دورة الذكاء الاصطناعي العملية

import { z } from "zod";

export const TicketSchema = z.object({
  category: z.enum(["billing", "technical", "account", "other"]),
  urgency: z.number().int().min(1).max(5),
  summary_ar: z.string().max(200),
  needs_human: z.boolean(),
});
export type Ticket = z.infer<typeof TicketSchema>;

const SYSTEM = `أنت مصنّف طلبات دعم.
- صنّف الطلب ولا تجب على العميل.
- إن كان الطلب يتضمن شكوى قانونية أو مالية حسّاسة اجعل needs_human = true.
- أعد JSON فقط بلا أي نص إضافي.`;

export async function classify(ticketText: string): Promise<Ticket> {
  const res = await fetch("https://ai.gateway.lovable.dev/v1/chat/completions", {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env["LOVABLE_API_KEY"]}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      model: "google/gemini-2.5-flash",
      temperature: 0,
      messages: [
        { role: "system", content: SYSTEM },
        { role: "user", content: ticketText },
      ],
      response_format: {
        type: "json_schema",
        json_schema: {
          name: "ticket",
          strict: true,
          schema: {
            type: "object",
            additionalProperties: false,
            required: ["category", "urgency", "summary_ar", "needs_human"],
            properties: {
              category: { type: "string", enum: ["billing", "technical", "account", "other"] },
              urgency: { type: "integer", minimum: 1, maximum: 5 },
              summary_ar: { type: "string" },
              needs_human: { type: "boolean" },
            },
          },
        },
      },
    }),
  });

  const json = await res.json();
  // لا تثق بالمخرج: تحقّق دائماً قبل التخزين أو العرض
  return TicketSchema.parse(JSON.parse(json.choices[0].message.content));
}

يجبر النموذج على مخطط JSON ثابت ثم يتحقّق منه بـ Zod قبل استخدامه.

create extension if not exists vector;

create table public.doc_chunks (
  id uuid primary key default gen_random_uuid(),
  owner_id uuid not null references auth.users(id) on delete cascade,
  source_title text not null,
  source_url text,
  chunk_index int not null,
  content text not null,
  embedding vector(768) not null,
  created_at timestamptz not null default now()
);

grant select, insert, update, delete on public.doc_chunks to authenticated;
grant all on public.doc_chunks to service_role;

alter table public.doc_chunks enable row level security;

create policy "owners read their chunks"
on public.doc_chunks for select to authenticated
using (owner_id = auth.uid());

create policy "owners write their chunks"
on public.doc_chunks for insert to authenticated
with check (owner_id = auth.uid());

create index doc_chunks_embedding_idx
  on public.doc_chunks using ivfflat (embedding vector_cosine_ops) with (lists = 100);

جدول المقاطع مع عمود متجهي وفهرس بحث تقريبي — مع GRANT وRLS كما في الإنتاج.

export function chunk(text: string, size = 900, overlap = 150) {
  const clean = text.replace(/\s+/g, " ").trim();
  const out: string[] = [];
  for (let i = 0; i < clean.length; i += size - overlap) {
    out.push(clean.slice(i, i + size));
  }
  return out.filter((c) => c.length > 80);
}

export async function embed(input: string[]): Promise<number[][]> {
  const res = await fetch("https://ai.gateway.lovable.dev/v1/embeddings", {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env["LOVABLE_API_KEY"]}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({ model: "google/text-embedding-004", input }),
  });
  const json = await res.json();
  return json.data.map((d: { embedding: number[] }) => d.embedding);
}

/** يعيد أفضل k مقاطع مع عنوان ورابط المصدر للاستشهاد. */
export async function retrieve(supabase: SupabaseClient, question: string, k = 3) {
  const [queryEmbedding] = await embed([question]);
  const { data, error } = await supabase.rpc("match_doc_chunks", {
    query_embedding: queryEmbedding,
    match_count: k,
    min_similarity: 0.72,
  });
  if (error) throw new Error(error.message);
  return data as { content: string; source_title: string; source_url: string | null }[];
}

تقطيع بتداخل، توليد التضمينات، ثم استرجاع أفضل 3 مقاطع مع مصدرها.