add dbiz, add history

supabase/functions/writing-check/index.ts

@@ -1,6 +1,6 @@
 // Supabase Edge Function: writing-check
 // Uses GLM API (OpenAI-compatible) to analyze English writing submissions.
-// Deploy: supabase functions deploy writing-check
+// Deploy: supabase functions deploy writing-check --no-verify-jwt
 // Secrets: supabase secrets set GLM_API_KEY=<your_key>
 
 import OpenAI from "npm:openai@^4"
@@ -13,10 +13,8 @@ const glm = new OpenAI({
 const CORS_HEADERS = {
   "Access-Control-Allow-Origin": "*",
   "Access-Control-Allow-Headers": "authorization, x-client-info, apikey, content-type",
-  "Content-Type": "application/json",
 }
 
-// Instructs the model to return a strict JSON structure with Vietnamese feedback.
 const SYSTEM_PROMPT = `You are an expert English writing teacher specialising in TOEIC and IELTS assessment.
 Analyse the student's writing and respond ONLY with valid JSON — no markdown, no extra text:
 {
@@ -29,7 +27,6 @@ Analyse the student's writing and respond ONLY with valid JSON — no markdown,
 }`
 
 Deno.serve(async (req: Request) => {
-  // Handle CORS pre-flight
   if (req.method === "OPTIONS") {
     return new Response("ok", { headers: CORS_HEADERS })
   }
@@ -40,13 +37,11 @@ Deno.serve(async (req: Request) => {
     if (!content || content.trim().length < 10) {
       return new Response(
         JSON.stringify({ error: "Bài viết quá ngắn. Vui lòng nhập ít nhất 10 ký tự." }),
-        { status: 400, headers: CORS_HEADERS },
+        { status: 400, headers: { ...CORS_HEADERS, "Content-Type": "application/json" } },
       )
     }
 
-    const completion = await glm.chat.completions.create({
-      // GLM-4-32B-0414-128K: cheapest paid model at $0.1/$0.1 per 1M tokens.
-      // Override via: supabase secrets set GLM_MODEL=<other-model>
+    const stream = await glm.chat.completions.create({
       model: Deno.env.get("GLM_MODEL") ?? "GLM-4.5-Flash",
       messages: [
         { role: "system", content: SYSTEM_PROMPT },
@@ -54,20 +49,42 @@ Deno.serve(async (req: Request) => {
       ],
       temperature: 0.3,
       max_tokens: 1500,
+      stream: true,
     })
 
-    const raw = completion.choices[0]?.message?.content ?? "{}"
+    const encoder = new TextEncoder()
+    const body = new ReadableStream({
+      async start(controller) {
+        try {
+          for await (const chunk of stream) {
+            const text = chunk.choices[0]?.delta?.content ?? ""
+            if (text) {
+              controller.enqueue(encoder.encode(`data: ${JSON.stringify({ text })}\n\n`))
+            }
+          }
+        } catch (err) {
+          console.error("writing-check stream error:", err)
+          controller.enqueue(
+            encoder.encode(`data: ${JSON.stringify({ error: "Đã có lỗi khi chấm bài. Vui lòng thử lại." })}\n\n`),
+          )
+        }
+        controller.enqueue(encoder.encode("data: [DONE]\n\n"))
+        controller.close()
+      },
+    })
 
-    // Strip markdown code fences if the model adds them despite instructions
-    const cleaned = raw.replace(/^```(?:json)?\s*/i, "").replace(/\s*```$/, "").trim()
-    const feedback = JSON.parse(cleaned)
-
-    return new Response(JSON.stringify(feedback), { headers: CORS_HEADERS })
+    return new Response(body, {
+      headers: {
+        ...CORS_HEADERS,
+        "Content-Type": "text/event-stream",
+        "Cache-Control": "no-cache",
+      },
+    })
   } catch (err) {
     console.error("writing-check error:", err)
     return new Response(
       JSON.stringify({ error: "Đã có lỗi khi chấm bài. Vui lòng thử lại." }),
-      { status: 500, headers: CORS_HEADERS },
+      { status: 500, headers: { ...CORS_HEADERS, "Content-Type": "application/json" } },
     )
   }
 })