Conversation compacted


This session is being continued from a previous conversation that ran out of context. The summary below covers the earlier portion of the conversation.

Analysis:
Let me go through the conversation chronologically to capture all details.

**Message 1 (System/Context):** This is a continuation from a previous conversation. The summary describes extensive prior work:
- Project at `/var/www/mssql.danmarcrm.com/dev1/extension2/` - email intelligence system
- Previously ported AI chat changes from extension2 to extension2v1
- Was in plan mode for enhancing thread_view.php with agents, context builder, tokens, logging
- Also needed: speed up main page, fix thread contact name bug, hide AI Thread Analysis section

**Message 2 (Assistant continues):** I wrote the final plan to `/root/.claude/plans/scalable-doodling-peach.md` and called ExitPlanMode. Plan was approved.

**Implementation of 4 Tasks:**

TASK 1: Hide AI Thread Analysis (index.php + app.js)
- Commented out `refreshAnalysisStatus()` and `setInterval(refreshAnalysisStatus, 30000)` in app.js lines 1589-1592
- Note: The display:none on index.php was mentioned in plan but appears to have been done in the previous session already

TASK 2: Speed up main page
- Changed `limit: 20` to `limit: 10` in `loadContacts()` at app.js:176
- Changed `limit: 20` to `limit: 10` in `loadEmails()` at app.js:650

TASK 3: Fix thread contact name bug in QueryAdapter.php
- MongoDB `getThreadsMongo()`: Replaced `'contact_id' => ['$max' => '$contact_id']` with `'all_contacts' => ['$push' => ['cid' => '$contact_id', 'email' => '$from_email', 'dir' => '$direction']]`
- Post-processes to find most frequent inbound external sender (excluding GMAIL_USER_EMAIL)
- Batch lookup contact names from contacts collection
- SQL `getThreadsSQL()`: Replaced `MAX(e.contact_id)` and `MAX(c.name)` with correlated subqueries finding most frequent inbound sender

TASK 4: Enhance thread_view.php
- 4A: Full-width layout - changed max-width from 1600px to 100%, grid from 1fr 400px to 1fr 500px
- 4B: Agent buttons (General, Quotes, Deception, Profiler, Composer) with quick prompts
- 4C: Context builder - search contacts/threads, add threads from any contact
- 4D: Token estimation with MODEL_LIMITS map
- 4E: System prompt injection per agent
- 4F: Debug logging endpoint `log_ai_debug` in api.php + JS calls
- 4G: Contact memory injection

**Message 3 (User):** "pls check the logs, I send about 20 email thread.. and in interface got only one show as over 200000 tokens, though it said before it is ok. No error or nothing shows up in the interface after refresh though I sent to 4 AI models"

**Investigation and Fixes:**
Found multiple issues:
1. PHP memory exhaustion - Thread with 57 emails caused `json_encode` to crash at 128MB limit
2. Content was 1.47MB / 420K tokens - way over model limits
3. Token estimation used `contextThreads.length * 2000` (showed 40K for what was actually 420K)
4. No error shown because PHP 500 response couldn't be parsed as JSON

Fixes applied:
1. New `thread_for_ai` API endpoint - lightweight, stripped bodies, 3K cap per email
2. Better token estimation - `emailCount * 500` per thread
3. Content truncation at 85% of smallest model limit
4. Robust error handling with try/catch on each thread fetch
5. Debug log capped to 10K chars

**Message 4 (User):** "can you run and test my latest test without me searching etc in the interface?"

**Testing:**
- Tested `thread_for_ai` endpoint: 53 emails, 34K chars (vs 33MB crash before)
- Tested all 20 context threads: 315 emails, 283K chars, ~81K tokens, 48MB memory
- Full end-to-end test sending to Claude Sonnet: SUCCESS, 78s, $0.38, 11725 char response
- Sent to OpenAI + Mistral + Cohere: OpenAI SUCCESS, Mistral 429 rate limit, Cohere SUCCESS

**Message 5 (User):** "pls continue" (after the 3 providers test)

**Message 6 (User):** Long request for Two-Round AI feature:
"add option so user can decide if: after the first set of AI models reply, make sure to wait for their reply but don't stuck of one or more fails, get a new summary based by all returned responses. User should have a checkbox to decide from beginning if goes by two rounds of AI where the second one is sent to all first selected AI with previous content received from first round. Pls make sure to wait for all or declare unusable the ones not responding timely. Or implement the option so user can select relevant answers and ask questions with the previous answers."

**Implementation of Two-Round AI:**

Started implementing in thread_view.php:
1. Added CSS for round options, response selection bar, response checkboxes, round badges, provider timeout
2. Added HTML: Two-round checkbox, provider timeout dropdown, response selection bar with All/None/Ask Follow-up buttons, Round 2 response container
3. Added JS: `lastRound1Responses`, `sendRound2()`, `displayRound2Response()`, `switchRound2Tab()`, `askFollowUp()`, `getSelectedResponseTexts()`, `selectAllResponses()`, `deselectAllResponses()`, `fetchWithTimeout()` with AbortController
4. Modified `displayAIResponse()` to add selection checkboxes on each response card, show follow-up bar, track success/fail counts
5. Modified `submitToAI()` to use `fetchWithTimeout` with configurable timeout

**Current state:** The implementation is INCOMPLETE. I was in the middle of modifying `submitToAI()`. Specifically:
- I replaced the `fetch` call with `fetchWithTimeout` (with the timeout dropdown value)
- BUT I have NOT yet added the code to trigger Round 2 automatically when the two-round checkbox is on
- The `displayAIResponse(data)` call on line ~2931 needs to be updated to call `displayAIResponse(data, 'Round 1')` and then check if two-round mode is enabled to call `sendRound2()`

Looking at what's been done vs what's pending:
- The `sendRound2()` function is fully implemented
- The `askFollowUp()` function is fully implemented
- The `displayAIResponse()` has been rewritten with checkboxes
- The `fetchWithTimeout()` helper is implemented
- BUT the connection between Round 1 completion and Round 2 auto-trigger is NOT yet wired up in `submitToAI()`

The todo list shows:
1. [completed] Add Two-Round AI checkbox and response selection UI
2. [completed] Implement Round 2 auto-summary logic in submitToAI
3. [completed] Add manual response selection + follow-up feature
4. [in_progress] Add timeout handling for slow providers
5. [pending] Test and verify PHP syntax

But #2 isn't fully completed - the auto-trigger in submitToAI is missing. The `sendRound2` function exists but isn't called from anywhere yet.

Let me also note: I need to store `lastRound1Providers`, `lastRound1Models`, `lastRound1Question` when Round 1 completes, and the `displayAIResponse` call needs the round label parameter.

Summary:
1. Primary Request and Intent:

The user is building an AI-powered email thread analysis system with a Chrome extension. This session continued from a previous conversation. The explicit requests were:

**Phase 1 (from prior session, completed at start):** Port AI chat changes from `extension2/` to `extension2v1/`, then enhance `thread_view.php` with new features + fix 3 dashboard issues. This was planned and approved.

**Phase 2 (implemented):** Execute the approved 4-task plan:
- TASK 1: Hide AI Thread Analysis section (slow, shows "Unknown")
- TASK 2: Reduce thread/contact load limits from 20→10
- TASK 3: Fix thread contact name bug ("Etienne Turner" showing for all threads)
- TASK 4: Enhance thread_view.php with agents, context builder, token estimation, debug logging, contact memory

**Phase 3 (bug fix):** User tested with 20 threads → got no response. Investigation revealed PHP memory exhaustion, wildly inaccurate token estimation, no content truncation, and silent JS error handling.

**Phase 4 (testing):** User asked to run full end-to-end tests programmatically. Tested successfully with Claude, OpenAI, Mistral, Cohere.

**Phase 5 (current, IN PROGRESS):** Add Two-Round AI feature:
- Checkbox for auto two-round mode: Round 1 → all providers answer → Round 2 → all providers receive ALL Round 1 answers and produce unified summary
- Provider timeout control to skip slow/failed providers
- Manual response selection: user picks which AI responses to include, then asks follow-up questions with those as context
- Don't get stuck if providers fail/timeout

2. Key Technical Concepts:
   - MongoDB as primary database (SQL is legacy/empty) — always use `QueryAdapter`
   - `MongoDatabase::insertOrUpdate()` for upserts (NOT `upsert()`)
   - AI proxy at `aiapi/api_opus/api/query.php` — supports multi-provider simultaneous requests
   - AI proxy at `aiapi/api_codex51/api/index.php` — single-provider requests
   - Models keyed by provider: `[$provider => $model]` (NOT `[$model]`)
   - `ThreadAnalyzer::stripQuotedContent()` — public static method for removing quoted email content
   - Token estimation: `Math.ceil(charCount / 3.5)` for character-to-token conversion
   - Content budget: 85% of smallest selected model's context limit
   - PHP memory limit: 128MB (134217728 bytes) — caused crashes with large thread data
   - `AbortController` for JS fetch timeout handling
   - Node.js on server is v10.19 — no arrow functions or optional chaining in server-checked JS
   - `ai_query_responses` MongoDB collection for saved thread_view AI responses
   - `ai_contact_memory` MongoDB collection for contact facts

3. Files and Code Sections:

   - **`/var/www/mssql.danmarcrm.com/dev1/extension2v1/public/assets/app.js`**
     - Dashboard JS for main page
     - Disabled `refreshAnalysisStatus()` and 30s interval (lines 1589-1592, commented out)
     - Reduced contacts limit from 20 to 10 (line 176)
     - Reduced threads limit from 20 to 10 (line 650)

   - **`/var/www/mssql.danmarcrm.com/dev1/extension2v1/src/QueryAdapter.php`**
     - Core data access layer routing between MySQL/MongoDB
     - **`getThreadsMongo()` (lines 569-650):** Complete rewrite — replaced `'contact_id' => ['$max' => '$contact_id']` with `'all_contacts' => ['$push' => ['cid' => '$contact_id', 'email' => '$from_email', 'dir' => '$direction']]`. Post-processes to find most frequent inbound external sender, batch lookups contact names.
     - **`getThreadsSQL()` (lines 514-567):** Replaced `MAX(e.contact_id)` and `MAX(c.name)` with correlated subqueries:
       ```sql
       (SELECT e2.contact_id FROM emails e2
        WHERE e2.thread_id = e.thread_id
        AND e2.direction = 'inbound'
        AND LOWER(e2.from_email) != ?
        GROUP BY e2.contact_id
        ORDER BY COUNT(*) DESC LIMIT 1) as contact_id
       ```
     - Added `GMAIL_USER_EMAIL` as bind parameter for both subqueries

   - **`/var/www/mssql.danmarcrm.com/dev1/extension2v1/public/api.php`**
     - Main API endpoint file (~5500+ lines)
     - **Added `log_ai_debug` endpoint** (after `save_ai_response` case): Writes JSON log entries to `logs/ai_debug.log`
     - **Added `thread_for_ai` endpoint** (after `thread` case): Lightweight thread data for AI context — strips quoted content server-side via `ThreadAnalyzer::stripQuotedContent()`, truncates each email body to 3000 chars, returns only email metadata + stripped bodies (no analysis, no raw data). This fixed the PHP memory exhaustion.
       ```php
       case 'thread_for_ai':
           // ... fetches thread, strips/truncates bodies
           $aiEmails[] = [
               'from_name' => ..., 'from_email' => ...,
               'date' => ..., 'direction' => ...,
               'subject' => ..., 'body_text' => $body // stripped + truncated
           ];
           jsonResponse(['thread_id' => $threadId, 'emails' => $aiEmails,
                         'email_count' => count($aiEmails), 'total_chars' => $totalChars]);
       ```

   - **`/var/www/mssql.danmarcrm.com/dev1/extension2v1/public/thread_view.php`** (now ~3300+ lines)
     - The main file being enhanced. Contains PHP + HTML + CSS + JS all inline.
     - **CSS additions:** Full-width layout (max-width: 100%), agent buttons, context builder, token estimate, response selection, two-round controls, round badges, provider timeout styling
     - **HTML additions:**
       - Agent selector section with quick prompts
       - Context builder (search + add threads from any contact)
       - Token estimation display
       - Two-round mode checkbox with description
       - Provider timeout dropdown (60s/90s/120s/180s/300s)
       - Response selection bar (All/None/Ask Follow-up buttons)
       - Round 2 response container (separate from Round 1)
       - Response checkboxes on each AI response card
     - **JS constants:** `AI_AGENTS` (5 agents with systemPrompt + quickPrompts), `MODEL_LIMITS` (25+ model→token mappings), `selectedAgent`, `contextThreads[]`, `contactMemories[]`
     - **JS functions added:**
       - `initAgentButtons()`, `selectAgent()`, `updateAgentQuickPrompts()`, `useQuickPrompt()`
       - `toggleContextBuilder()`, `debounceContextSearch()`, `searchContext()`, `loadContactThreads()`, `addThreadToContext()`, `removeThreadFromContext()`, `updateContextCart()`, `addAllContactThreads()`
       - `estimateCurrentTokens()`, `updateTokenEstimate()`, `getSmallestModelLimit()`
       - `loadContactMemories()`, `renderContactMemories()`
       - `logAiDebug()`
       - `sendRound2()` — builds Round 2 prompt from all successful Round 1 responses, sends to same providers
       - `displayRound2Response()`, `switchRound2Tab()`
       - `askFollowUp()` — prompts user for follow-up question, sends with selected response texts as context
       - `getSelectedResponseTexts()`, `selectAllResponses()`, `deselectAllResponses()`
       - `fetchWithTimeout()` — uses `AbortController` for configurable timeout
     - **Modified `displayAIResponse(data, roundLabel)`:** Now adds selection checkboxes on each successful response, shows follow-up bar, tracks success/fail counts, stores responses in `lastRound1Responses`
     - **Modified `submitToAI()`:** Uses `fetchWithTimeout`, injects agent system prompt + contact memories, fetches context threads via `thread_for_ai` endpoint (not `thread`), truncates content to 85% of model limit, logs to debug file, better error handling with try/catch per thread fetch

4. Errors and fixes:

   - **PHP memory exhaustion (134217728 bytes):**
     - Cause: Thread `18de73e1494697fb` had 57 emails. `api.php?action=thread` returned full data including analysis/raw — ~33MB. `json_encode()` in `jsonResponse()` exhausted 128MB PHP memory limit.
     - Fix: Created new `thread_for_ai` endpoint returning only stripped/truncated email bodies (no analysis). Reduced from ~33MB to ~38K for that thread.

   - **Wildly inaccurate token estimation:**
     - Cause: Pre-estimate used `contextThreads.length * 2000` (= ~40K for 20 threads), but actual content was 1.47MB / 420K tokens
     - Fix: Changed to `emailCount * 500` per thread (much closer to reality: 81K estimated vs 96K actual)

   - **No content truncation before sending to AI:**
     - Cause: 420K tokens sent to models with 128K-200K limits
     - Fix: Added `maxChars = Math.floor(modelLimit * 3.5 * 0.85)` truncation before sending

   - **Silent JS error on PHP 500 response:**
     - Cause: PHP fatal error returned HTTP 500 with HTML body, `response.json()` threw, but user didn't see meaningful error
     - Fix: Added `response.ok` check, `.text()` then `JSON.parse()` with explicit error messages, try/catch on each thread fetch

   - **Debug log file was 1.5MB:**
     - Cause: Logging entire `fullContent` (1.47MB) in the debug log
     - Fix: Capped `full_content` in log to first 10K chars

   - **cURL localhost redirect (301):**
     - Cause: During testing, `http://localhost/dev1/...` redirected to HTTPS
     - Fix: Changed test URL to `https://mssql.danmarcrm.com/dev1/...`

   - **Wrong working directory for PHP CLI:**
     - Cause: Shell cwd was reset between commands
     - Fix: Added `cd /var/www/mssql.danmarcrm.com/dev1/extension2v1/public &&` prefix

5. Problem Solving:

   - Successfully identified that the PHP memory crash was the root cause of "no error showing" — the HTTP 500 with HTML body couldn't be parsed as JSON by the JS fetch handler
   - Verified fixes with full end-to-end programmatic tests: 21 threads, 315 emails → Claude (78s, $0.38), GPT-4o (24s), Cohere (76s, $0.32). Mistral hit their rate limit (429) — not our bug.
   - Confirmed memory usage dropped from crash at 128MB to stable 48-52MB
   - The Two-Round AI feature implementation is IN PROGRESS

6. All user messages:
   - "pls check the logs, I send about 20 email thread.. and in interface got only one show as over 200000 tokens, though it said before it is ok. No error or nothing shows up in the interface after refresh though I sent to 4 AI models"
   - "can you run and test my latest test without me searching etc in the interface?"
   - "pls continue" (after OpenAI+Mistral+Cohere test started)
   - "add option so user can decide if: after the first set of AI models reply, make sure to wait for their reply but don't stuck of one or more fails, get a new summary based by all retuned respoonses. Useer should have a checkbox to decide from beginning if goes by two rounds of AI where the second one is sent to all first selected AI with previous content received from first round. Pls make sure to wait for all ot declare unusable the ones not responging timely. Or implement the option so user can select relevant answers and ask questions with the previous answers."

7. Pending Tasks:
   - **Complete Two-Round AI wiring in `submitToAI()`:** The `sendRound2()` function exists but is NOT YET CALLED from `submitToAI()` after Round 1 completes. Need to:
     1. Store `lastRound1Providers`, `lastRound1Models`, `lastRound1Question` when Round 1 finishes
     2. Update `displayAIResponse(data)` call to pass `'Round 1'` label
     3. After displaying Round 1, check `document.getElementById('two-round-mode').checked` and if true, call `sendRound2(lastRound1Responses, selectedProvidersList, modelsMap, actualQuestion)`
     4. If two-round mode is off, still keep the submit button enabled so user can use the follow-up bar
   - **PHP syntax verification** of thread_view.php after all JS changes
   - **End-to-end test** of the two-round and follow-up features

8. Current Work:
   I was implementing the Two-Round AI feature in `thread_view.php`. I had:
   - Added all CSS, HTML, and most JS (functions `sendRound2`, `askFollowUp`, `fetchWithTimeout`, `displayRound2Response`, etc.)
   - Rewrote `displayAIResponse()` to add checkboxes and follow-up bar
   - Modified the fetch in `submitToAI()` to use `fetchWithTimeout` with configurable timeout

   **What's incomplete:** The `submitToAI()` function does NOT yet:
   1. Pass `'Round 1'` to `displayAIResponse(data)` — currently calls `displayAIResponse(data)` without round label
   2. Store the providers/models/question for Round 2
   3. Check the two-round checkbox and trigger `sendRound2()` after Round 1 display
   4. Keep the loading overlay active between rounds (for auto two-round mode)

   The specific line that needs updating is around line 2931 where `displayAIResponse(data)` is called — this needs to become `displayAIResponse(data, 'Round 1')` followed by the Round 2 trigger logic.

9. Optional Next Step:
   Complete the wiring in `submitToAI()` to connect Round 1 completion to Round 2 auto-trigger. Specifically, find the section after `displayAIResponse(data)` at ~line 2931 and add:
   - `displayAIResponse(data, 'Round 1')` (add round label)
   - Store `lastRound1Providers = selectedProvidersList`, `lastRound1Models = modelsMap`, `lastRound1Question = actualQuestion`
   - Check `document.getElementById('two-round-mode').checked` and if true, call `sendRound2(lastRound1Responses, selectedProvidersList, modelsMap, actualQuestion)` — keeping the loading overlay visible between rounds
   - Then run PHP syntax check and test

   User's exact request: "add option so user can decide if: after the first set of AI models reply, make sure to wait for their reply but don't stuck of one or more fails, get a new summary based by all retuned respoonses. Useer should have a checkbox to decide from beginning if goes by two rounds of AI where the second one is sent to all first selected AI with previous content received from first round."

If you need specific details from before compaction (like exact code snippets, error messages, or content you generated), read the full transcript at: /root/.claude/projects/-var-www-mssql-danmarcrm-com-dev1-extension2/75ef92ac-556a-4223-9d55-17c4e535294d.jsonl
Please continue the conversation from where we left off without asking the user any further questions. Continue with the last task that you were asked to work on.


Let me continue where I left off. The main incomplete task is wiring up the Two-Round AI feature in `submitToAI()`. I need to:

1. Find the current state of `submitToAI()` in thread_view.php
2. Update `displayAIResponse(data)` to pass `'Round 1'` label
3. Store providers/models/question for Round 2
4. Check the two-round checkbox and trigger `sendRound2()` after Round 1 completes
5. Then verify PHP syntax and test

Let me first read the current state of the relevant section in thread_view.php.


Continuing with the Two-Round AI implementation. I need to wire up the Round 1 → Round 2 auto-trigger in `submitToAI()`. Let me read the current state of the code.


TodoWrite

Add Two-Round AI checkbox and response selection UI

Implement Round 2 auto-summary logic in submitToAI

Add manual response selection + follow-up feature

Wire Round 1 completion to Round 2 auto-trigger in submitToAI

Test and verify PHP syntax


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

Add Two-Round AI checkbox and response selection UI

Implement Round 2 auto-summary logic in submitToAI

Add manual response selection + follow-up feature

Add timeout handling for slow providers

Test and verify PHP syntax

Wire Round 1 completion to Round 2 auto-trigger in submitToAI

Test and verify PHP syntax


  2900→                                agent: selectedAgent,
  2901→                                content_mode: contentMode,
  2902→                                content_sent: fullContent,
  2903→                                content_length: fullContent.length,
  2904→                                estimated_tokens: finalTokens,
  2905→                                provider: prov,
  2906→                                model: modelsMap[prov],
  2907→                                query_id: data.query_id,
  2908→                                response: providerResponse,
  2909→                                total_cost: providerResponse.cost || 0,
  2910→                                all_providers: selectedProvidersList,
  2911→                                conversation_history_count: conversationHistory.length
  2912→                            });
  2913→                        }
  2914→                    }
  2915→
  2916→                    // ADD TO CONVERSATION HISTORY (first successful response)
  2917→                    if (firstSuccessfulProvider && firstSuccessfulResponse && firstSuccessfulResponse.response) {
  2918→                        addToConversation(
  2919→                            actualQuestion,
  2920→                            firstSuccessfulResponse.response,
  2921→                            firstSuccessfulProvider,
  2922→                            modelsMap[firstSuccessfulProvider],
  2923→                            context
  2924→                        );
  2925→                    }
  2926→
  2927→                    // Clear the question field for next question
  2928→                    document.getElementById('ai-question').value = '';
  2929→                    updateTokenEstimate();
  2930→
  2931→                    // Display response
  2932→                    displayAIResponse(data);
  2933→                } else {
  2934→                    alert('AI request failed: ' + (data.error || 'Unknown error'));
  2935→                }
  2936→            } catch (error) {
  2937→                console.error('AI request error:', error);
  2938→                alert('Error: ' + error.message);
  2939→            } finally {
  2940→                document.getElementById('loading-overlay').classList.remove('active');
  2941→                document.getElementById('submit-ai-btn').disabled = false;
  2942→            }
  2943→        }
  2944→
  2945→        // Save AI response to MongoDB
  2946→        async function saveAIResponse(responseData) {
  2947→            try {
  2948→                await fetch('api.php?action=save_ai_response', {
  2949→                    method: 'POST',
  2950→                    headers: { 'Content-Type': 'application/json' },
  2951→                    body: JSON.stringify(responseData)
  2952→                });
  2953→            } catch (error) {
  2954→                console.error('Failed to save response:', error);
  2955→            }
  2956→        }
  2957→
  2958→        // Display AI response
  2959→        function displayAIResponse(data, roundLabel) {
  2960→            var container = document.getElementById('ai-response-container');
  2961→            var tabsContainer = document.getElementById('response-tabs');
  2962→            var contentContainer = document.getElementById('ai-responses-content');
  2963→            var badge = document.getElementById('response-round-badge');
  2964→
  2965→            container.style.display = 'block';
  2966→            tabsContainer.innerHTML = '';
  2967→            contentContainer.innerHTML = '';
  2968→
  2969→            // Update badge
  2970→            if (badge) {
  2971→                badge.textContent = roundLabel || 'Round 1';
  2972→                badge.className = 'round-badge round-1';
  2973→            }
  2974→
  2975→            // Hide Round 2 container (fresh start)
  2976→            document.getElementById('ai-response-round2-container').style.display = 'none';
  2977→
  2978→            // Store responses for follow-up
  2979→            lastRound1Responses = {};
  2980→
  2981→            var tabIndex = 0;
  2982→            var successCount = 0;
  2983→            var failCount = 0;
  2984→
  2985→            for (var key in data.responses) {
  2986→                var response = data.responses[key];
  2987→                var providerName = key.replace('_response', '');
  2988→                var providerConfig = providers[providerName] || { name: providerName };
  2989→
  2990→                // Store for Round 2 / follow-up
  2991→                lastRound1Responses[providerName] = response;
  2992→
  2993→                // Create tab
  2994→                var tab = document.createElement('button');
  2995→                tab.className = 'response-tab' + (tabIndex === 0 ? ' active' : '');
  2996→                tab.textContent = providerConfig.name + (response.success ? '' : ' (fail)');
  2997→                tab.dataset.index = tabIndex;
  2998→                (function(idx) {
  2999→                    tab.onclick = function() { switchResponseTab(idx); };

                                agent: selectedAgent,
                                content_mode: contentMode,
                                content_sent: fullContent,
                                content_length: fullContent.length,
                                estimated_tokens: finalTokens,
                                provider: prov,
                                model: modelsMap[prov],
                                query_id: data.query_id,
                                response: providerResponse,
                                total_cost: providerResponse.cost || 0,
                                all_providers: selectedProvidersList,
                                conversation_history_count: conversationHistory.length
                            });
                        }
                    }

                    // ADD TO CONVERSATION HISTORY (first successful response)
                    if (firstSuccessfulProvider && firstSuccessfulResponse && firstSuccessfulResponse.response) {
                        addToConversation(
                            actualQuestion,
                            firstSuccessfulResponse.response,
                            firstSuccessfulProvider,
                            modelsMap[firstSuccessfulProvider],
                            context
                        );
                    }

                    // Clear the question field for next question
                    document.getElementById('ai-question').value = '';
                    updateTokenEstimate();

                    // Display response
                    displayAIResponse(data);
                } else {
                    alert('AI request failed: ' + (data.error || 'Unknown error'));
                }
            } catch (error) {
                console.error('AI request error:', error);
                alert('Error: ' + error.message);
            } finally {
                document.getElementById('loading-overlay').classList.remove('active');
                document.getElementById('submit-ai-btn').disabled = false;
            }
        }

        // Save AI response to MongoDB
        async function saveAIResponse(responseData) {
            try {
                await fetch('api.php?action=save_ai_response', {
                    method: 'POST',
                    headers: { 'Content-Type': 'application/json' },
                    body: JSON.stringify(responseData)
                });
            } catch (error) {
                console.error('Failed to save response:', error);
            }
        }

        // Display AI response
        function displayAIResponse(data, roundLabel) {
            var container = document.getElementById('ai-response-container');
            var tabsContainer = document.getElementById('response-tabs');
            var contentContainer = document.getElementById('ai-responses-content');
            var badge = document.getElementById('response-round-badge');

            container.style.display = 'block';
            tabsContainer.innerHTML = '';
            contentContainer.innerHTML = '';

            // Update badge
            if (badge) {
                badge.textContent = roundLabel || 'Round 1';
                badge.className = 'round-badge round-1';
            }

            // Hide Round 2 container (fresh start)
            document.getElementById('ai-response-round2-container').style.display = 'none';

            // Store responses for follow-up
            lastRound1Responses = {};

            var tabIndex = 0;
            var successCount = 0;
            var failCount = 0;

            for (var key in data.responses) {
                var response = data.responses[key];
                var providerName = key.replace('_response', '');
                var providerConfig = providers[providerName] || { name: providerName };

                // Store for Round 2 / follow-up
                lastRound1Responses[providerName] = response;

                // Create tab
                var tab = document.createElement('button');
                tab.className = 'response-tab' + (tabIndex === 0 ? ' active' : '');
                tab.textContent = providerConfig.name + (response.success ? '' : ' (fail)');
                tab.dataset.index = tabIndex;
                (function(idx) {
                    tab.onclick = function() { switchResponseTab(idx); };


2999→                    tab.onclick = function() { switchResponseTab(idx); };
  3000→                })(tabIndex);
  3001→                tabsContainer.appendChild(tab);
  3002→
  3003→                // Create content with selection checkbox
  3004→                var contentDiv = document.createElement('div');
  3005→                contentDiv.className = 'response-content' + (tabIndex === 0 ? ' active' : '');
  3006→                contentDiv.id = 'response-tab-' + tabIndex;
  3007→
  3008→                if (response.success) {
  3009→                    successCount++;
  3010→                    var cbId = 'resp-cb-' + providerName;
  3011→                    contentDiv.innerHTML = '
' +
  3012→                        '<input type="checkbox" class="response-select-cb" id="' + cbId + '" checked ' +
  3013→                        'data-provider="' + escapeHtml(providerName) + '" ' +
  3014→                        'data-model="' + escapeHtml(response.model || '') + '" ' +
  3015→                        'data-response-text="' + escapeHtml(response.response || '').replace(/"/g, '"') + '">' +
  3016→                        'Include in follow-up' +
  3017→                        '
' +
  3018→                        '
' +
  3019→                        '
' +
  3020→                        '' + escapeHtml(providerConfig.name) + '' +
  3021→                        '' +
  3022→                        'Model: ' + escapeHtml(response.model || 'Unknown') + ' | ' +
  3023→                        'Time: ' + (response.request_time ? response.request_time.toFixed(2) : '?') + 's | ' +
  3024→                        'Cost: $' + (response.cost ? response.cost.toFixed(6) : '0') +
  3025→                        '
' +
  3026→                        '
' + escapeHtml(response.response) + '
' +
  3027→                        '
';
  3028→                } else {
  3029→                    failCount++;
  3030→                    contentDiv.innerHTML = '
' +
  3031→                        'Error (' + escapeHtml(providerConfig.name) + '):' +
  3032→                        '
' + escapeHtml(response.error || 'Unknown error / timeout') + '

';
  3033→                }
  3034→
  3035→                contentContainer.appendChild(contentDiv);
  3036→                tabIndex++;
  3037→            }
  3038→
  3039→            // Show the follow-up bar
  3040→            var selectBar = document.getElementById('response-select-bar');
  3041→            if (selectBar && successCount > 0) {
  3042→                selectBar.style.display = 'flex';
  3043→            }
  3044→
  3045→            // Add summary line if mixed results
  3046→            if (failCount > 0 && successCount > 0) {
  3047→                var summaryDiv = document.createElement('div');
  3048→                summaryDiv.className = 'provider-timeout';
  3049→                summaryDiv.style.marginTop = '10px';
  3050→                summaryDiv.innerHTML = successCount + ' provider(s) responded, ' + failCount + ' failed/timed out. Successful responses are shown above.';
  3051→                contentContainer.appendChild(summaryDiv);
  3052→            }
  3053→
  3054→            container.scrollIntoView({ behavior: 'smooth' });
  3055→        }
  3056→
  3057→        // Switch response tabs - scoped to response container only
  3058→        function switchResponseTab(index) {
  3059→            const tabsContainer = document.getElementById('response-tabs');
  3060→            const contentContainer = document.getElementById('ai-responses-content');
  3061→
  3062→            if (!tabsContainer || !contentContainer) return;
  3063→
  3064→            // Only target tabs within our container
  3065→            tabsContainer.querySelectorAll('.response-tab').forEach(tab => {
  3066→                const tabIndex = parseInt(tab.dataset.index);
  3067→                tab.classList.remove('active');
  3068→                if (tabIndex === index) {
  3069→                    tab.classList.add('active');
  3070→                }
  3071→            });
  3072→
  3073→            // Only target content within our container
  3074→            contentContainer.querySelectorAll('.response-content').forEach((content, i) => {
  3075→                content.classList.remove('active');
  3076→                if (i === index) {
  3077→                    content.classList.add('active');
  3078→                }
  3079→            });
  3080→        }
  3081→
  3082→        // Close response
  3083→        function closeResponse() {
  3084→            document.getElementById('ai-response-container').style.display = 'none';
  3085→        }
  3086→
  3087→        // Mark a saved response row as last viewed
  3088→        function markAsLastViewed(responseId) {
  3089→            // Remove last-viewed from all rows
  3090→            document.querySelectorAll('.saved-response.last-viewed').forEach(el => {
  3091→                el.classList.remove('last-viewed');
  3092→            });
  3093→            // Add to the current row
  3094→            const row = document.getElementById('saved-response-' + responseId);
  3095→            if (row) {
  3096→                row.classList.add('last-viewed');
  3097→            }
  3098→        }
  3099→
  3100→        // Load saved response
  3101→        async function loadSavedResponse(responseId) {
  3102→            try {
  3103→                // Mark this row as last viewed
  3104→                markAsLastViewed(responseId);
  3105→
  3106→                document.getElementById('loading-overlay').classList.add('active');
  3107→                document.getElementById('loading-message').textContent = 'Loading saved response...';
  3108→
  3109→                const response = await fetch(`api.php?action=get_ai_response&id=${responseId}`);
  3110→                const data = await response.json();
  3111→
  3112→                if (data.success && data.response) {
  3113→                    const saved = data.response;
  3114→
  3115→                    // Display it
  3116→                    const container = document.getElementById('ai-response-container');
  3117→                    const tabsContainer = document.getElementById('response-tabs');
  3118→                    const contentContainer = document.getElementById('ai-responses-content');

tab.onclick = function() { switchResponseTab(idx); };
                })(tabIndex);
                tabsContainer.appendChild(tab);

                // Create content with selection checkbox
                var contentDiv = document.createElement('div');
                contentDiv.className = 'response-content' + (tabIndex === 0 ? ' active' : '');
                contentDiv.id = 'response-tab-' + tabIndex;

                if (response.success) {
                    successCount++;
                    var cbId = 'resp-cb-' + providerName;
                    contentDiv.innerHTML = '
' +
                        '<input type="checkbox" class="response-select-cb" id="' + cbId + '" checked ' +
                        'data-provider="' + escapeHtml(providerName) + '" ' +
                        'data-model="' + escapeHtml(response.model || '') + '" ' +
                        'data-response-text="' + escapeHtml(response.response || '').replace(/"/g, '"') + '">' +
                        'Include in follow-up' +
                        '
' +
                        '
' +
                        '
' +
                        '' + escapeHtml(providerConfig.name) + '' +
                        '' +
                        'Model: ' + escapeHtml(response.model || 'Unknown') + ' | ' +
                        'Time: ' + (response.request_time ? response.request_time.toFixed(2) : '?') + 's | ' +
                        'Cost: $' + (response.cost ? response.cost.toFixed(6) : '0') +
                        '
' +
                        '
' + escapeHtml(response.response) + '
' +
                        '
';
                } else {
                    failCount++;
                    contentDiv.innerHTML = '
' +
                        'Error (' + escapeHtml(providerConfig.name) + '):' +
                        '
' + escapeHtml(response.error || 'Unknown error / timeout') + '

';
                }

                contentContainer.appendChild(contentDiv);
                tabIndex++;
            }

            // Show the follow-up bar
            var selectBar = document.getElementById('response-select-bar');
            if (selectBar && successCount > 0) {
                selectBar.style.display = 'flex';
            }

            // Add summary line if mixed results
            if (failCount > 0 && successCount > 0) {
                var summaryDiv = document.createElement('div');
                summaryDiv.className = 'provider-timeout';
                summaryDiv.style.marginTop = '10px';
                summaryDiv.innerHTML = successCount + ' provider(s) responded, ' + failCount + ' failed/timed out. Successful responses are shown above.';
                contentContainer.appendChild(summaryDiv);
            }

            container.scrollIntoView({ behavior: 'smooth' });
        }

        // Switch response tabs - scoped to response container only
        function switchResponseTab(index) {
            const tabsContainer = document.getElementById('response-tabs');
            const contentContainer = document.getElementById('ai-responses-content');

            if (!tabsContainer || !contentContainer) return;

            // Only target tabs within our container
            tabsContainer.querySelectorAll('.response-tab').forEach(tab => {
                const tabIndex = parseInt(tab.dataset.index);
                tab.classList.remove('active');
                if (tabIndex === index) {
                    tab.classList.add('active');
                }
            });

            // Only target content within our container
            contentContainer.querySelectorAll('.response-content').forEach((content, i) => {
                content.classList.remove('active');
                if (i === index) {
                    content.classList.add('active');
                }
            });
        }

        // Close response
        function closeResponse() {
            document.getElementById('ai-response-container').style.display = 'none';
        }

        // Mark a saved response row as last viewed
        function markAsLastViewed(responseId) {
            // Remove last-viewed from all rows
            document.querySelectorAll('.saved-response.last-viewed').forEach(el => {
                el.classList.remove('last-viewed');
            });
            // Add to the current row
            const row = document.getElementById('saved-response-' + responseId);
            if (row) {
                row.classList.add('last-viewed');
            }
        }

        // Load saved response
        async function loadSavedResponse(responseId) {
            try {
                // Mark this row as last viewed
                markAsLastViewed(responseId);

                document.getElementById('loading-overlay').classList.add('active');
                document.getElementById('loading-message').textContent = 'Loading saved response...';

                const response = await fetch(`api.php?action=get_ai_response&id=${responseId}`);
                const data = await response.json();

                if (data.success && data.response) {
                    const saved = data.response;

                    // Display it
                    const container = document.getElementById('ai-response-container');
                    const tabsContainer = document.getElementById('response-tabs');
                    const contentContainer = document.getElementById('ai-responses-content');


Now let me see the section around lines 2920-2943 more carefully to understand the exact flow after Round 1 completes:


  2825→                if (wasTruncated) {
  2826→                    document.getElementById('loading-message').textContent = 'Content truncated to ' + finalTokens.toLocaleString() + ' tokens. Sending to ' + selectedProvidersList.length + ' AI(s)...';
  2827→                } else {
  2828→                    document.getElementById('loading-message').textContent = 'Sending ~' + finalTokens.toLocaleString() + ' tokens to ' + selectedProvidersList.length + ' AI provider(s)...';
  2829→                }
  2830→
  2831→                // Send to AI API with timeout
  2832→                var timeoutSec = parseInt(document.getElementById('provider-timeout').value) || 120;
  2833→                var response = await fetchWithTimeout('../aiapi/api_opus/api/query.php', {
  2834→                    method: 'POST',
  2835→                    headers: { 'Content-Type': 'application/json' },
  2836→                    body: JSON.stringify(requestBody)
  2837→                }, timeoutSec * 1000);
  2838→
  2839→                if (!response.ok) {
  2840→                    var errText = '';
  2841→                    try { errText = await response.text(); } catch(e) {}
  2842→                    throw new Error('AI API returned HTTP ' + response.status + (errText ? ': ' + errText.substring(0, 200) : ''));
  2843→                }
  2844→
  2845→                var responseText = await response.text();
  2846→                var data;
  2847→                try {
  2848→                    data = JSON.parse(responseText);
  2849→                } catch (parseErr) {
  2850→                    throw new Error('AI API returned invalid JSON: ' + responseText.substring(0, 200));
  2851→                }
  2852→
  2853→                // Log response to debug file
  2854→                var responsePreview = '';
  2855→                if (data.responses) {
  2856→                    for (var rk in data.responses) {
  2857→                        if (data.responses[rk] && data.responses[rk].response) {
  2858→                            responsePreview = data.responses[rk].response.substring(0, 500);
  2859→                            break;
  2860→                        }
  2861→                    }
  2862→                }
  2863→                logAiDebug({
  2864→                    type: 'response',
  2865→                    thread_id: currentThreadId,
  2866→                    agent: selectedAgent,
  2867→                    providers: selectedProvidersList,
  2868→                    models: modelsMap,
  2869→                    estimated_tokens: finalTokens,
  2870→                    question: actualQuestion,
  2871→                    response: responsePreview
  2872→                });
  2873→
  2874→                console.log('=== AI RESPONSE LOG ===');
  2875→                console.log('Success:', data.success);
  2876→                console.log('Query ID:', data.query_id);
  2877→                console.log('Total Cost:', data.total_cost);
  2878→                console.log('=======================');
  2879→
  2880→                if (data.success) {
  2881→                    var firstSuccessfulProvider = null;
  2882→                    var firstSuccessfulResponse = null;
  2883→
  2884→                    // Save to MongoDB for each provider
  2885→                    for (var pi = 0; pi < selectedProvidersList.length; pi++) {
  2886→                        var prov = selectedProvidersList[pi];
  2887→                        var providerResponse = data.responses[prov + '_response'];
  2888→                        if (providerResponse && providerResponse.success) {
  2889→                            if (!firstSuccessfulProvider) {
  2890→                                firstSuccessfulProvider = prov;
  2891→                                firstSuccessfulResponse = providerResponse;
  2892→                            }
  2893→
  2894→                            // Save to MongoDB via our API
  2895→                            await saveAIResponse({
  2896→                                thread_ids: [currentThreadId].concat(allAdditionalThreads),
  2897→                                contact_id: primaryContactId,
  2898→                                question: actualQuestion,
  2899→                                context: context,
  2900→                                agent: selectedAgent,
  2901→                                content_mode: contentMode,
  2902→                                content_sent: fullContent,
  2903→                                content_length: fullContent.length,
  2904→                                estimated_tokens: finalTokens,

                if (wasTruncated) {
                    document.getElementById('loading-message').textContent = 'Content truncated to ' + finalTokens.toLocaleString() + ' tokens. Sending to ' + selectedProvidersList.length + ' AI(s)...';
                } else {
                    document.getElementById('loading-message').textContent = 'Sending ~' + finalTokens.toLocaleString() + ' tokens to ' + selectedProvidersList.length + ' AI provider(s)...';
                }

                // Send to AI API with timeout
                var timeoutSec = parseInt(document.getElementById('provider-timeout').value) || 120;
                var response = await fetchWithTimeout('../aiapi/api_opus/api/query.php', {
                    method: 'POST',
                    headers: { 'Content-Type': 'application/json' },
                    body: JSON.stringify(requestBody)
                }, timeoutSec * 1000);

                if (!response.ok) {
                    var errText = '';
                    try { errText = await response.text(); } catch(e) {}
                    throw new Error('AI API returned HTTP ' + response.status + (errText ? ': ' + errText.substring(0, 200) : ''));
                }

                var responseText = await response.text();
                var data;
                try {
                    data = JSON.parse(responseText);
                } catch (parseErr) {
                    throw new Error('AI API returned invalid JSON: ' + responseText.substring(0, 200));
                }

                // Log response to debug file
                var responsePreview = '';
                if (data.responses) {
                    for (var rk in data.responses) {
                        if (data.responses[rk] && data.responses[rk].response) {
                            responsePreview = data.responses[rk].response.substring(0, 500);
                            break;
                        }
                    }
                }
                logAiDebug({
                    type: 'response',
                    thread_id: currentThreadId,
                    agent: selectedAgent,
                    providers: selectedProvidersList,
                    models: modelsMap,
                    estimated_tokens: finalTokens,
                    question: actualQuestion,
                    response: responsePreview
                });

                console.log('=== AI RESPONSE LOG ===');
                console.log('Success:', data.success);
                console.log('Query ID:', data.query_id);
                console.log('Total Cost:', data.total_cost);
                console.log('=======================');

                if (data.success) {
                    var firstSuccessfulProvider = null;
                    var firstSuccessfulResponse = null;

                    // Save to MongoDB for each provider
                    for (var pi = 0; pi < selectedProvidersList.length; pi++) {
                        var prov = selectedProvidersList[pi];
                        var providerResponse = data.responses[prov + '_response'];
                        if (providerResponse && providerResponse.success) {
                            if (!firstSuccessfulProvider) {
                                firstSuccessfulProvider = prov;
                                firstSuccessfulResponse = providerResponse;
                            }

                            // Save to MongoDB via our API
                            await saveAIResponse({
                                thread_ids: [currentThreadId].concat(allAdditionalThreads),
                                contact_id: primaryContactId,
                                question: actualQuestion,
                                context: context,
                                agent: selectedAgent,
                                content_mode: contentMode,
                                content_sent: fullContent,
                                content_length: fullContent.length,
                                estimated_tokens: finalTokens,


Now I can see the exact point. Lines 2931-2942 are where I need to make changes. The current flow is:

1. Line 2932: `displayAIResponse(data)` — needs `'Round 1'` label
2. Lines 2936-2942: catch/finally block — need to add Round 2 trigger before finally

Let me also check the `sendRound2` function to see what parameters it expects:


1872:        var lastRound1Providers = [];
1873:        var lastRound1Models = {};
1874:        var lastRound1Question = '';
1878:        function sendRound2(round1Responses, providersList, modelsMap, originalQuestion) {
2071:        function askFollowUp() {
2223:        function fetchWithTimeout(url, options, timeoutMs) {


  1870→        // ============================================
  1871→        var lastRound1Responses = {}; // {providerName: {success, response, model, ...}}
  1872→        var lastRound1Providers = [];
  1873→        var lastRound1Models = {};
  1874→        var lastRound1Question = '';
  1875→        var lastFullContent = '';
  1876→
  1877→        // Send Round 2 with all Round 1 responses as context
  1878→        function sendRound2(round1Responses, providersList, modelsMap, originalQuestion) {
  1879→            var successfulResponses = [];
  1880→            for (var prov in round1Responses) {
  1881→                var r = round1Responses[prov];
  1882→                if (r && r.success && r.response) {
  1883→                    successfulResponses.push({
  1884→                        provider: prov,
  1885→                        model: r.model || 'unknown',
  1886→                        response: r.response
  1887→                    });
  1888→                }
  1889→            }
  1890→
  1891→            if (successfulResponses.length === 0) {
  1892→                console.warn('No successful Round 1 responses for Round 2');
  1893→                return;
  1894→            }
  1895→
  1896→            // Build Round 2 prompt
  1897→            var round2Content = '=== ROUND 2: UNIFIED ANALYSIS ===\n';
  1898→            round2Content += 'You previously analyzed an email conversation. Below are the analyses from ' + successfulResponses.length + ' different AI models.\n';
  1899→            round2Content += 'Your task: Synthesize ALL analyses into a single comprehensive summary. Highlight where models AGREE and where they DISAGREE. Provide a final unified assessment.\n\n';
  1900→            round2Content += 'Original question: ' + originalQuestion + '\n\n';
  1901→
  1902→            successfulResponses.forEach(function(sr, idx) {
  1903→                round2Content += '--- ANALYSIS FROM ' + sr.provider.toUpperCase() + ' (' + sr.model + ') ---\n';
  1904→                // Cap each response to 4000 chars to stay within limits
  1905→                var respText = sr.response;
  1906→                if (respText.length > 4000) {
  1907→                    respText = respText.substring(0, 4000) + '\n...(truncated)';
  1908→                }
  1909→                round2Content += respText + '\n\n';
  1910→            });
  1911→
  1912→            round2Content += '=== END OF ROUND 1 ANALYSES ===\n\n';
  1913→            round2Content += 'Please provide a unified, comprehensive summary that synthesizes all the above analyses. Note agreements, disagreements, and your overall assessment.';
  1914→
  1915→            // Check token budget
  1916→            var r2Tokens = Math.ceil(round2Content.length / 3.5);
  1917→            var modelLimit = getSmallestModelLimit();
  1918→            var maxChars = Math.floor(modelLimit * 3.5 * 0.85);
  1919→            if (round2Content.length > maxChars) {
  1920→                round2Content = round2Content.substring(0, maxChars) + '\n\n...(Content truncated to fit model limit)';
  1921→                r2Tokens = Math.ceil(round2Content.length / 3.5);
  1922→            }
  1923→
  1924→            console.log('Round 2: ' + round2Content.length + ' chars, ~' + r2Tokens + ' tokens, ' + providersList.length + ' providers');
  1925→
  1926→            document.getElementById('loading-overlay').classList.add('active');
  1927→            document.getElementById('loading-message').textContent = 'Round 2: Synthesizing with ' + providersList.length + ' AI(s)...';
  1928→
  1929→            var requestBody = {
  1930→                user_content: round2Content,
  1931→                providers: providersList
  1932→            };
  1933→            for (var p in modelsMap) {
  1934→                requestBody['model_' + p] = modelsMap[p];
  1935→            }
  1936→
  1937→            var timeoutSec = parseInt(document.getElementById('provider-timeout').value) || 120;
  1938→
  1939→            logAiDebug({
  1940→                type: 'request_round2',
  1941→                thread_id: currentThreadId,
  1942→                agent: selectedAgent,
  1943→                providers: providersList,
  1944→                content_length: round2Content.length,
  1945→                estimated_tokens: r2Tokens,
  1946→                question: 'Round 2 synthesis of ' + successfulResponses.length + ' responses'
  1947→            });
  1948→
  1949→            fetchWithTimeout('../aiapi/api_opus/api/query.php', {

        // ============================================
        var lastRound1Responses = {}; // {providerName: {success, response, model, ...}}
        var lastRound1Providers = [];
        var lastRound1Models = {};
        var lastRound1Question = '';
        var lastFullContent = '';

        // Send Round 2 with all Round 1 responses as context
        function sendRound2(round1Responses, providersList, modelsMap, originalQuestion) {
            var successfulResponses = [];
            for (var prov in round1Responses) {
                var r = round1Responses[prov];
                if (r && r.success && r.response) {
                    successfulResponses.push({
                        provider: prov,
                        model: r.model || 'unknown',
                        response: r.response
                    });
                }
            }

            if (successfulResponses.length === 0) {
                console.warn('No successful Round 1 responses for Round 2');
                return;
            }

            // Build Round 2 prompt
            var round2Content = '=== ROUND 2: UNIFIED ANALYSIS ===\n';
            round2Content += 'You previously analyzed an email conversation. Below are the analyses from ' + successfulResponses.length + ' different AI models.\n';
            round2Content += 'Your task: Synthesize ALL analyses into a single comprehensive summary. Highlight where models AGREE and where they DISAGREE. Provide a final unified assessment.\n\n';
            round2Content += 'Original question: ' + originalQuestion + '\n\n';

            successfulResponses.forEach(function(sr, idx) {
                round2Content += '--- ANALYSIS FROM ' + sr.provider.toUpperCase() + ' (' + sr.model + ') ---\n';
                // Cap each response to 4000 chars to stay within limits
                var respText = sr.response;
                if (respText.length > 4000) {
                    respText = respText.substring(0, 4000) + '\n...(truncated)';
                }
                round2Content += respText + '\n\n';
            });

            round2Content += '=== END OF ROUND 1 ANALYSES ===\n\n';
            round2Content += 'Please provide a unified, comprehensive summary that synthesizes all the above analyses. Note agreements, disagreements, and your overall assessment.';

            // Check token budget
            var r2Tokens = Math.ceil(round2Content.length / 3.5);
            var modelLimit = getSmallestModelLimit();
            var maxChars = Math.floor(modelLimit * 3.5 * 0.85);
            if (round2Content.length > maxChars) {
                round2Content = round2Content.substring(0, maxChars) + '\n\n...(Content truncated to fit model limit)';
                r2Tokens = Math.ceil(round2Content.length / 3.5);
            }

            console.log('Round 2: ' + round2Content.length + ' chars, ~' + r2Tokens + ' tokens, ' + providersList.length + ' providers');

            document.getElementById('loading-overlay').classList.add('active');
            document.getElementById('loading-message').textContent = 'Round 2: Synthesizing with ' + providersList.length + ' AI(s)...';

            var requestBody = {
                user_content: round2Content,
                providers: providersList
            };
            for (var p in modelsMap) {
                requestBody['model_' + p] = modelsMap[p];
            }

            var timeoutSec = parseInt(document.getElementById('provider-timeout').value) || 120;

            logAiDebug({
                type: 'request_round2',
                thread_id: currentThreadId,
                agent: selectedAgent,
                providers: providersList,
                content_length: round2Content.length,
                estimated_tokens: r2Tokens,
                question: 'Round 2 synthesis of ' + successfulResponses.length + ' responses'
            });

            fetchWithTimeout('../aiapi/api_opus/api/query.php', {


1949→            fetchWithTimeout('../aiapi/api_opus/api/query.php', {
  1950→                method: 'POST',
  1951→                headers: { 'Content-Type': 'application/json' },
  1952→                body: JSON.stringify(requestBody)
  1953→            }, timeoutSec * 1000)
  1954→            .then(function(response) {
  1955→                if (!response.ok) throw new Error('HTTP ' + response.status);
  1956→                return response.text();
  1957→            })
  1958→            .then(function(text) {
  1959→                var data;
  1960→                try { data = JSON.parse(text); } catch(e) { throw new Error('Invalid JSON from AI API'); }
  1961→
  1962→                if (data.success) {
  1963→                    displayRound2Response(data);
  1964→
  1965→                    // Save Round 2 responses
  1966→                    providersList.forEach(function(prov) {
  1967→                        var pr = data.responses[prov + '_response'];
  1968→                        if (pr && pr.success) {
  1969→                            saveAIResponse({
  1970→                                thread_ids: [currentThreadId],
  1971→                                contact_id: primaryContactId,
  1972→                                question: 'Round 2 Synthesis: ' + originalQuestion,
  1973→                                agent: selectedAgent,
  1974→                                content_mode: 'round2',
  1975→                                content_length: round2Content.length,
  1976→                                estimated_tokens: r2Tokens,
  1977→                                provider: prov,
  1978→                                model: modelsMap[prov],
  1979→                                query_id: data.query_id,
  1980→                                response: pr,
  1981→                                total_cost: pr.cost || 0,
  1982→                                all_providers: providersList,
  1983→                                round: 2
  1984→                            });
  1985→                        }
  1986→                    });
  1987→
  1988→                    logAiDebug({
  1989→                        type: 'response_round2',
  1990→                        thread_id: currentThreadId,
  1991→                        providers: providersList,
  1992→                        question: 'Round 2 synthesis'
  1993→                    });
  1994→                } else {
  1995→                    alert('Round 2 failed: ' + (data.error || 'Unknown error'));
  1996→                }
  1997→            })
  1998→            .catch(function(err) {
  1999→                console.error('Round 2 error:', err);
  2000→                alert('Round 2 error: ' + err.message);
  2001→            })
  2002→            .finally(function() {
  2003→                document.getElementById('loading-overlay').classList.remove('active');
  2004→                document.getElementById('submit-ai-btn').disabled = false;
  2005→            });
  2006→        }
  2007→
  2008→        // Display Round 2 responses in separate container
  2009→        function displayRound2Response(data) {
  2010→            var container = document.getElementById('ai-response-round2-container');
  2011→            var tabsContainer = document.getElementById('response-tabs-round2');
  2012→            var contentContainer = document.getElementById('ai-responses-content-round2');
  2013→
  2014→            container.style.display = 'block';
  2015→            tabsContainer.innerHTML = '';
  2016→            contentContainer.innerHTML = '';
  2017→
  2018→            var tabIndex = 0;
  2019→            for (var key in data.responses) {
  2020→                var response = data.responses[key];
  2021→                var providerName = key.replace('_response', '');
  2022→                var providerConfig = providers[providerName] || { name: providerName };
  2023→
  2024→                var tab = document.createElement('button');
  2025→                tab.className = 'response-tab' + (tabIndex === 0 ? ' active' : '');
  2026→                tab.textContent = providerConfig.name;
  2027→                tab.dataset.index = tabIndex;
  2028→                (function(idx) {
  2029→                    tab.onclick = function() { switchRound2Tab(idx); };
  2030→                })(tabIndex);
  2031→                tabsContainer.appendChild(tab);
  2032→
  2033→                var content = document.createElement('div');
  2034→                content.className = 'response-content' + (tabIndex === 0 ? ' active' : '');
  2035→                content.id = 'response-tab-r2-' + tabIndex;
  2036→
  2037→                if (response.success) {
  2038→                    content.innerHTML = '
' +
  2039→                        '
' +
  2040→                        '' + escapeHtml(providerConfig.name) + ' Round 2' +
  2041→                        'Model: ' + escapeHtml(response.model || '?') + ' | Time: ' + (response.request_time ? response.request_time.toFixed(2) : '?') + 's | Cost: $' + (response.cost ? response.cost.toFixed(6) : '0') + '' +
  2042→                        '
' +
  2043→                        '
' + escapeHtml(response.response) + '
' +
  2044→                        '
';
  2045→                } else {
  2046→                    content.innerHTML = '
' +
  2047→                        'Error:' +
  2048→                        '
' + escapeHtml(response.error || 'Unknown error') + '

';
  2049→                }
  2050→
  2051→                contentContainer.appendChild(content);
  2052→                tabIndex++;
  2053→            }
  2054→
  2055→            container.scrollIntoView({ behavior: 'smooth' });
  2056→        }
  2057→
  2058→        function switchRound2Tab(index) {
  2059→            var tabs = document.getElementById('response-tabs-round2');
  2060→            var content = document.getElementById('ai-responses-content-round2');
  2061→            if (!tabs || !content) return;
  2062→            tabs.querySelectorAll('.response-tab').forEach(function(t) {
  2063→                t.classList.toggle('active', parseInt(t.dataset.index) === index);
  2064→            });
  2065→            content.querySelectorAll('.response-content').forEach(function(c, i) {
  2066→                c.classList.toggle('active', i === index);
  2067→            });
  2068→        }
  2069→
  2070→        // Manual follow-up: user selects responses and asks a new question
  2071→        function askFollowUp() {
  2072→            var question = prompt('Enter your follow-up question:');
  2073→            if (!question || !question.trim()) return;
  2074→
  2075→            // Collect selected responses
  2076→            var selected = getSelectedResponseTexts();
  2077→            if (selected.length === 0) {
  2078→                alert('Please select at least one response to include as context.');

fetchWithTimeout('../aiapi/api_opus/api/query.php', {
                method: 'POST',
                headers: { 'Content-Type': 'application/json' },
                body: JSON.stringify(requestBody)
            }, timeoutSec * 1000)
            .then(function(response) {
                if (!response.ok) throw new Error('HTTP ' + response.status);
                return response.text();
            })
            .then(function(text) {
                var data;
                try { data = JSON.parse(text); } catch(e) { throw new Error('Invalid JSON from AI API'); }

                if (data.success) {
                    displayRound2Response(data);

                    // Save Round 2 responses
                    providersList.forEach(function(prov) {
                        var pr = data.responses[prov + '_response'];
                        if (pr && pr.success) {
                            saveAIResponse({
                                thread_ids: [currentThreadId],
                                contact_id: primaryContactId,
                                question: 'Round 2 Synthesis: ' + originalQuestion,
                                agent: selectedAgent,
                                content_mode: 'round2',
                                content_length: round2Content.length,
                                estimated_tokens: r2Tokens,
                                provider: prov,
                                model: modelsMap[prov],
                                query_id: data.query_id,
                                response: pr,
                                total_cost: pr.cost || 0,
                                all_providers: providersList,
                                round: 2
                            });
                        }
                    });

                    logAiDebug({
                        type: 'response_round2',
                        thread_id: currentThreadId,
                        providers: providersList,
                        question: 'Round 2 synthesis'
                    });
                } else {
                    alert('Round 2 failed: ' + (data.error || 'Unknown error'));
                }
            })
            .catch(function(err) {
                console.error('Round 2 error:', err);
                alert('Round 2 error: ' + err.message);
            })
            .finally(function() {
                document.getElementById('loading-overlay').classList.remove('active');
                document.getElementById('submit-ai-btn').disabled = false;
            });
        }

        // Display Round 2 responses in separate container
        function displayRound2Response(data) {
            var container = document.getElementById('ai-response-round2-container');
            var tabsContainer = document.getElementById('response-tabs-round2');
            var contentContainer = document.getElementById('ai-responses-content-round2');

            container.style.display = 'block';
            tabsContainer.innerHTML = '';
            contentContainer.innerHTML = '';

            var tabIndex = 0;
            for (var key in data.responses) {
                var response = data.responses[key];
                var providerName = key.replace('_response', '');
                var providerConfig = providers[providerName] || { name: providerName };

                var tab = document.createElement('button');
                tab.className = 'response-tab' + (tabIndex === 0 ? ' active' : '');
                tab.textContent = providerConfig.name;
                tab.dataset.index = tabIndex;
                (function(idx) {
                    tab.onclick = function() { switchRound2Tab(idx); };
                })(tabIndex);
                tabsContainer.appendChild(tab);

                var content = document.createElement('div');
                content.className = 'response-content' + (tabIndex === 0 ? ' active' : '');
                content.id = 'response-tab-r2-' + tabIndex;

                if (response.success) {
                    content.innerHTML = '
' +
                        '
' +
                        '' + escapeHtml(providerConfig.name) + ' Round 2' +
                        'Model: ' + escapeHtml(response.model || '?') + ' | Time: ' + (response.request_time ? response.request_time.toFixed(2) : '?') + 's | Cost: $' + (response.cost ? response.cost.toFixed(6) : '0') + '' +
                        '
' +
                        '
' + escapeHtml(response.response) + '
' +
                        '
';
                } else {
                    content.innerHTML = '
' +
                        'Error:' +
                        '
' + escapeHtml(response.error || 'Unknown error') + '

';
                }

                contentContainer.appendChild(content);
                tabIndex++;
            }

            container.scrollIntoView({ behavior: 'smooth' });
        }

        function switchRound2Tab(index) {
            var tabs = document.getElementById('response-tabs-round2');
            var content = document.getElementById('ai-responses-content-round2');
            if (!tabs || !content) return;
            tabs.querySelectorAll('.response-tab').forEach(function(t) {
                t.classList.toggle('active', parseInt(t.dataset.index) === index);
            });
            content.querySelectorAll('.response-content').forEach(function(c, i) {
                c.classList.toggle('active', i === index);
            });
        }

        // Manual follow-up: user selects responses and asks a new question
        function askFollowUp() {
            var question = prompt('Enter your follow-up question:');
            if (!question || !question.trim()) return;

            // Collect selected responses
            var selected = getSelectedResponseTexts();
            if (selected.length === 0) {
                alert('Please select at least one response to include as context.');


Good. Now I have the full picture. The key changes needed are at lines 2931-2942 in `submitToAI()`. I need to:

1. Pass `'Round 1'` to `displayAIResponse(data)`
2. Store `lastRound1Providers`, `lastRound1Models`, `lastRound1Question`
3. Check if two-round mode is enabled and trigger `sendRound2()`
4. Keep the loading overlay active between rounds if auto Round 2 is triggered


Edit

                    // Clear the question field for next question
                    document.getElementById('ai-question').value = '';
                    updateTokenEstimate();

                    // Display response
                    displayAIResponse(data);
                } else {
                    alert('AI request failed: ' + (data.error || 'Unknown error'));
                }
            } catch (error) {
                console.error('AI request error:', error);
                alert('Error: ' + error.message);
            } finally {
                document.getElementById('loading-overlay').classList.remove('active');
                document.getElementById('submit-ai-btn').disabled = false;
            }
        }

                    // Clear the question field for next question
                    document.getElementById('ai-question').value = '';
                    updateTokenEstimate();

                    // Store Round 1 info for potential Round 2 / follow-ups
                    lastRound1Providers = selectedProvidersList.slice();
                    lastRound1Models = Object.assign({}, modelsMap);
                    lastRound1Question = actualQuestion;
                    lastFullContent = fullContent;

                    // Display Round 1 response
                    displayAIResponse(data, 'Round 1');

                    // Check if Two-Round mode is enabled → auto-trigger Round 2
                    var twoRoundCheckbox = document.getElementById('two-round-mode');
                    if (twoRoundCheckbox && twoRoundCheckbox.checked) {
                        // Count successful responses
                        var r1SuccessCount = 0;
                        for (var rk in lastRound1Responses) {
                            if (lastRound1Responses[rk] && lastRound1Responses[rk].success) r1SuccessCount++;
                        }
                        if (r1SuccessCount > 0) {
                            // Keep loading overlay active — sendRound2 will manage it
                            document.getElementById('loading-message').textContent = 'Round 1 complete (' + r1SuccessCount + ' responses). Starting Round 2 synthesis...';
                            sendRound2(lastRound1Responses, lastRound1Providers, lastRound1Models, lastRound1Question);
                            return; // Don't hide overlay — sendRound2's finally will do it
                        }
                    }
                } else {
                    alert('AI request failed: ' + (data.error || 'Unknown error'));
                }
            } catch (error) {
                console.error('AI request error:', error);
                alert('Error: ' + error.message);
            } finally {
                document.getElementById('loading-overlay').classList.remove('active');
                document.getElementById('submit-ai-btn').disabled = false;
            }
        }