361 lines
11 KiB
TypeScript
361 lines
11 KiB
TypeScript
import "server-only";
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import sharp from "sharp";
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import { uploadFile } from "@/lib/storage/service";
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interface FalImageConfig {
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apiKey: string;
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baseURL: string;
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}
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interface FalImageParams {
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aspectRatio?: string;
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imageSize?: string;
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imageCount?: number;
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outputFormat?: "png" | "jpg" | "jpeg" | "webp";
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safetyTolerance?: string | number;
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enableWebSearch?: boolean;
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}
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interface UploadedImage {
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thumbnail: string;
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original: string;
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}
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const DEFAULT_ASPECT_RATIO = "auto";
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const DEFAULT_RESOLUTION = "1K";
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const DEFAULT_OUTPUT_FORMAT = "png";
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const DEFAULT_SAFETY_TOLERANCE = "4";
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const DEFAULT_TIMEOUT_MS = 180000;
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function normalizeFalCredentials(apiKey: string) {
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return apiKey.trim().replace(/^bearer\s+/i, "").replace(/^key\s+/i, "");
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}
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function normalizeUrlForCompare(url: string) {
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try {
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const parsed = new URL(url);
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parsed.search = "";
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parsed.hash = "";
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return parsed.toString();
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} catch {
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return url.split("?")[0]?.split("#")[0] || url;
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}
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}
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function filterSourceImages(urls: string[], sourceUrls: string[]) {
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if (sourceUrls.length === 0) return urls;
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const sourceSet = new Set(sourceUrls.map((url) => normalizeUrlForCompare(url)));
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return urls.filter((url) => !sourceSet.has(normalizeUrlForCompare(url)));
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}
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function normalizeAspectRatio(aspectRatio?: string) {
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if (!aspectRatio) return DEFAULT_ASPECT_RATIO;
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const ratio = aspectRatio.trim();
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const normalized = ratio.toLowerCase();
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if (
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[
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"auto",
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"21:9",
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"16:9",
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"3:2",
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"4:3",
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"5:4",
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"1:1",
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"4:5",
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"3:4",
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"2:3",
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"9:16",
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].includes(normalized)
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) {
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return normalized === "auto" ? "auto" : ratio;
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}
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return DEFAULT_ASPECT_RATIO;
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}
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function normalizeResolution(imageSize?: string) {
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if (!imageSize) return DEFAULT_RESOLUTION;
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const normalized = imageSize.trim().toUpperCase();
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if (["1K", "2K", "4K"].includes(normalized)) return normalized;
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return DEFAULT_RESOLUTION;
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}
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function normalizeOutputFormat(outputFormat?: string) {
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if (!outputFormat) return DEFAULT_OUTPUT_FORMAT;
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const normalized = outputFormat.trim().toLowerCase();
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if (normalized === "jpg" || normalized === "jpeg") return "jpeg";
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if (normalized === "webp") return "webp";
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return "png";
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}
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function normalizeSafetyTolerance(value?: string | number) {
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if (value === undefined || value === null) return DEFAULT_SAFETY_TOLERANCE;
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const normalized = String(value).trim();
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if (["1", "2", "3", "4", "5", "6"].includes(normalized)) return normalized;
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return DEFAULT_SAFETY_TOLERANCE;
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}
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function detectImageExtension(imageUrl: string, contentType?: string | null) {
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const type = (contentType || "").toLowerCase();
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if (type.includes("jpeg") || type.includes("jpg")) return "jpg";
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if (type.includes("webp")) return "webp";
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if (type.includes("png")) return "png";
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const cleanUrl = imageUrl.split("?")[0]?.toLowerCase() || "";
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if (cleanUrl.endsWith(".jpg") || cleanUrl.endsWith(".jpeg")) return "jpg";
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if (cleanUrl.endsWith(".webp")) return "webp";
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if (cleanUrl.endsWith(".png")) return "png";
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return "png";
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}
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async function createThumbnail(buffer: Buffer): Promise<Buffer> {
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try {
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return await sharp(buffer)
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.resize(400, 400, { fit: "inside", withoutEnlargement: true })
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.jpeg({ quality: 80 })
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.toBuffer();
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} catch (error) {
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console.error("[Fal Image] Failed to create thumbnail:", error);
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return buffer;
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}
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}
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function generateFilename(prefix: string, extension: string) {
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const ts = Date.now();
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const rand = Math.random().toString(36).slice(2, 8);
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return `${prefix}-${ts}-${rand}.${extension}`;
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}
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async function downloadAndUploadImage(imageUrl: string): Promise<UploadedImage> {
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const response = await fetch(imageUrl);
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if (!response.ok) {
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throw new Error(`Failed to download image: ${response.status}`);
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}
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const arrayBuffer = await response.arrayBuffer();
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const buffer = Buffer.from(arrayBuffer);
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const thumbnailBuffer = await createThumbnail(buffer);
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const originalExt = detectImageExtension(imageUrl, response.headers.get("content-type"));
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const originalFilename = generateFilename("fal-image-orig", originalExt);
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const originalArrayBuffer = buffer.buffer.slice(
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buffer.byteOffset,
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buffer.byteOffset + buffer.byteLength
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) as ArrayBuffer;
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const originalUploaded = await uploadFile(originalFilename, originalArrayBuffer);
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const thumbFilename = generateFilename("fal-image-thumb", "jpg");
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const thumbArrayBuffer = thumbnailBuffer.buffer.slice(
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thumbnailBuffer.byteOffset,
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thumbnailBuffer.byteOffset + thumbnailBuffer.byteLength
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) as ArrayBuffer;
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const thumbUploaded = await uploadFile(thumbFilename, thumbArrayBuffer);
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return {
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thumbnail: thumbUploaded.url,
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original: originalUploaded.url,
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};
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}
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function extractPromptAndImages(messages: Array<{ role: string; content: any }>) {
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const lastUserMessage = messages.filter((message) => message.role === "user").pop();
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if (!lastUserMessage) {
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throw new Error("No user message found");
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}
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let prompt = "";
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const imageUrls: string[] = [];
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const pushImageUrl = (url?: string) => {
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if (!url) return;
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const normalized = String(url).trim();
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if (normalized.startsWith("data:")) {
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throw new Error("FAL 不支持 Base64 图片传输，请先上传图片后再编辑");
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}
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if (!normalized.startsWith("http")) return;
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if (!imageUrls.includes(normalized)) {
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imageUrls.push(normalized);
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}
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};
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if (typeof lastUserMessage.content === "string") {
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prompt = lastUserMessage.content.trim();
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} else if (Array.isArray(lastUserMessage.content)) {
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for (const part of lastUserMessage.content) {
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if (part?.type === "text" && typeof part.text === "string") {
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prompt = `${prompt} ${part.text}`.trim();
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} else if (part?.type === "image_url" && part.image_url?.url) {
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pushImageUrl(part.image_url.url);
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} else if (part?.type === "file") {
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pushImageUrl(part.url || part.data);
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} else if (part?.type === "image") {
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pushImageUrl(part.image || part.url);
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}
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}
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}
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if (!prompt) {
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throw new Error("No prompt found in user message");
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}
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return { prompt, imageUrls };
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}
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function collectImageUrls(payload: any): string[] {
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const urls = new Set<string>();
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const isLikelyImageUrl = (value: string) =>
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/^https?:\/\//i.test(value) &&
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(/\.(png|jpg|jpeg|webp|gif)(\?|$)/i.test(value) ||
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value.includes("image") ||
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value.includes("fal.media"));
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const walk = (value: any, parentKey = "") => {
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if (typeof value === "string") {
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if (isLikelyImageUrl(value)) {
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urls.add(value);
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}
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return;
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}
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if (Array.isArray(value)) {
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for (const item of value) {
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walk(item, parentKey);
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}
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return;
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}
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if (value && typeof value === "object") {
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for (const [key, nestedValue] of Object.entries(value)) {
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if (key === "url" && typeof nestedValue === "string" && /^https?:\/\//i.test(nestedValue)) {
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if (/image|img|file|output|result|artifact/i.test(parentKey) || isLikelyImageUrl(nestedValue)) {
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urls.add(nestedValue);
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}
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}
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walk(nestedValue, key);
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}
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}
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};
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walk(payload);
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return Array.from(urls);
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}
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function formatMarkdown(images: UploadedImage[], resolution: string) {
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return images
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.map((image) => ``)
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.join("\n\n");
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}
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export function createFalImage({ apiKey, baseURL }: FalImageConfig) {
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return {
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provider: "fal-image",
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chat: (modelId: string) => ({
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provider: "fal-image",
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doGenerate: async (options: {
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messages: Array<{ role: string; content: any }>;
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imageParams?: FalImageParams;
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overrideModelId?: string;
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}) => {
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const { prompt, imageUrls } = extractPromptAndImages(options.messages);
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const aspectRatio = normalizeAspectRatio(options.imageParams?.aspectRatio);
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const resolution = normalizeResolution(options.imageParams?.imageSize);
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const outputFormat = normalizeOutputFormat(options.imageParams?.outputFormat);
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const safetyTolerance = normalizeSafetyTolerance(options.imageParams?.safetyTolerance);
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const imageCount = Math.max(1, Math.min(6, Number(options.imageParams?.imageCount || 1)));
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const activeModelId = options.overrideModelId || modelId;
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console.log("[Fal Image] Submitting request", {
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model: activeModelId,
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baseURL,
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imageCount,
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aspectRatio,
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resolution,
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});
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const fal = await import("@fal-ai/serverless-client");
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fal.config({
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credentials: normalizeFalCredentials(apiKey),
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});
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const input: Record<string, any> = {
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prompt,
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num_images: imageCount,
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aspect_ratio: aspectRatio,
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resolution,
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output_format: outputFormat,
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safety_tolerance: safetyTolerance,
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};
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if (imageUrls.length > 0) {
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input.image_urls = imageUrls;
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}
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if (typeof options.imageParams?.enableWebSearch === "boolean") {
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input.enable_web_search = options.imageParams.enableWebSearch;
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}
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const result: any = await fal.subscribe(activeModelId, {
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input,
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logs: true,
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timeout: DEFAULT_TIMEOUT_MS,
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onQueueUpdate: (update: any) => {
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if (update?.status === "IN_PROGRESS" && Array.isArray(update.logs)) {
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for (const log of update.logs) {
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if (log?.message) {
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console.log(`[Fal Image][${activeModelId}]`, log.message);
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}
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}
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}
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},
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});
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let outputUrls = filterSourceImages(collectImageUrls(result), imageUrls);
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if (outputUrls.length === 0 && result?.data) {
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outputUrls = filterSourceImages(collectImageUrls(result.data), imageUrls);
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}
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if (outputUrls.length === 0) {
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throw new Error("FAL 未返回可用图片");
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}
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const uploadedImages: UploadedImage[] = [];
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for (const outputUrl of outputUrls.slice(0, imageCount)) {
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uploadedImages.push(await downloadAndUploadImage(outputUrl));
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}
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if (uploadedImages.length === 0) {
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throw new Error("FAL 未返回可用图片");
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}
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const text = formatMarkdown(uploadedImages, resolution);
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return {
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text,
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finishReason: "stop" as const,
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usage: {
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promptTokens: 0,
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completionTokens: text.length,
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},
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};
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},
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doStream: async function* (options: {
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messages: Array<{ role: string; content: any }>;
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imageParams?: FalImageParams;
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overrideModelId?: string;
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}) {
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const result = await this.doGenerate(options);
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yield {
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type: "text-delta",
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textDelta: result.text,
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};
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},
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}),
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};
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}
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