feat: Generation Page AI workflows + AI/Vector modules + exam session fixes

Generation Page (complete rebuild):
- Full production-parity exam generation wizard with 4 IELTS modules
- Reading: AI passage gen, 5 exercise types (MCQ, Fill, Write, T/F, Match)
- Listening: 4 section types, AI context gen, TTS audio gen (ElevenLabs)
- Writing: Task 1/2, AI instruction gen, word limits, marks
- Speaking: 3 parts, AI script gen, avatar video gen (7 avatars)
- Per-module config: timer, CEFR difficulty, access, approval, rubrics
- Exam submission workflow (draft/published)

Exam Structures:
- New encoach.exam.structure model + CRUD controller
- ExamStructuresPage wired to real API

AI Module (encoach_ai):
- OpenAI service, ElevenLabs TTS, AWS Polly, ELAI avatars
- AI settings model with Odoo config parameters
- 7 generation endpoints (passage, exercises, instructions, scripts, context)

Vector Module (encoach_vector):
- pgvector integration for RAG-based content search
- Embedding service with sentence-transformers

Exam Session Fixes:
- Fixed ExamSession.tsx field mapping (question_type→type, exam_title→title)
- Fixed submit payload to include attempt_id and answers
- Fixed normalizeType to handle null/undefined

Tested: 12/12 API tests passed, browser-verified with real OpenAI calls
Made-with: Cursor

src/components/ai/AiBatchOptimizer.tsx

@@ -25,6 +25,8 @@ export default function AiBatchOptimizer({ batchId }: Props) {
     },
   });
 
+  type OptResult = Awaited<ReturnType<typeof analyticsService.getBatchOptimization>>;
+
   const handleOpen = () => {
     if (batchId == null) {
       toast({
@@ -39,9 +41,23 @@ export default function AiBatchOptimizer({ batchId }: Props) {
     mutation.mutate(batchId);
   };
 
+  const applyMutation = useMutation({
+    mutationFn: () => analyticsService.applyBatchOptimization(batchId!, mutation.data?.optimized ?? []),
+    onSuccess: (res) => {
+      toast({ title: "Suggestion Applied", description: `${res.applied} optimization(s) saved successfully.` });
+      setOpen(false);
+    },
+    onError: (err: Error) => {
+      toast({
+        variant: "destructive",
+        title: "Apply failed",
+        description: err.message || "Could not apply batch optimization.",
+      });
+    },
+  });
+
   const handleApply = () => {
-    toast({ title: "Suggestion Applied", description: "Batch split recommendation has been saved successfully." });
-    setOpen(false);
+    applyMutation.mutate();
   };
 
   const onOpenChange = (next: boolean) => {
@@ -49,9 +65,10 @@ export default function AiBatchOptimizer({ batchId }: Props) {
     if (!next) mutation.reset();
   };
 
-  const suggestions = mutation.data ?? [];
-  const showResults = !mutation.isPending && !mutation.isError && suggestions.length > 0;
-  const showEmpty = !mutation.isPending && !mutation.isError && mutation.isSuccess && suggestions.length === 0;
+  const optData = mutation.data as OptResult | undefined;
+  const hasSuggestions = !!optData?.summary;
+  const showResults = !mutation.isPending && !mutation.isError && hasSuggestions;
+  const showEmpty = !mutation.isPending && !mutation.isError && mutation.isSuccess && !hasSuggestions;
 
   return (
     <>
@@ -71,20 +88,28 @@ export default function AiBatchOptimizer({ batchId }: Props) {
             </div>
           ) : mutation.isError ? (
             <p className="text-sm text-muted-foreground py-4 text-center">Something went wrong. Try again.</p>
-          ) : showResults ? (
+          ) : showResults && optData ? (
             <div className="space-y-4">
-              <div className="space-y-3 max-h-[50vh] overflow-y-auto">
-                {suggestions.map((s, i) => (
-                  <div key={i} className="rounded-lg bg-muted/30 p-4 border border-border/60">
-                    <p className="text-xs font-semibold text-primary uppercase tracking-wide mb-1">{s.impact} impact</p>
-                    <p className="text-sm font-medium">{s.suggestion}</p>
-                    {s.details ? <p className="text-sm text-muted-foreground mt-2 leading-relaxed">{s.details}</p> : null}
-                  </div>
-                ))}
+              <div className="rounded-lg bg-muted/30 p-4 border border-border/60">
+                <p className="text-xs font-semibold text-primary uppercase tracking-wide mb-1">{optData.impact} impact</p>
+                <p className="text-sm font-medium">{optData.summary}</p>
               </div>
+              {Array.isArray(optData.optimized) && optData.optimized.length > 0 && (
+                <div className="space-y-2 max-h-[40vh] overflow-y-auto">
+                  {optData.optimized.map((item, i) => (
+                    <div key={i} className="rounded-lg bg-muted/20 p-3 border text-sm">
+                      {typeof item === "object" && item !== null ? JSON.stringify(item) : String(item)}
+                    </div>
+                  ))}
+                </div>
+              )}
               <div className="flex gap-2">
-                <Button className="flex-1" onClick={handleApply}>
-                  Apply Suggestion
+                <Button className="flex-1" onClick={handleApply} disabled={applyMutation.isPending}>
+                  {applyMutation.isPending ? (
+                    <><Loader2 className="h-4 w-4 mr-2 animate-spin" /> Applying...</>
+                  ) : (
+                    "Apply Suggestion"
+                  )}
                 </Button>
                 <Button variant="outline" onClick={() => onOpenChange(false)}>
                   Dismiss