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.


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.


78:  let savedAIContext = [];
342:      const storage = await chrome.storage.local.get('savedAIContext');
343:      if (storage.savedAIContext && Array.isArray(storage.savedAIContext)) {
344:        savedAIContext = storage.savedAIContext;
345:        console.log("[Email Intelligence] Loaded", savedAIContext.length, "saved context items");
357:      await chrome.storage.local.set({ savedAIContext });
358:      console.log("[Email Intelligence] Saved context:", savedAIContext.length, "items");
381:    savedAIContext.push(item);
393:    savedAIContext = savedAIContext.filter(item => item.id !== id);
402:    savedAIContext = [];
411:    if (savedAIContext.length === 0) return '';
416:    savedAIContext.forEach((item, index) => {
446:    if (savedAIContext.length === 0) {
454:        📌 Saved Context (${savedAIContext.length})
466:        ${savedAIContext.map(item => {

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.


Grep

function loadThreads|function loadContacts|function searchContacts

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.


159:async function loadContacts(page = 1) {

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.


340→  async function loadSavedAIContext() {
   341→    try {
   342→      const storage = await chrome.storage.local.get('savedAIContext');
   343→      if (storage.savedAIContext && Array.isArray(storage.savedAIContext)) {
   344→        savedAIContext = storage.savedAIContext;
   345→        console.log("[Email Intelligence] Loaded", savedAIContext.length, "saved context items");
   346→      }
   347→    } catch (e) {
   348→      console.log("[Email Intelligence] Could not load saved context:", e);
   349→    }
   350→  }
   351→
   352→  /**
   353→   * Save context to Chrome storage
   354→   */
   355→  async function saveSavedAIContext() {
   356→    try {
   357→      await chrome.storage.local.set({ savedAIContext });
   358→      console.log("[Email Intelligence] Saved context:", savedAIContext.length, "items");
   359→    } catch (e) {
   360→      console.log("[Email Intelligence] Could not save context:", e);
   361→    }
   362→  }
   363→
   364→  /**
   365→   * Add item to saved context
   366→   * @param {string} type - 'question' | 'answer' | 'qa_pair' | 'selection'
   367→   * @param {string} content - The content to save
   368→   * @param {string} description - Optional short description
   369→   * @param {string} question - The question (for qa_pair type)
   370→   */
   371→  function addToSavedContext(type, content, description = '', question = '') {
   372→    const item = {
   373→      id: Date.now().toString(),
   374→      type: type,
   375→      content: content,
   376→      description: description || content.substring(0, 50),
   377→      question: question,
   378→      created_at: new Date().toISOString()
   379→    };
   380→
   381→    savedAIContext.push(item);
   382→    saveSavedAIContext();
   383→    updateSavedContextDisplay();
   384→
   385→    // Show confirmation
   386→    showToast('Context saved! It will be included in future AI requests.');
   387→  }
   388→
   389→  /**
   390→   * Remove item from saved context
   391→   */
   392→  function removeFromSavedContext(id) {
   393→    savedAIContext = savedAIContext.filter(item => item.id !== id);
   394→    saveSavedAIContext();
   395→    updateSavedContextDisplay();
   396→  }
   397→
   398→  /**
   399→   * Clear all saved context
   400→   */
   401→  function clearSavedAIContext() {
   402→    savedAIContext = [];
   403→    saveSavedAIContext();
   404→    updateSavedContextDisplay();
   405→  }
   406→
   407→  /**
   408→   * Build saved context string for AI request
   409→   */
   410→  function buildSavedContextPrompt() {
   411→    if (savedAIContext.length === 0) return '';
   412→
   413→    let context = '\n\n=== USER-SAVED CONTEXT (IMPORTANT - Always Consider) ===\n';
   414→    context += 'The user has saved the following important information that should inform all responses:\n\n';
   415→
   416→    savedAIContext.forEach((item, index) => {
   417→      const typeLabel = {
   418→        'question': '📝 Saved Question',
   419→        'answer': '💡 Saved Answer',
   420→        'qa_pair': '🔗 Saved Q&A',
   421→        'selection': '📌 Saved Note'
   422→      }[item.type] || '📌 Context';
   423→
   424→      context += `[${typeLabel} ${index + 1}]\n`;
   425→      if (item.type === 'qa_pair' && item.question) {
   426→        context += `Q: ${item.question}\n`;
   427→        context += `A: ${item.content}\n`;
   428→      } else {
   429→        context += `${item.content}\n`;
   430→      }
   431→      context += '\n';
   432→    });
   433→
   434→    context += '=== END SAVED CONTEXT ===\n\n';
   435→    return context;
   436→  }
   437→
   438→  /**
   439→   * Update saved context display in sidebar
   440→   */
   441→  function updateSavedContextDisplay() {
   442→    if (!shadowRoot) return;
   443→    const container = shadowRoot.querySelector('#ai-saved-context');
   444→    if (!container) return;
   445→
   446→    if (savedAIContext.length === 0) {
   447→      container.style.display = 'none';
   448→      return;
   449→    }
   450→
   451→    container.style.display = 'block';
   452→    container.innerHTML = `
   453→

   454→        📌 Saved Context (${savedAIContext.length})
   455→        <button id="clear-saved-context-btn" style="
   456→          background: #fef2f2;
   457→          border: 1px solid #fecaca;
   458→          color: #dc2626;
   459→          padding: 2px 6px;
   460→          border-radius: 3px;
   461→          font-size: 9px;
   462→          cursor: pointer;
   463→        ">Clear All</button>
   464→

   465→

   466→        ${savedAIContext.map(item => {
   467→          const typeIcon = { 'question': '❓', 'answer': '💡', 'qa_pair': '🔗', 'selection': '📌' }[item.type] || '📌';
   468→          return `
   469→

   470→              ${typeIcon} ${escapeHtml(item.description.substring(0, 35))}${item.description.length > 35 ? '...' : ''}
   471→              <button class="remove-saved-context" data-id="${item.id}" style="
   472→                position: absolute;
   473→                top: 2px;
   474→                right: 4px;
   475→                background: none;
   476→                border: none;
   477→                color: #dc2626;
   478→                cursor: pointer;
   479→                font-size: 11px;
   480→                padding: 0;
   481→              ">✕</button>
   482→

   483→          `;
   484→        }).join('')}
   485→

   486→    `;
   487→
   488→    // Wire up clear all button
   489→    const clearAllBtn = container.querySelector('#clear-saved-context-btn');

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.


159→async function loadContacts(page = 1) {
   160→    const container = document.getElementById('contacts-list');
   161→    container.innerHTML = '
Loading contacts...
';
   162→
   163→    try {
   164→        state.contacts.page = page;
   165→        state.contacts.search = document.getElementById('contact-search')?.value || '';
   166→        state.contacts.type = document.getElementById('contact-type-filter')?.value || '';
   167→
   168→        const data = await apiCall('contacts', {
   169→            page: page,
   170→            search: state.contacts.search,
   171→            type: state.contacts.type,
   172→            limit: 20
   173→        });
   174→
   175→        if (data.contacts.length === 0) {
   176→            container.innerHTML = '
No contacts found
';
   177→            return;
   178→        }
   179→
   180→        let html = `
   181→

   182→

   183→

   184→                        Contact
   185→                        Type
   186→                        Emails
   187→                        Relationship
   188→                        Risk
   189→                        Last Contact
   190→                        Actions
   191→

   192→

   193→

   194→        `;
   195→
   196→        data.contacts.forEach(contact => {
   197→            const riskClass = contact.risk_level ? 'badge-' + contact.risk_level : 'badge-low';
   198→            const relClass = contact.relationship_health ? 'badge-' + contact.relationship_health.replace('_', '-') : 'badge-new';
   199→            const enrichedBadge = contact.enrichment_status === 'complete' ? '✓' : '';
   200→
   201→            html += `
   202→

   203→
   204→                        ${escapeHtml(contact.name || contact.email)} ${enrichedBadge}
   205→                        ${contact.name ? '
' + escapeHtml(contact.email) + '' : ''}
   206→                        ${contact.company ? '
' + escapeHtml(contact.company) + '' : ''}
   207→
   208→                    ${contact.type}
   209→                    ${contact.total_emails || 0}
   210→                    ${contact.relationship_health || 'new'}
   211→                    ${contact.risk_level || 'low'}
   212→                    ${contact.last_contact ? formatDate(contact.last_contact) : '-'}
   213→
   214→                        <button class="btn btn-sm btn-enrich" data-email="${escapeHtml(contact.email)}" data-contact-id="${contact.id}" onclick="event.stopPropagation(); enrichContactFromList(this);">
   215→                            🔬 Enrich
   216→                        </button>
   217→
   218→

   219→            `;
   220→        });
   221→
   222→        html += '

';
   223→        container.innerHTML = html;
   224→
   225→        // Pagination
   226→        renderPagination('contacts-pagination', data.pagination, loadContacts);
   227→
   228→    } catch (error) {
   229→        container.innerHTML = '
Error loading contacts: ' + escapeHtml(error.message) + '
';
   230→    }
   231→}
   232→
   233→async function showContact(contactId) {
   234→    showLoading('Loading contact...');
   235→
   236→    try {
   237→        const data = await apiCall('contact', { id: contactId });
   238→        const contact = data.contact;

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.


3453:  async function askAI(question) {

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.


Bash

List AI proxy API directory

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.


total 12
drwxrwxrwx 2 root root 4096 Dec 21 00:04 .
drwxrwxrwx 7 root root 4096 Dec 21 00:04 ..
-rwxrwxrwx 1 root root 2345 Feb 18 22:47 index.php

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.


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.


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

Prompt:
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.


3453→  async function askAI(question) {
  3454→    const chatHistory = shadowRoot.getElementById('ai-chat-history');
  3455→
  3456→    // Add question
  3457→    const questionDiv = document.createElement('div');
  3458→    questionDiv.style.cssText = "background: #667eea; color: white; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px;";
  3459→    questionDiv.textContent = question;
  3460→    chatHistory.appendChild(questionDiv);
  3461→
  3462→    // Add loading
  3463→    const loadingDiv = document.createElement('div');
  3464→    loadingDiv.style.cssText = "background: #f9fafb; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px; color: #999;";
  3465→    loadingDiv.textContent = "Thinking...";
  3466→    chatHistory.appendChild(loadingDiv);
  3467→    chatHistory.scrollTop = chatHistory.scrollHeight;
  3468→
  3469→    try {
  3470→      // Resolve thread ID first if it's a URL-style ID (FMfcgz...)
  3471→      if (currentThreadId && currentMessageId && !isRealGmailThreadId(currentThreadId)) {
  3472→        await resolveRealThreadId();
  3473→      }
  3474→
  3475→      const response = await sendMessage('askAI', {
  3476→        question: question,
  3477→        thread_id: currentThreadId,
  3478→        contact_id: currentContactId
  3479→      });
  3480→
  3481→      loadingDiv.remove();
  3482→
  3483→      if (response.success && response.data.answer) {
  3484→        const answerDiv = document.createElement('div');
  3485→        answerDiv.style.cssText = "background: #f9fafb; border: 1px solid #e0e0e0; padding: 12px; border-radius: 8px; margin-bottom: 12px; font-size: 12px; line-height: 1.6; color: #333;";
  3486→        // Use formatted HTML instead of plain text
  3487→        answerDiv.innerHTML = formatAIResponse(response.data.answer);
  3488→        chatHistory.appendChild(answerDiv);
  3489→        chatHistory.scrollTop = chatHistory.scrollHeight;
  3490→      } else {
  3491→        const errorDiv = document.createElement('div');
  3492→        errorDiv.style.cssText = "background: #fef2f2; border: 1px solid #fecaca; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px; color: #dc2626;";
  3493→        errorDiv.textContent = "Sorry, I couldn't process that question.";
  3494→        chatHistory.appendChild(errorDiv);
  3495→      }
  3496→    } catch (error) {
  3497→      const errorDiv = document.createElement('div');
  3498→      errorDiv.style.cssText = "background: #fef2f2; border: 1px solid #fecaca; padding: 10px; border-radius: 8px; margin-bottom: 8px; font-size: 12px; color: #dc2626;";
  3499→      errorDiv.textContent = `Error: ${error.message}`;
  3500→      chatHistory.appendChild(errorDiv);
  3501→    }
  3502→  }
  3503→
  3504→  /**
  3505→   * Load reply options with thread context
  3506→   */
  3507→  async function loadReplyOptions() {
  3508→    if (!currentThreadId) {
  3509→      replyContent.innerHTML = '
No thread selected
';
  3510→      return;
  3511→    }
  3512→
  3513→    replyContent.innerHTML = '
Loading...
';
  3514→
  3515→    // Resolve thread ID first if it's a URL-style ID (FMfcgz...)
  3516→    if (currentMessageId && !isRealGmailThreadId(currentThreadId)) {
  3517→      await resolveRealThreadId();
  3518→    }
  3519→
  3520→    // Fetch thread participants for context
  3521→    let participants = [];
  3522→    let threadSubject = currentSubject || '';
  3523→    if (currentThreadId) {
  3524→      try {
  3525→        const resp = await sendMessage('getThreadParticipants', {thread_id: currentThreadId});
  3526→        if (resp.success && resp.data) {
  3527→          participants = resp.data.participants?.filter(p => p.participant_type === 'external') || [];
  3528→          threadSubject = resp.data.subject || threadSubject;
  3529→        }
  3530→      } catch (e) {
  3531→        console.log("[Email Intelligence] Could not load participants for Reply context");
  3532→      }
  3533→    }
  3534→
  3535→    const participantNames = participants.map(p => p.name || p.email.split('@')[0]).join(', ');
  3536→    const hasContext = currentThreadId && participants.length > 0;
  3537→
  3538→    // Load saved templates from storage
  3539→    let templates = [];
  3540→    try {
  3541→      const storage = await chrome.storage.local.get('replyTemplates');
  3542→      templates = storage.replyTemplates || [];
  3543→    } catch (e) {
  3544→      console.log("[Email Intelligence] Could not load templates:", e);
  3545→    }
  3546→
  3547→    const templateOptions = templates.length > 0
  3548→      ? templates.map((t, i) => `<option value="${i}">${escapeHtml(t.name)}</option>`).join('')
  3549→      : '';
  3550→
  3551→    replyContent.innerHTML = `
  3552→      ${hasContext ? `
  3553→

  3554→
REPLYING TO

  3555→
${escapeHtml(threadSubject)}

  3556→
Recipients: ${escapeHtml(participantNames)}

  3557→

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

  3562→

  3563→

  3564→            ✨ AI Reply Suggestions
  3565→

  3566→          <button id="load-suggestions-btn" style="
  3567→            background: #0ea5e9;
  3568→            color: white;
  3569→            border: none;
  3570→            padding: 6px 12px;
  3571→            border-radius: 4px;
  3572→            cursor: pointer;

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.


107:async function apiCall(action, params = {}, method = 'GET') {

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.