phase 2

supabase/functions/writing-check/index.ts

@@ -0,0 +1,73 @@
+// Supabase Edge Function: writing-check
+// Uses GLM API (OpenAI-compatible) to analyze English writing submissions.
+// Deploy: supabase functions deploy writing-check
+// Secrets: supabase secrets set GLM_API_KEY=<your_key>
+
+import OpenAI from "npm:openai@^4"
+
+const glm = new OpenAI({
+  apiKey: Deno.env.get("GLM_API_KEY") ?? "",
+  baseURL: "https://open.bigmodel.cn/api/paas/v4/",
+})
+
+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:
+{
+  "score": "<estimated band score, e.g. 6.5>",
+  "grammar": ["<issue 1 with correction, mix English example + Vietnamese explanation>", ...],
+  "vocabulary": ["<vocabulary observation in Vietnamese>", ...],
+  "structure": "<2–3 sentence structure assessment in Vietnamese>",
+  "improved_version": "<the full improved text in English>",
+  "summary": "<2–3 sentence overall assessment in Vietnamese>"
+}`
+
+Deno.serve(async (req: Request) => {
+  // Handle CORS pre-flight
+  if (req.method === "OPTIONS") {
+    return new Response("ok", { headers: CORS_HEADERS })
+  }
+
+  try {
+    const { content } = await req.json() as { content: string }
+
+    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 },
+      )
+    }
+
+    const completion = await glm.chat.completions.create({
+      // GLM-4-32B-0414-128K: cheapest paid model at $0.1/$0.1 per 1M tokens.
+      // Override via: supabase secrets set GLM_MODEL=<other-model>
+      model: Deno.env.get("GLM_MODEL") ?? "GLM-4-32B-0414-128K",
+      messages: [
+        { role: "system", content: SYSTEM_PROMPT },
+        { role: "user", content: `Analyse this writing:\n\n${content.slice(0, 2000)}` },
+      ],
+      temperature: 0.3,
+      max_tokens: 1500,
+    })
+
+    const raw = completion.choices[0]?.message?.content ?? "{}"
+
+    // 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 })
+  } 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 },
+    )
+  }
+})