import { NextRequest, NextResponse } from "next/server";
import { z } from "zod";
import { db, recipes, recipeIngredients, recipeSteps } from "@epicure/db";
import { requireSessionOrApiKey } from "@/lib/api-auth";
import { applyRateLimit } from "@/lib/rate-limit";
import { withAiQuota, resolveAiConfigOrError } from "@/lib/ai/ai-error";
import { importFromPhoto } from "@/lib/ai/features/import-photo";
import { getModelConfigForUseCase } from "@/lib/ai/resolve-user-key";
import { checkTierLimitInTransaction, TierLimitError } from "@/lib/tiers";
import { requireFeatureEnabledResponse } from "@/lib/feature-flags";

const Schema = z.object({
  imageBase64: z.string().max(14_000_000),
  mimeType: z.enum(["image/jpeg", "image/png", "image/webp"]),
});

export async function POST(req: NextRequest) {
  const { session, response } = await requireSessionOrApiKey(req);
  if (response) return response;

  const featureDenied = await requireFeatureEnabledResponse(session!.user.id, "recipe_import_photo");
  if (featureDenied) return featureDenied;

  const body = await req.json() as unknown;
  const parsed = Schema.safeParse(body);
  if (!parsed.success) {
    return NextResponse.json({ error: "Validation error", issues: parsed.error.issues }, { status: 400 });
  }

  const limited = await applyRateLimit(`rl:ai:${session!.user.id}`, 5, 60);
  if (limited) return limited;

  const userId = session!.user.id;
  const locale = (session!.user as { locale?: string }).locale ?? "en";

  const visionConfigResult = await resolveAiConfigOrError(() => getModelConfigForUseCase(userId, "vision"));
  if (!visionConfigResult.ok) return visionConfigResult.response;
  const visionConfig = visionConfigResult.data;

  // Fall back to vision-capable defaults if no explicit model configured
  if (!visionConfig.model) {
    if (visionConfig.provider === "openai") visionConfig.model = "gpt-4o";
    else if (visionConfig.provider === "anthropic") visionConfig.model = "claude-sonnet-4-6";
  }

  const textConfigResult = await resolveAiConfigOrError(() => getModelConfigForUseCase(userId, "text"));
  if (!textConfigResult.ok) return textConfigResult.response;
  const textConfig = textConfigResult.data;

  const result = await withAiQuota(userId, session!.user.tier as "free" | "pro" | "family", () =>
    importFromPhoto(parsed.data.imageBase64, parsed.data.mimeType, visionConfig, textConfig, locale),
    { skipQuota: visionConfig.isByok && textConfig.isByok }
  );
  if (!result.ok) return result.response;
  const recipe = result.data;

  if (!recipe.found) {
    return NextResponse.json({ error: "No recipe recognized in photo" }, { status: 422 });
  }

  const newRecipeId = crypto.randomUUID();
  const now = new Date();

  try {
    await db.transaction(async (tx) => {
    await checkTierLimitInTransaction(tx, userId, session!.user.tier as "free" | "pro" | "family", "recipe");
    await tx.insert(recipes).values({
      id: newRecipeId,
      authorId: userId,
      title: recipe.title,
      description: recipe.description,
      baseServings: recipe.baseServings ?? 4,
      recipeType: recipe.recipeType,
      visibility: "private",
      difficulty: recipe.difficulty,
      prepMins: recipe.prepMins,
      cookMins: recipe.cookMins,
      dietaryTags: recipe.dietaryTags ?? {},
      aiGenerated: true,
      // The extraction prompt always writes the recipe in the caller's own
      // locale (see importFromPhoto's langInstruction) regardless of what
      // language the photo/label was in — so this *is* the recipe's
      // language, not a guess, and lets the Translate button correctly
      // stay hidden until the user's app language changes.
      language: locale,
      createdAt: now,
      updatedAt: now,
    });

    if (recipe.ingredients.length > 0) {
      await tx.insert(recipeIngredients).values(
        recipe.ingredients.map((ing, i) => ({
          id: crypto.randomUUID(),
          recipeId: newRecipeId,
          rawName: ing.rawName,
          quantity: ing.quantity !== undefined ? String(ing.quantity) : undefined,
          unit: ing.unit,
          note: ing.note,
          order: i,
        }))
      );
    }

    if (recipe.steps.length > 0) {
      await tx.insert(recipeSteps).values(
        recipe.steps.map((step, i) => ({
          id: crypto.randomUUID(),
          recipeId: newRecipeId,
          instruction: step.instruction,
          timerSeconds: step.timerSeconds,
          order: i,
        }))
      );
    }
    });
  } catch (err) {
    if (err instanceof TierLimitError) {
      return NextResponse.json({ error: "Recipe limit reached for your tier" }, { status: 403 });
    }
    throw err;
  }

  return NextResponse.json({ id: newRecipeId });
}
