image editing support

packages/fluent-ai/package.json

@@ -49,4 +49,4 @@
   "prettier": {
     "trailingComma": "all"
   }
-}
+}

packages/fluent-ai/src/builder/image.ts

@@ -40,6 +40,16 @@ export class ImageBuilder<TProvider extends string = string> {
     return this;
   }
 
+  edit(images: string[]) {
+    this.input.edit = images;
+    return this;
+  }
+
+  upload(options: ImageJob["input"]["upload"]) {
+    this.input.upload = options;
+    return this;
+  }
+
   build() {
     return {
       type: "image" as const,

packages/fluent-ai/src/job/fal.ts

@@ -1,5 +1,9 @@
 import type { ImageJob } from "~/src/job/schema";
-import { createHTTPJob, downloadImages } from "~/src/job/http";
+import {
+  createHTTPJob,
+  downloadImages,
+  uploadLocalImages,
+} from "~/src/job/http";
 
 // TODO: switch to fal queue api
 const BASE_URL = "https://fal.run";
@@ -8,17 +12,28 @@ export const runner = {
   image: async (input: ImageJob["input"], options?: ImageJob["options"]) => {
     const apiKey = options?.apiKey || process.env.FAL_API_KEY;
 
+    let editImages = input.edit;
+    if (editImages && input.upload) {
+      editImages = await uploadLocalImages(editImages, input.upload);
+    }
+
+    const body: any = {
+      prompt: input.prompt,
+      image_size: input.size,
+      num_images: input.n,
+    };
+
+    if (editImages && editImages.length > 0) {
+      body.image_urls = editImages;
+    }
+
     const request = new Request(`${BASE_URL}/${input.model}`, {
       method: "POST",
       headers: {
         Authorization: `Key ${apiKey}`,
         "Content-Type": "application/json",
       },
-      body: JSON.stringify({
-        prompt: input.prompt,
-        image_size: input.size,
-        num_images: input.n,
-      }),
+      body: JSON.stringify(body),
     });
 
     return createHTTPJob(request, async (response: Response) => {

packages/fluent-ai/src/job/http.ts

@@ -1,6 +1,54 @@
-import * as fs from "node:fs";
+import * as fs from "node:fs/promises";
 import * as path from "node:path";
-import type { ImageJob } from "./schema";
+import type { ImageJob } from "~/src/job/schema";
+
+const MIME_TYPES: Record<string, string> = {
+  ".png": "image/png",
+  ".jpg": "image/jpeg",
+  ".jpeg": "image/jpeg",
+  ".gif": "image/gif",
+  ".webp": "image/webp",
+};
+
+function isRemoteUrl(url: string) {
+  return url.startsWith("http://") || url.startsWith("https://");
+}
+
+async function convertToBase64(filePath: string) {
+  try {
+    const fileBuffer = await fs.readFile(filePath);
+    const base64Data = fileBuffer.toString("base64");
+
+    const ext = path.extname(filePath).toLowerCase();
+    const mimeType = MIME_TYPES[ext] || "image/png";
+
+    return `data:${mimeType};base64,${base64Data}`;
+  } catch (error) {
+    console.error(`Failed to read local file ${filePath}:`, error);
+    throw new Error(`Failed to upload local image: ${filePath}`);
+  }
+}
+
+export async function uploadLocalImages(
+  images: string[],
+  uploadOption: ImageJob["input"]["upload"],
+) {
+  if (!uploadOption) {
+    return images;
+  }
+
+  return Promise.all(
+    images.map(async (img) => {
+      if (isRemoteUrl(img)) return img;
+
+      if (uploadOption === "base64") {
+        return await convertToBase64(img);
+      }
+
+      return img;
+    }),
+  );
+}
 
 export async function createHTTPJob<T>(
   request: RequestInfo | URL,
@@ -24,8 +72,10 @@ export async function downloadImages(
 ): Promise<Array<{ url: string; downloadPath?: string; [key: string]: any }>> {
   const localDir = options!.local;
 
-  if (!fs.existsSync(localDir)) {
-    fs.mkdirSync(localDir, { recursive: true });
+  try {
+    await fs.access(localDir);
+  } catch {
+    await fs.mkdir(localDir, { recursive: true });
   }
 
   const downloadedImages = await Promise.all(
@@ -47,7 +97,7 @@ export async function downloadImages(
         const filePath = path.join(localDir, filename);
 
         const buffer = await response.arrayBuffer();
-        fs.writeFileSync(filePath, Buffer.from(buffer));
+        await fs.writeFile(filePath, Buffer.from(buffer));
 
         return {
           ...img,

packages/fluent-ai/src/job/schema.ts

@@ -53,6 +53,7 @@ const embeddingOutputSchema = z.object({
 });
 
 const downloadOptionsSchema = z.union([z.object({ local: z.string() })]);
+const uploadOptionsSchema = z.union([z.literal("base64")]);
 
 const imageSizeSchema = z.object({
   width: z.number(),
@@ -69,6 +70,8 @@ const imageInputSchema = z.object({
   outputFormat: z.string().optional(),
   guidanceScale: z.number().optional(),
   download: downloadOptionsSchema.optional(),
+  edit: z.array(z.string()).optional(),
+  upload: uploadOptionsSchema.optional(),
 });
 
 const imageOutputSchema = z.object({

packages/fluent-ai/test/job.test.ts

@@ -7,6 +7,7 @@ import {
   type Job,
   user,
   voyage,
+  type ImageJob,
 } from "~/src/index";
 import { Runner } from "~/src/job/runner";
 
@@ -55,6 +56,42 @@ test("image job", () => {
   );
 });
 
+test("image edit job", () => {
+  const job: ImageJob = {
+    provider: "fal",
+    type: "image",
+    input: {
+      model: "fal-ai/bytedance/seedream/v4/edit",
+      prompt:
+        "Dress the model in the clothes and hat. Add a cat to the scene and change the background to a Victorian era building.",
+      edit: [
+        "./input1.png",
+        "https://storage.googleapis.com/falserverless/example_inputs/seedream4_edit_input_2.png",
+      ],
+      size: {
+        width: 3840,
+        height: 2160,
+      },
+      upload: "base64",
+    },
+  };
+
+  expect(job).toEqual(
+    fal()
+      .image("fal-ai/bytedance/seedream/v4/edit")
+      .prompt(
+        "Dress the model in the clothes and hat. Add a cat to the scene and change the background to a Victorian era building.",
+      )
+      .edit([
+        "./input1.png",
+        "https://storage.googleapis.com/falserverless/example_inputs/seedream4_edit_input_2.png",
+      ])
+      .size({ width: 3840, height: 2160 })
+      .upload("base64")
+      .build(),
+  );
+});
+
 test("embedding job", () => {
   const job: Job = {
     provider: "voyage",