2026-06-13 10:19:23 +08:00
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import { randomUUID } from "node:crypto";
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import { mkdir, writeFile } from "node:fs/promises";
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import { join } from "node:path";
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import { extractPdfText } from "@snapotter/ai";
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import { getBundleForTool, TOOL_BUNDLE_MAP } from "@snapotter/shared";
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import type { FastifyInstance, FastifyReply, FastifyRequest } from "fastify";
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import { z } from "zod";
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import { registerAiJobHandler } from "../../jobs/ai-handlers.js";
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import { enqueueToolJob } from "../../jobs/enqueue.js";
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import { formatZodErrors, stripInternalPaths } from "../../lib/errors.js";
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import { isToolInstalled } from "../../lib/feature-status.js";
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import { receiveUpload } from "../../lib/upload-stream.js";
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2026-06-16 15:48:07 +08:00
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import { getAuthUser } from "../../plugins/auth.js";
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2026-06-13 10:19:23 +08:00
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const settingsSchema = z.object({
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quality: z.enum(["fast", "balanced", "best"]).default("balanced"),
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language: z.enum(["auto", "en", "de", "fr", "es", "zh", "ja", "ko"]).default("auto"),
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pages: z.string().max(100).default("all"),
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});
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// -- AI job handler (runs inside the BullMQ worker) --
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registerAiJobHandler("ocr-pdf", async (input, data, ctx) => {
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const settings = settingsSchema.parse(data.settings);
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ctx.report(5, "Preparing PDF");
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// Write the input buffer to a temp file (extractPdfText needs a file path)
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const pdfDir = join(ctx.scratchDir, "pdf");
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await mkdir(pdfDir, { recursive: true });
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const pdfPath = join(pdfDir, data.filename);
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await writeFile(pdfPath, input);
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ctx.report(10, "Extracting text from PDF");
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const result = await extractPdfText(
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pdfPath,
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{
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quality: settings.quality,
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language: settings.language,
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pages: settings.pages,
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},
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(percent, stage) => ctx.report(percent, stage),
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);
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const base = data.filename.replace(/\.[^.]+$/, "");
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const outName = `${base}_ocr.txt`;
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return {
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buffer: Buffer.from(result.text, "utf-8"),
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filename: outName,
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contentType: "text/plain",
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resultPayload: {
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pages: result.pages,
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engine: result.engine,
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},
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};
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});
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export function registerOcrPdf(app: FastifyInstance) {
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2026-06-20 11:47:59 +08:00
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app.post("/api/v1/tools/pdf/ocr-pdf", async (request: FastifyRequest, reply: FastifyReply) => {
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2026-06-13 10:19:23 +08:00
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const toolId = "ocr-pdf";
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if (!isToolInstalled(toolId)) {
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const bundle = getBundleForTool(toolId);
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return reply.status(501).send({
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error: "Feature not installed",
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code: "FEATURE_NOT_INSTALLED",
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feature: TOOL_BUNDLE_MAP[toolId],
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featureName: bundle?.name ?? toolId,
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estimatedSize: bundle?.estimatedSize ?? "unknown",
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});
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}
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2026-06-16 15:48:07 +08:00
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const userId = getAuthUser(request)?.id ?? null;
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2026-06-13 10:19:23 +08:00
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const jobId = randomUUID();
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let filename = "document.pdf";
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let settingsRaw: string | null = null;
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let clientJobId: string | null = null;
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2026-06-16 15:48:07 +08:00
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let fileId: string | null = null;
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2026-06-13 10:19:23 +08:00
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let inputKey: string | null = null;
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try {
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const parts = request.parts();
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for await (const part of parts) {
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if (part.type === "file") {
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const upload = await receiveUpload(part, jobId);
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inputKey = upload.key;
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filename = upload.filename;
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} else if (part.fieldname === "settings") {
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settingsRaw = part.value as string;
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} else if (part.fieldname === "clientJobId") {
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const raw = part.value as string;
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if (/^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$/i.test(raw)) {
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clientJobId = raw;
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}
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2026-06-16 15:48:07 +08:00
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} else if (part.fieldname === "fileId") {
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fileId = part.value as string;
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2026-06-13 10:19:23 +08:00
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}
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}
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} catch (err) {
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return reply.status(400).send({
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error: "Failed to parse multipart request",
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details: stripInternalPaths(err instanceof Error ? err.message : String(err)),
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});
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}
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if (!inputKey) {
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return reply.status(400).send({ error: "No PDF file provided" });
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}
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let settings: z.infer<typeof settingsSchema>;
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try {
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const parsed = settingsRaw ? JSON.parse(settingsRaw) : {};
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const result = settingsSchema.safeParse(parsed);
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if (!result.success) {
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return reply.status(400).send({
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error: "Invalid settings",
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details: formatZodErrors(result.error.issues),
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});
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}
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settings = result.data;
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} catch {
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return reply.status(400).send({ error: "Settings must be valid JSON" });
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}
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const progressJobId = clientJobId || jobId;
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await enqueueToolJob({
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jobId,
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toolId,
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2026-06-16 15:48:07 +08:00
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userId,
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2026-06-13 10:19:23 +08:00
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pool: "ai",
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inputRefs: [inputKey],
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filename,
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settings,
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clientJobId: clientJobId ?? undefined,
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2026-06-16 15:48:07 +08:00
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fileId: fileId ?? undefined,
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2026-06-13 10:19:23 +08:00
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kind: "ai-tool",
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});
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return reply.status(202).send({ jobId: progressJobId, async: true });
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});
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}
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