Files
encoach_frontend_new_v2/src/components/ai/AiBatchOptimizer.tsx
Yamen Ahmad 74c2c9f2d2 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
2026-04-11 14:27:03 +04:00

127 lines
4.7 KiB
TypeScript

import { useState } from "react";
import { useMutation } from "@tanstack/react-query";
import { Dialog, DialogContent, DialogHeader, DialogTitle } from "@/components/ui/dialog";
import { Button } from "@/components/ui/button";
import { Sparkles, Loader2 } from "lucide-react";
import { useToast } from "@/hooks/use-toast";
import { analyticsService } from "@/services/analytics.service";
interface Props {
batchId?: number;
}
export default function AiBatchOptimizer({ batchId }: Props) {
const [open, setOpen] = useState(false);
const { toast } = useToast();
const mutation = useMutation({
mutationFn: (id: number) => analyticsService.getBatchOptimization(id),
onError: (err: Error) => {
toast({
title: "Optimization failed",
description: err.message || "Could not analyze this batch.",
variant: "destructive",
});
},
});
type OptResult = Awaited<ReturnType<typeof analyticsService.getBatchOptimization>>;
const handleOpen = () => {
if (batchId == null) {
toast({
title: "No batch selected",
description: "Choose a batch to analyze, or open this from a batch detail page.",
variant: "destructive",
});
return;
}
mutation.reset();
setOpen(true);
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 = () => {
applyMutation.mutate();
};
const onOpenChange = (next: boolean) => {
setOpen(next);
if (!next) mutation.reset();
};
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 (
<>
<Button variant="outline" size="sm" onClick={handleOpen}>
<Sparkles className="h-3.5 w-3.5 mr-1 text-primary" /> AI Suggest Batch Split
</Button>
<Dialog open={open} onOpenChange={onOpenChange}>
<DialogContent className="max-w-md">
<DialogHeader>
<DialogTitle className="flex items-center gap-2">
<Sparkles className="h-4 w-4 text-primary" /> AI Batch Optimization
</DialogTitle>
</DialogHeader>
{mutation.isPending ? (
<div className="flex items-center gap-2 text-sm text-muted-foreground py-6 justify-center">
<Loader2 className="h-5 w-5 animate-spin text-primary" /> Analyzing batch data...
</div>
) : mutation.isError ? (
<p className="text-sm text-muted-foreground py-4 text-center">Something went wrong. Try again.</p>
) : showResults && optData ? (
<div className="space-y-4">
<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} 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
</Button>
</div>
</div>
) : showEmpty ? (
<p className="text-sm text-muted-foreground py-4 text-center">No optimization suggestions for this batch.</p>
) : null}
</DialogContent>
</Dialog>
</>
);
}