// 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 },
    )
  }
})