74 lines
2.8 KiB
TypeScript
74 lines
2.8 KiB
TypeScript
// Supabase Edge Function: writing-check
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// Uses GLM API (OpenAI-compatible) to analyze English writing submissions.
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// Deploy: supabase functions deploy writing-check
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// Secrets: supabase secrets set GLM_API_KEY=<your_key>
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import OpenAI from "npm:openai@^4"
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const glm = new OpenAI({
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apiKey: Deno.env.get("GLM_API_KEY") ?? "",
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baseURL: "https://open.bigmodel.cn/api/paas/v4/",
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})
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const CORS_HEADERS = {
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"Access-Control-Allow-Origin": "*",
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"Access-Control-Allow-Headers": "authorization, x-client-info, apikey, content-type",
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"Content-Type": "application/json",
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}
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// Instructs the model to return a strict JSON structure with Vietnamese feedback.
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const SYSTEM_PROMPT = `You are an expert English writing teacher specialising in TOEIC and IELTS assessment.
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Analyse the student's writing and respond ONLY with valid JSON — no markdown, no extra text:
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{
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"score": "<estimated band score, e.g. 6.5>",
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"grammar": ["<issue 1 with correction, mix English example + Vietnamese explanation>", ...],
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"vocabulary": ["<vocabulary observation in Vietnamese>", ...],
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"structure": "<2–3 sentence structure assessment in Vietnamese>",
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"improved_version": "<the full improved text in English>",
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"summary": "<2–3 sentence overall assessment in Vietnamese>"
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}`
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Deno.serve(async (req: Request) => {
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// Handle CORS pre-flight
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if (req.method === "OPTIONS") {
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return new Response("ok", { headers: CORS_HEADERS })
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}
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try {
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const { content } = await req.json() as { content: string }
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if (!content || content.trim().length < 10) {
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return new Response(
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JSON.stringify({ error: "Bài viết quá ngắn. Vui lòng nhập ít nhất 10 ký tự." }),
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{ status: 400, headers: CORS_HEADERS },
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)
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}
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const completion = await glm.chat.completions.create({
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// GLM-4-32B-0414-128K: cheapest paid model at $0.1/$0.1 per 1M tokens.
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// Override via: supabase secrets set GLM_MODEL=<other-model>
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model: Deno.env.get("GLM_MODEL") ?? "GLM-4-32B-0414-128K",
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messages: [
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{ role: "system", content: SYSTEM_PROMPT },
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{ role: "user", content: `Analyse this writing:\n\n${content.slice(0, 2000)}` },
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],
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temperature: 0.3,
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max_tokens: 1500,
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})
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const raw = completion.choices[0]?.message?.content ?? "{}"
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// Strip markdown code fences if the model adds them despite instructions
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const cleaned = raw.replace(/^```(?:json)?\s*/i, "").replace(/\s*```$/, "").trim()
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const feedback = JSON.parse(cleaned)
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return new Response(JSON.stringify(feedback), { headers: CORS_HEADERS })
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} catch (err) {
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console.error("writing-check error:", err)
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return new Response(
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JSON.stringify({ error: "Đã có lỗi khi chấm bài. Vui lòng thử lại." }),
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{ status: 500, headers: CORS_HEADERS },
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)
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}
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})
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