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/blur-faces.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 { blurFaces } from "@stirling-image/ai";
+import { createWorkspace } from "../../lib/workspace.js";
+
+/**
+ * Face detection and blurring route.
+ * Uses MediaPipe for detection, PIL for blurring.
+ */
+export function registerBlurFaces(app: FastifyInstance) {
+  app.post(
+    "/api/v1/tools/blur-faces",
+    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 jobId = randomUUID();
+        const workspacePath = await createWorkspace(jobId);
+
+        // Save input
+        const inputPath = join(workspacePath, "input", filename);
+        await writeFile(inputPath, fileBuffer);
+
+        // Process
+        const result = await blurFaces(
+          fileBuffer,
+          join(workspacePath, "output"),
+          {
+            blurRadius: settings.blurRadius ?? 30,
+            sensitivity: settings.sensitivity ?? 0.5,
+          },
+        );
+
+        // Save output
+        const outputFilename =
+          filename.replace(/\.[^.]+$/, "") + "_blurred.png";
+        const outputPath = join(workspacePath, "output", outputFilename);
+        await writeFile(outputPath, result.buffer);
+
+        return reply.send({
+          jobId,
+          downloadUrl: `/api/v1/download/${jobId}/${encodeURIComponent(outputFilename)}`,
+          originalSize: fileBuffer.length,
+          processedSize: result.buffer.length,
+          facesDetected: result.facesDetected,
+          faces: result.faces,
+        });
+      } catch (err) {
+        return reply.status(422).send({
+          error: "Face blur failed",
+          details: err instanceof Error ? err.message : "Unknown error",
+        });
+      }
+    },
+  );
+}

apps/api/src/routes/tools/erase-object.ts

@@ -0,0 +1,88 @@
+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 { inpaint } from "@stirling-image/ai";
+import { createWorkspace } from "../../lib/workspace.js";
+
+/**
+ * Object eraser / inpainting route.
+ * Accepts an image and a mask image, erases masked areas.
+ */
+export function registerEraseObject(app: FastifyInstance) {
+  app.post(
+    "/api/v1/tools/erase-object",
+    async (request: FastifyRequest, reply: FastifyReply) => {
+      let imageBuffer: Buffer | null = null;
+      let maskBuffer: Buffer | null = null;
+      let filename = "image";
+
+      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);
+            }
+            const buf = Buffer.concat(chunks);
+            if (part.fieldname === "mask") {
+              maskBuffer = buf;
+            } else {
+              imageBuffer = buf;
+              filename = basename(part.filename ?? "image");
+            }
+          }
+        }
+      } catch (err) {
+        return reply.status(400).send({
+          error: "Failed to parse multipart request",
+          details: err instanceof Error ? err.message : String(err),
+        });
+      }
+
+      if (!imageBuffer || imageBuffer.length === 0) {
+        return reply.status(400).send({ error: "No image file provided" });
+      }
+      if (!maskBuffer || maskBuffer.length === 0) {
+        return reply
+          .status(400)
+          .send({ error: "No mask image provided. Upload a mask as a second file with fieldname 'mask'" });
+      }
+
+      try {
+        const jobId = randomUUID();
+        const workspacePath = await createWorkspace(jobId);
+
+        // Save input
+        const inputPath = join(workspacePath, "input", filename);
+        await writeFile(inputPath, imageBuffer);
+
+        // Process
+        const resultBuffer = await inpaint(
+          imageBuffer,
+          maskBuffer,
+          join(workspacePath, "output"),
+        );
+
+        // Save output
+        const outputFilename =
+          filename.replace(/\.[^.]+$/, "") + "_erased.png";
+        const outputPath = join(workspacePath, "output", outputFilename);
+        await writeFile(outputPath, resultBuffer);
+
+        return reply.send({
+          jobId,
+          downloadUrl: `/api/v1/download/${jobId}/${encodeURIComponent(outputFilename)}`,
+          originalSize: imageBuffer.length,
+          processedSize: resultBuffer.length,
+        });
+      } catch (err) {
+        return reply.status(422).send({
+          error: "Object erasing failed",
+          details: err instanceof Error ? err.message : "Unknown error",
+        });
+      }
+    },
+  );
+}

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

@@ -32,6 +32,13 @@ import { registerFavicon } from "./favicon.js";
 import { registerImageToPdf } from "./image-to-pdf.js";
 // Phase 3: Adjustments extra
 import { registerReplaceColor } from "./replace-color.js";
+// Phase 4: AI Tools
+import { registerRemoveBackground } from "./remove-background.js";
+import { registerUpscale } from "./upscale.js";
+import { registerOcr } from "./ocr.js";
+import { registerBlurFaces } from "./blur-faces.js";
+import { registerEraseObject } from "./erase-object.js";
+import { registerSmartCrop } from "./smart-crop.js";
 
 /**
  * Registry that imports and registers all tool routes.
@@ -79,5 +86,13 @@ export async function registerToolRoutes(app: FastifyInstance): Promise<void> {
   // Phase 3: Adjustments extra
   registerReplaceColor(app);
 
-  app.log.info("Tool routes registered (26 tools, 29 endpoints)");
+  // Phase 4: AI Tools
+  registerRemoveBackground(app);
+  registerUpscale(app);
+  registerOcr(app);
+  registerBlurFaces(app);
+  registerEraseObject(app);
+  registerSmartCrop(app);
+
+  app.log.info("Tool routes registered (32 tools, 35 endpoints)");
 }

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

@@ -0,0 +1,68 @@
+import type { FastifyInstance, FastifyRequest, FastifyReply } from "fastify";
+import { randomUUID } from "node:crypto";
+import { basename } from "node:path";
+import { extractText } from "@stirling-image/ai";
+import { createWorkspace } from "../../lib/workspace.js";
+
+/**
+ * OCR / text extraction route.
+ * Returns JSON with extracted text rather than an image.
+ */
+export function registerOcr(app: FastifyInstance) {
+  app.post(
+    "/api/v1/tools/ocr",
+    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 jobId = randomUUID();
+        const workspacePath = await createWorkspace(jobId);
+
+        const result = await extractText(fileBuffer, workspacePath, {
+          engine: settings.engine,
+          language: settings.language,
+        });
+
+        return reply.send({
+          jobId,
+          filename,
+          text: result.text,
+          engine: result.engine,
+        });
+      } catch (err) {
+        return reply.status(422).send({
+          error: "OCR failed",
+          details: err instanceof Error ? err.message : "Unknown error",
+        });
+      }
+    },
+  );
+}

apps/api/src/routes/tools/remove-background.ts

@@ -0,0 +1,80 @@
+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 { removeBackground } from "@stirling-image/ai";
+import { createWorkspace } from "../../lib/workspace.js";
+
+/**
+ * AI background removal route.
+ * Uses Python + rembg under the hood.
+ */
+export function registerRemoveBackground(app: FastifyInstance) {
+  app.post(
+    "/api/v1/tools/remove-background",
+    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 jobId = randomUUID();
+        const workspacePath = await createWorkspace(jobId);
+
+        // Save input
+        const inputPath = join(workspacePath, "input", filename);
+        await writeFile(inputPath, fileBuffer);
+
+        // Process
+        const resultBuffer = await removeBackground(
+          fileBuffer,
+          join(workspacePath, "output"),
+          { model: settings.model },
+        );
+
+        // Save output
+        const outputFilename = filename.replace(/\.[^.]+$/, "") + "_nobg.png";
+        const outputPath = join(workspacePath, "output", outputFilename);
+        await writeFile(outputPath, resultBuffer);
+
+        return reply.send({
+          jobId,
+          downloadUrl: `/api/v1/download/${jobId}/${encodeURIComponent(outputFilename)}`,
+          originalSize: fileBuffer.length,
+          processedSize: resultBuffer.length,
+        });
+      } catch (err) {
+        return reply.status(422).send({
+          error: "Background removal failed",
+          details: err instanceof Error ? err.message : "Unknown error",
+        });
+      }
+    },
+  );
+}

apps/api/src/routes/tools/smart-crop.ts

@@ -0,0 +1,33 @@
+import { z } from "zod";
+import sharp from "sharp";
+import type { FastifyInstance } from "fastify";
+import { createToolRoute } from "../tool-factory.js";
+
+const settingsSchema = z.object({
+  width: z.number().int().positive(),
+  height: z.number().int().positive(),
+});
+
+/**
+ * Smart crop using Sharp's attention-based strategy.
+ * Uses entropy/saliency detection to find the most interesting region.
+ * No Python needed.
+ */
+export function registerSmartCrop(app: FastifyInstance) {
+  createToolRoute(app, {
+    toolId: "smart-crop",
+    settingsSchema,
+    process: async (inputBuffer, settings, filename) => {
+      const result = await sharp(inputBuffer)
+        .resize(settings.width, settings.height, {
+          fit: "cover",
+          position: sharp.strategy.attention,
+        })
+        .png()
+        .toBuffer();
+
+      const outputFilename = filename.replace(/\.[^.]+$/, "") + "_smartcrop.png";
+      return { buffer: result, filename: outputFilename, contentType: "image/png" };
+    },
+  });
+}

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",
+        });
+      }
+    },
+  );
+}