feat: add Phase 4 AI tools with Python bridge and 6 new tools

Add Python bridge (packages/ai/src/bridge.ts) that calls Python scripts
via child_process with venv-first fallback to system python3. Implements
6 AI-powered tools:

- Remove Background: rembg-based with U2-Net/IS-Net models
- Image Upscaling: Real-ESRGAN with Lanczos fallback
- OCR/Text Extraction: Tesseract + PaddleOCR engines
- Face/PII Blur: MediaPipe face detection with configurable blur
- Object Eraser: LaMa inpainting with mask-based input
- Smart Crop: Sharp attention-based entropy cropping (no Python needed)

Each tool includes: Python script, TypeScript wrapper, API route,
and React settings component. All Python scripts handle ImportError
gracefully with clear installation messages.

apps/api/src/routes/tools/upscale.ts

@@ -0,0 +1,86 @@
+import type { FastifyInstance, FastifyRequest, FastifyReply } from "fastify";
+import { randomUUID } from "node:crypto";
+import { writeFile } from "node:fs/promises";
+import { join, basename } from "node:path";
+import { upscale } from "@stirling-image/ai";
+import { createWorkspace } from "../../lib/workspace.js";
+
+/**
+ * AI image upscaling route.
+ * Uses Real-ESRGAN when available, falls back to Lanczos.
+ */
+export function registerUpscale(app: FastifyInstance) {
+  app.post(
+    "/api/v1/tools/upscale",
+    async (request: FastifyRequest, reply: FastifyReply) => {
+      let fileBuffer: Buffer | null = null;
+      let filename = "image";
+      let settingsRaw: string | null = null;
+
+      try {
+        const parts = request.parts();
+        for await (const part of parts) {
+          if (part.type === "file") {
+            const chunks: Buffer[] = [];
+            for await (const chunk of part.file) {
+              chunks.push(chunk);
+            }
+            fileBuffer = Buffer.concat(chunks);
+            filename = basename(part.filename ?? "image");
+          } else if (part.fieldname === "settings") {
+            settingsRaw = part.value as string;
+          }
+        }
+      } catch (err) {
+        return reply.status(400).send({
+          error: "Failed to parse multipart request",
+          details: err instanceof Error ? err.message : String(err),
+        });
+      }
+
+      if (!fileBuffer || fileBuffer.length === 0) {
+        return reply.status(400).send({ error: "No image file provided" });
+      }
+
+      try {
+        const settings = settingsRaw ? JSON.parse(settingsRaw) : {};
+        const scale = Number(settings.scale) || 2;
+
+        const jobId = randomUUID();
+        const workspacePath = await createWorkspace(jobId);
+
+        // Save input
+        const inputPath = join(workspacePath, "input", filename);
+        await writeFile(inputPath, fileBuffer);
+
+        // Process
+        const result = await upscale(
+          fileBuffer,
+          join(workspacePath, "output"),
+          { scale },
+        );
+
+        // Save output
+        const outputFilename =
+          filename.replace(/\.[^.]+$/, "") + `_${scale}x.png`;
+        const outputPath = join(workspacePath, "output", outputFilename);
+        await writeFile(outputPath, result.buffer);
+
+        return reply.send({
+          jobId,
+          downloadUrl: `/api/v1/download/${jobId}/${encodeURIComponent(outputFilename)}`,
+          originalSize: fileBuffer.length,
+          processedSize: result.buffer.length,
+          width: result.width,
+          height: result.height,
+          method: result.method,
+        });
+      } catch (err) {
+        return reply.status(422).send({
+          error: "Upscaling failed",
+          details: err instanceof Error ? err.message : "Unknown error",
+        });
+      }
+    },
+  );
+}