import { randomUUID } from "node:crypto";
import { mkdir, rm } from "node:fs/promises";
import { tmpdir } from "node:os";
import { join } from "node:path";
import { outpaint } from "@snapotter/ai";
import { getBundleForTool, TOOL_BUNDLE_MAP } from "@snapotter/shared";
import type { FastifyInstance, FastifyReply, FastifyRequest } from "fastify";
import sharp from "sharp";
import { z } from "zod";
import { registerAiJobHandler } from "../../jobs/ai-handlers.js";
import { enqueueToolJob } from "../../jobs/enqueue.js";
import { autoOrient } from "../../lib/auto-orient.js";
import { formatZodErrors, stripInternalPaths } from "../../lib/errors.js";
import { isToolInstalled } from "../../lib/feature-status.js";
import { validateImageBuffer } from "../../lib/file-validation.js";
import { decodeToSharpCompat, needsCliDecode } from "../../lib/format-decoders.js";
import { encodeJxl } from "../../lib/format-encoders.js";
import { decodeHeic, encodeHeic } from "../../lib/heic-converter.js";
import { getObjectBuffer, putObject } from "../../lib/object-storage.js";
import { resolveOutputFormat } from "../../lib/output-format.js";
import { receiveUpload } from "../../lib/upload-stream.js";
import { getAuthUser } from "../../plugins/auth.js";
import { registerToolProcessFn } from "../tool-factory.js";

const settingsSchema = z.object({
  extendTop: z.number().int().min(0).default(0),
  extendRight: z.number().int().min(0).default(0),
  extendBottom: z.number().int().min(0).default(0),
  extendLeft: z.number().int().min(0).default(0),
  tier: z.enum(["fast", "balanced", "high"]).default("balanced"),
  format: z
    .enum(["auto", "png", "jpg", "jpeg", "webp", "tiff", "gif", "avif", "heic", "heif", "jxl"])
    .default("auto"),
  quality: z.number().int().min(1).max(100).default(95),
});

type Settings = z.infer<typeof settingsSchema>;

// ── AI job handler ────────────────────────────────────────────────
registerAiJobHandler("ai-canvas-expand", async (input, data, ctx) => {
  const settings = settingsSchema.parse(data.settings);
  let format: string = settings.format;
  let quality = settings.quality;

  if (format === "auto") {
    const detected = await resolveOutputFormat(input, data.filename);
    format = detected.format === "jpeg" ? "jpg" : detected.format;
    quality = detected.quality;
  }

  const resultBuffer = await outpaint(
    input,
    {
      extendTop: settings.extendTop,
      extendRight: settings.extendRight,
      extendBottom: settings.extendBottom,
      extendLeft: settings.extendLeft,
      tier: settings.tier,
    },
    ctx.scratchDir,
    (percent, stage) => ctx.report(percent, stage),
  );

  // Convert to requested output format
  const needsNodeConversion = ["heic", "heif", "avif", "jxl"].includes(format);
  let outputBuffer: Buffer;
  let finalFormat = format;

  if (needsNodeConversion) {
    if (format === "heic" || format === "heif") {
      outputBuffer = await encodeHeic(resultBuffer, quality);
      finalFormat = format;
    } else if (format === "jxl") {
      outputBuffer = await encodeJxl(resultBuffer, quality);
      finalFormat = "jxl";
    } else {
      outputBuffer = await sharp(resultBuffer).avif({ quality }).toBuffer();
      finalFormat = "avif";
    }
  } else if (format === "jpg" || format === "jpeg") {
    outputBuffer = await sharp(resultBuffer).jpeg({ quality }).toBuffer();
    finalFormat = "jpg";
  } else if (format === "webp") {
    outputBuffer = await sharp(resultBuffer).webp({ quality }).toBuffer();
    finalFormat = "webp";
  } else if (format === "tiff") {
    outputBuffer = await sharp(resultBuffer).tiff({ quality }).toBuffer();
    finalFormat = "tiff";
  } else if (format === "gif") {
    outputBuffer = await sharp(resultBuffer).gif().toBuffer();
    finalFormat = "gif";
  } else {
    outputBuffer = resultBuffer;
    finalFormat = "png";
  }

  const EXT_MAP: Record<string, string> = {
    jpeg: "jpg",
    jpg: "jpg",
    png: "png",
    webp: "webp",
    tiff: "tiff",
    gif: "gif",
    avif: "avif",
    heic: "heic",
    heif: "heif",
    jxl: "jxl",
  };
  const ext = EXT_MAP[finalFormat] || "png";
  const outputFilename = `${data.filename.replace(/\.[^.]+$/, "")}_extended.${ext}`;

  const CONTENT_TYPES: Record<string, string> = {
    png: "image/png",
    jpg: "image/jpeg",
    jpeg: "image/jpeg",
    webp: "image/webp",
    tiff: "image/tiff",
    gif: "image/gif",
    avif: "image/avif",
    heic: "image/heic",
    heif: "image/heif",
    jxl: "image/jxl",
  };

  return {
    buffer: outputBuffer,
    filename: outputFilename,
    contentType: CONTENT_TYPES[finalFormat] || "image/png",
  };
});

export function registerAiCanvasExpand(app: FastifyInstance) {
  app.post(
    "/api/v1/tools/image/ai-canvas-expand",
    async (request: FastifyRequest, reply: FastifyReply) => {
      const toolId = "ai-canvas-expand";
      if (!isToolInstalled(toolId)) {
        const bundle = getBundleForTool(toolId);
        return reply.status(501).send({
          error: "Feature not installed",
          code: "FEATURE_NOT_INSTALLED",
          feature: TOOL_BUNDLE_MAP[toolId],
          featureName: bundle?.name ?? toolId,
          estimatedSize: bundle?.estimatedSize ?? "unknown",
        });
      }

      const userId = getAuthUser(request)?.id ?? null;
      const jobId = randomUUID();
      let fileBuffer: Buffer | null = null;
      let filename = "image";
      let settingsRaw: string | null = null;
      let clientJobId: string | null = null;
      let fileId: string | null = null;
      let inputKey: string | null = null;

      try {
        const parts = request.parts();
        for await (const part of parts) {
          if (part.type === "file") {
            const upload = await receiveUpload(part, jobId);
            inputKey = upload.key;
            filename = upload.filename;
          } else if (part.fieldname === "settings") {
            settingsRaw = part.value as string;
          } else if (part.fieldname === "clientJobId") {
            const raw = part.value as string;
            if (/^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$/i.test(raw)) {
              clientJobId = raw;
            }
          } else if (part.fieldname === "fileId") {
            fileId = part.value as string;
          }
        }
      } catch (err) {
        return reply.status(400).send({
          error: "Failed to parse multipart request",
          details: stripInternalPaths(err instanceof Error ? err.message : String(err)),
        });
      }

      if (!inputKey) {
        return reply.status(400).send({ error: "No image file provided" });
      }

      fileBuffer = await getObjectBuffer(inputKey);

      const validation = await validateImageBuffer(fileBuffer, filename);
      if (!validation.valid) {
        return reply.status(400).send({ error: `Invalid image: ${validation.reason}` });
      }

      // Validate settings
      let settings: Settings;
      try {
        const raw = settingsRaw ? JSON.parse(settingsRaw) : {};
        const result = settingsSchema.safeParse(raw);
        if (!result.success) {
          return reply
            .status(400)
            .send({ error: "Invalid settings", details: formatZodErrors(result.error.issues) });
        }
        settings = result.data;
      } catch {
        return reply.status(400).send({ error: "Settings must be valid JSON" });
      }

      // At least one extend direction must be > 0
      if (
        settings.extendTop === 0 &&
        settings.extendRight === 0 &&
        settings.extendBottom === 0 &&
        settings.extendLeft === 0
      ) {
        return reply.status(400).send({
          error: "At least one extend direction must be greater than 0",
        });
      }

      try {
        if (validation.format === "heif") {
          fileBuffer = await decodeHeic(fileBuffer);
        }
        if (needsCliDecode(validation.format)) {
          fileBuffer = await decodeToSharpCompat(fileBuffer, validation.format);
        }
        fileBuffer = await autoOrient(fileBuffer);
      } catch (err) {
        request.log.error({ err, toolId: "ai-canvas-expand" }, "Input decoding failed");
        return reply.status(422).send({
          error: "AI canvas expand failed",
          details: stripInternalPaths(err instanceof Error ? err.message : "Unknown error"),
        });
      }

      const decodedKey = `uploads/${jobId}/${filename}`;
      if (decodedKey !== inputKey) {
        await putObject(decodedKey, fileBuffer);
        inputKey = decodedKey;
      } else {
        await putObject(inputKey, fileBuffer);
      }

      const progressJobId = clientJobId || jobId;

      await enqueueToolJob({
        jobId,
        toolId,
        userId,
        pool: "ai",
        inputRefs: [inputKey],
        filename,
        settings,
        clientJobId: clientJobId ?? undefined,
        fileId: fileId ?? undefined,
        kind: "ai-tool",
      });

      return reply.status(202).send({ jobId: progressJobId, async: true });
    },
  );

  // Register in the pipeline/batch registry
  registerToolProcessFn({
    toolId: "ai-canvas-expand",
    settingsSchema,
    process: async (inputBuffer, settings, filename, ctx) => {
      const s = settings as Settings;

      const ext = filename.split(".").pop()?.toLowerCase() ?? "";
      let buf = inputBuffer;
      if (["heic", "heif", "hif"].includes(ext)) {
        buf = await decodeHeic(buf);
      }
      const cliCheck = await validateImageBuffer(inputBuffer, filename);
      if (cliCheck.valid && needsCliDecode(cliCheck.format)) {
        buf = await decodeToSharpCompat(inputBuffer, cliCheck.format);
      }

      const orientedBuffer = await autoOrient(buf);
      const scratchDir = ctx?.scratchDir ?? join(tmpdir(), "snapotter-scratch", randomUUID());
      const needsCleanup = !ctx?.scratchDir;
      if (needsCleanup) await mkdir(scratchDir, { recursive: true });
      try {
        const resultBuffer = await outpaint(
          orientedBuffer,
          {
            extendTop: s.extendTop,
            extendRight: s.extendRight,
            extendBottom: s.extendBottom,
            extendLeft: s.extendLeft,
            tier: s.tier,
          },
          scratchDir,
        );

        const outputFilename = `${filename.replace(/\.[^.]+$/, "")}_extended.png`;
        return { buffer: resultBuffer, filename: outputFilename, contentType: "image/png" };
      } finally {
        if (needsCleanup) await rm(scratchDir, { recursive: true, force: true }).catch(() => {});
      }
    },
  });
}
