// Supabase Edge Function: writing-check
// Uses GLM API (OpenAI-compatible) to analyze English writing submissions.
// Deploy: supabase functions deploy writing-check --no-verify-jwt
// 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",
}

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) => {
  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, "Content-Type": "application/json" } },
      )
    }

    const stream = await glm.chat.completions.create({
      model: Deno.env.get("GLM_MODEL") ?? "GLM-4.5-Flash",
      messages: [
        { role: "system", content: SYSTEM_PROMPT },
        { role: "user", content: `Analyse this writing:\n\n${content.slice(0, 2000)}` },
      ],
      temperature: 0.3,
      max_tokens: 1500,
      stream: true,
    })

    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()
      },
    })

    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, "Content-Type": "application/json" } },
    )
  }
})