557→             GROUP BY e.thread_id
   558→             ORDER BY MAX(e.date) DESC
   559→             LIMIT ? OFFSET ?",
   560→            array_merge($params, [$limit, $offset])
   561→        );
   562→
   563→        return [
   564→            'threads' => $threads,
   565→            'total' => (int)$total
   566→        ];
   567→    }
   568→
   569→    private function getThreadsMongo(?int $contactId, string $search, int $limit, int $offset): array
   570→    {
   571→        $mongo = MongoDatabase::getInstance();
   572→
   573→        // Build match filter
   574→        $matchFilter = [
   575→            'thread_id' => ['$ne' => null, '$ne' => '']
   576→        ];
   577→
   578→        if ($contactId) {
   579→            $matchFilter['contact_id'] = $contactId;
   580→        }
   581→
   582→        if ($search) {
   583→            $matchFilter['subject'] = ['$regex' => $search, '$options' => 'i'];
   584→        }
   585→
   586→        // Count distinct threads for total
   587→        $countPipeline = [
   588→            ['$match' => $matchFilter],
   589→            ['$group' => ['_id' => '$thread_id']],
   590→            ['$count' => 'total']
   591→        ];
   592→
   593→        $countResult = $mongo->aggregate('emails', $countPipeline);
   594→        $total = !empty($countResult) ? $countResult[0]['total'] : 0;
   595→
   596→        // Get threads with aggregated data
   597→        $pipeline = [
   598→            ['$match' => $matchFilter],
   599→            ['$group' => [
   600→                '_id' => '$thread_id',
   601→                'first_email_id' => ['$min' => '$id'],
   602→                'last_email_id' => ['$max' => '$id'],
   603→                'subject' => ['$first' => '$subject'],
   604→                'first_date' => ['$min' => '$date'],
   605→                'last_date' => ['$max' => '$date'],
   606→                'email_count' => ['$sum' => 1],
   607→                'inbound_count' => ['$sum' => ['$cond' => [['$eq' => ['$direction', 'inbound']], 1, 0]]],
   608→                'outbound_count' => ['$sum' => ['$cond' => [['$eq' => ['$direction', 'outbound']], 1, 0]]],
   609→                'contact_id' => ['$max' => '$contact_id']
   610→            ]],
   611→            ['$lookup' => [
   612→                'from' => 'contacts',
   613→                'localField' => 'contact_id',
   614→                'foreignField' => 'id',
   615→                'as' => 'contact'
   616→            ]],
   617→            ['$lookup' => [
   618→                'from' => 'thread_analysis',
   619→                'localField' => '_id',
   620→                'foreignField' => 'thread_id',
   621→                'as' => 'analysis'
   622→            ]],
   623→            ['$project' => [
   624→                '_id' => 0,
   625→                'thread_id' => '$_id',
   626→                'first_email_id' => 1,
   627→                'last_email_id' => 1,
   628→                'subject' => 1,
   629→                'first_date' => 1,
   630→                'last_date' => 1,
   631→                'email_count' => 1,
   632→                'inbound_count' => 1,
   633→                'outbound_count' => 1,
   634→                'contact_id' => 1,
   635→                'contact_name' => ['$arrayElemAt' => ['$contact.name', 0]],
   636→                'is_analyzed' => ['$arrayElemAt' => ['$analysis.is_analyzed', 0]],
   637→                'needs_reanalysis' => ['$arrayElemAt' => ['$analysis.needs_reanalysis', 0]]
   638→            ]],
   639→            ['$sort' => ['last_date' => -1]],
   640→            ['$skip' => $offset],
   641→            ['$limit' => $limit]
   642→        ];
   643→
   644→        $threads = $mongo->aggregate('emails', $pipeline);
   645→
   646→        return [
   647→            'threads' => $threads,
   648→            'total' => $total
   649→        ];
   650→    }
   651→
   652→    /**
   653→     * Get full thread details with all emails and analysis
   654→     *
   655→     * @param string $threadId Gmail thread ID
   656→     * @return array ['thread_id', 'emails', 'analysis', 'email_count']
   657→     */
   658→    public function getThreadDetails(string $threadId): array
   659→    {
   660→        if ($this->useMongo) {
   661→            return $this->getThreadDetailsMongo($threadId);
   662→        }
   663→
   664→        return $this->getThreadDetailsSQL($threadId);
   665→    }
   666→
   667→    private function getThreadDetailsSQL(string $threadId): array
   668→    {
   669→        // Get all emails in thread with contact info
   670→        $emails = $this->db->fetchAll(
   671→            "SELECT e.*, c.name as contact_name, c.email as contact_email

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


   383→        case 'threads':
   384→            $contactId = (int)($_GET['contact'] ?? 0);
   385→            $search = trim($_GET['search'] ?? '');
   386→            $page = max(1, (int)($_GET['page'] ?? 1));
   387→            $limit = min(100, max(1, (int)($_GET['limit'] ?? 20)));
   388→            $offset = ($page - 1) * $limit;
   389→            $hasBusiness = isset($_GET['has_business']) && $_GET['has_business'];
   390→
   391→            // Use QueryAdapter for automatic MySQL/MongoDB routing
   392→            $adapter = QueryAdapter::getInstance();
   393→            $result = $adapter->getThreads(
   394→                $contactId ?: null,
   395→                $search,
   396→                $limit,
   397→                $offset
   398→            );
   399→
   400→            // Note: has_business filtering is handled by frontend due to raw_analysis being stored as JSON string
   401→            // Future: migrate raw_analysis to proper BSON objects for better querying
   402→
   403→            jsonResponse([
   404→                'threads' => $result['threads'],
   405→                'pagination' => [
   406→                    'page' => $page,
   407→                    'limit' => $limit,
   408→                    'total' => $result['total'],
   409→                    'pages' => ceil($result['total'] / $limit)
   410→                ]
   411→            ]);
   412→            break;
   413→
   414→        // ==========================================
   415→        // Single Thread with All Emails
   416→        // ==========================================
   417→        case 'thread':
   418→            $threadId = $_GET['thread_id'] ?? '';
   419→            if (!$threadId) jsonError('Thread ID required');
   420→
   421→            // Auto-resolve long URL thread ID to short hex ID from cache
   422→            $threadId = resolveThreadId($threadId);
   423→
   424→            // Use QueryAdapter for automatic MySQL/MongoDB routing
   425→            $adapter = QueryAdapter::getInstance();
   426→            $threadData = $adapter->getThreadDetails($threadId);
   427→
   428→            if (empty($threadData['emails'])) {
   429→                jsonError('Thread not found', 404);
   430→            }
   431→
   432→            $emails = $threadData['emails'];
   433→            $analysis = $threadData['analysis'];
   434→
   435→            // Parse JSON fields in analysis (for MySQL string storage)
   436→            if ($analysis && isset($analysis['raw_analysis']) && is_string($analysis['raw_analysis'])) {
   437→                // Strip markdown code block markers if present (```json ... ```)
   438→                $rawStr = trim($analysis['raw_analysis']);
   439→                if (preg_match('/^```(?:json)?\s*([\s\S]*?)\s*```$/s', $rawStr, $matches)) {
   440→                    $rawStr = $matches[1];
   441→                }
   442→                $analysis['raw_analysis'] = json_decode($rawStr, true);
   443→            }
   444→            if ($analysis && isset($analysis['key_points']) && is_string($analysis['key_points'])) {
   445→                $analysis['key_points'] = json_decode($analysis['key_points'], true);
   446→            }
   447→
   448→            // Ensure raw_analysis is an array for safe access
   449→            if ($analysis && !isset($analysis['raw_analysis'])) {
   450→                $analysis['raw_analysis'] = [];
   451→            }
   452→
   453→            // Extract participants_analysis from raw_analysis for easier access
   454→            $participantsAnalysis = [];
   455→            if ($analysis && isset($analysis['raw_analysis']['participants_analysis'])) {
   456→                $participantsAnalysis = $analysis['raw_analysis']['participants_analysis'];
   457→            }
   458→
   459→            // Build response with extracted analysis fields
   460→            $rawAnalysis = $analysis['raw_analysis'] ?? [];
   461→
   462→            // Determine true analyzed state: trust the DB flag, but also consider

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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

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

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


   290→        case 'contacts':
   291→            $page = max(1, (int)($_GET['page'] ?? 1));
   292→            $limit = min(100, max(10, (int)($_GET['limit'] ?? 20)));
   293→            $offset = ($page - 1) * $limit;
   294→            $search = $_GET['search'] ?? '';
   295→            $type = $_GET['type'] ?? '';
   296→            $sort = $_GET['sort'] ?? 'last_contact';
   297→            $order = strtoupper($_GET['order'] ?? 'DESC') === 'ASC' ? 'ASC' : 'DESC';
   298→
   299→            // Build query
   300→            $where = ['c.is_active = 1'];
   301→            $params = [];
   302→
   303→            if ($search) {
   304→                $where[] = "(c.email LIKE ? OR c.name LIKE ? OR c.company LIKE ?)";
   305→                $params[] = "%{$search}%";
   306→                $params[] = "%{$search}%";
   307→                $params[] = "%{$search}%";
   308→            }
   309→
   310→            if ($type && in_array($type, ['client', 'supplier', 'other'])) {
   311→                $where[] = "c.type = ?";
   312→                $params[] = $type;
   313→            }
   314→
   315→            $whereClause = implode(' AND ', $where);
   316→
   317→            // Allowed sort columns
   318→            $sortColumns = ['last_contact', 'total_emails', 'email', 'name', 'reliability_score'];
   319→            if (!in_array($sort, $sortColumns)) $sort = 'last_contact';
   320→
   321→            $sortColumn = $sort === 'reliability_score' ? 'cp.reliability_score' : "c.{$sort}";
   322→
   323→            // Get total count
   324→            $total = $db->fetchColumn(
   325→                "SELECT COUNT(*) FROM contacts c WHERE {$whereClause}",
   326→                $params
   327→            );
   328→
   329→            // Get contacts with profiles
   330→            $contacts = $db->fetchAll(
   331→                "SELECT c.*,
   332→                    cp.relationship_health, cp.reliability_score, cp.risk_level,
   333→                    cp.pricing_sensitivity, cp.ai_recommendations
   334→                 FROM contacts c
   335→                 LEFT JOIN contact_profiles cp ON c.id = cp.contact_id
   336→                 WHERE {$whereClause}
   337→                 ORDER BY {$sortColumn} {$order}
   338→                 LIMIT ? OFFSET ?",
   339→                array_merge($params, [$limit, $offset])
   340→            );
   341→
   342→            jsonResponse([
   343→                'contacts' => $contacts,
   344→                'pagination' => [
   345→                    'page' => $page,
   346→                    'limit' => $limit,
   347→                    'total' => (int)$total,
   348→                    'pages' => ceil($total / $limit)
   349→                ]
   350→            ]);
   351→            break;
   352→
   353→        // ==========================================
   354→        // Single Contact with Full Profile
   355→        // ==========================================
   356→        case 'contact':
   357→            $id = (int)($_GET['id'] ?? 0);
   358→            if (!$id) jsonError('Contact ID required');
   359→
   360→            // Use QueryAdapter for automatic MySQL/MongoDB routing
   361→            $adapter = QueryAdapter::getInstance();
   362→            $data = $adapter->getContactWithDetails($id);
   363→
   364→            if (!$data || !$data['contact']) {
   365→                jsonError('Contact not found', 404);
   366→            }
   367→
   368→            // Parse JSON fields (for MySQL string storage)
   369→            $jsonFields = ['personality_traits', 'detected_inconsistencies', 'risk_factors',

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

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

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

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

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

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

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

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

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

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

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