ai-chatbot/lib/ai/providers/stepfun-image.ts

454 lines
14 KiB
TypeScript

import "server-only";
import sharp from "sharp";
import { constrainImageDimensions } from "@/lib/ai/image-size-constraints";
import { createDeferredUploadedImage } from "@/lib/storage/image-archive";
import { uploadFile } from "@/lib/storage/service";
interface StepfunImageConfig {
apiKey: string;
baseURL: string;
}
export interface StepfunImageParams {
aspectRatio?: string;
imageSize?: string;
imageCount?: number;
size?: string;
seed?: number;
negativePrompt?: string;
}
interface UploadedImage {
thumbnail: string;
original: string;
}
const DEFAULT_BASE_URL = "https://api.stepfun.com";
const DEFAULT_TIMEOUT_MS = 600000;
const DEFAULT_CFG_SCALE = 1.0;
const DEFAULT_STEPS = 8;
const DEFAULT_TEXT_MODE = true;
const MAX_PROMPT_LENGTH = 512;
function normalizeBaseURL(baseURL: string) {
const normalized = String(baseURL || "").trim().replace(/\/+$/, "");
const base = normalized || DEFAULT_BASE_URL;
if (/\/v1$/i.test(base)) return base;
return `${base}/v1`;
}
function joinEndpoint(baseURL: string, path: string) {
const normalizedPath = path.startsWith("/") ? path : `/${path}`;
return `${normalizeBaseURL(baseURL)}${normalizedPath}`;
}
function normalizePrompt(prompt: string) {
const normalized = String(prompt || "").trim();
if (normalized.length <= MAX_PROMPT_LENGTH) return normalized;
console.warn("[StepFun Image] Prompt exceeds 512 characters, truncating for step-image-edit-2");
return normalized.slice(0, MAX_PROMPT_LENGTH);
}
function parseAspectRatioValue(ratio?: string | null) {
const normalized = String(ratio || "").trim();
const [width, height] = normalized.split(":").map((item) => Number(item));
if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
return 1;
}
return width / height;
}
function resolveStepfunSize(aspectRatio?: string, explicitSize?: string) {
const normalizedExplicit = String(explicitSize || "").trim();
if (/^\d{3,4}x\d{3,4}$/i.test(normalizedExplicit)) {
const [rawWidth, rawHeight] = normalizedExplicit.split("x").map((item) => Number(item));
const { width, height } = constrainImageDimensions(
{ width: rawWidth, height: rawHeight },
{
maxEdge: 1360,
maxPixels: 1360 * 1360,
minEdge: 256,
multiple: 8,
}
);
return `${width}x${height}`;
}
const ratio = parseAspectRatioValue(aspectRatio);
const candidates = [
{ size: "1024x1024", ratio: 1 },
{ size: "768x1360", ratio: 1360 / 768 },
{ size: "896x1184", ratio: 1184 / 896 },
{ size: "1360x768", ratio: 768 / 1360 },
{ size: "1184x896", ratio: 896 / 1184 },
];
let best = candidates[0];
let minDiff = Number.POSITIVE_INFINITY;
for (const candidate of candidates) {
const diff = Math.abs(candidate.ratio - ratio);
if (diff < minDiff) {
best = candidate;
minDiff = diff;
}
}
return best.size;
}
function detectImageExtension(imageUrl: string, contentType?: string | null) {
const type = String(contentType || "").toLowerCase();
if (type.includes("jpeg") || type.includes("jpg")) return "jpg";
if (type.includes("webp")) return "webp";
if (type.includes("png")) return "png";
const cleanUrl = imageUrl.split("?")[0]?.toLowerCase() || "";
if (cleanUrl.endsWith(".jpg") || cleanUrl.endsWith(".jpeg")) return "jpg";
if (cleanUrl.endsWith(".webp")) return "webp";
if (cleanUrl.endsWith(".png")) return "png";
return "png";
}
async function createThumbnail(buffer: Buffer) {
try {
return await sharp(buffer)
.resize(400, 400, { fit: "inside", withoutEnlargement: true })
.jpeg({ quality: 80 })
.toBuffer();
} catch (error) {
console.error("[StepFun Image] Failed to create thumbnail:", error);
return buffer;
}
}
function generateFilename(prefix: string, extension: string) {
const timestamp = Date.now();
const random = Math.random().toString(36).slice(2, 8);
return `${prefix}-${timestamp}-${random}.${extension}`;
}
async function uploadGeneratedBuffer(
buffer: Buffer,
extension: string,
mimeType: string
): Promise<UploadedImage> {
const thumbnailBuffer = await createThumbnail(buffer);
const originalFilename = generateFilename("stepfun-image-orig", extension);
const originalArrayBuffer = buffer.buffer.slice(
buffer.byteOffset,
buffer.byteOffset + buffer.byteLength
) as ArrayBuffer;
const originalUploaded = await uploadFile(originalFilename, originalArrayBuffer);
const thumbFilename = generateFilename("stepfun-image-thumb", "jpg");
const thumbArrayBuffer = thumbnailBuffer.buffer.slice(
thumbnailBuffer.byteOffset,
thumbnailBuffer.byteOffset + thumbnailBuffer.byteLength
) as ArrayBuffer;
const thumbUploaded = await uploadFile(thumbFilename, thumbArrayBuffer);
console.log("[StepFun Image] Uploaded generated image:", {
original: originalUploaded.url,
thumbnail: thumbUploaded.url,
mimeType,
});
return {
thumbnail: thumbUploaded.url,
original: originalUploaded.url,
};
}
async function downloadAndUploadImage(imageUrl: string): Promise<UploadedImage> {
const deferred = await createDeferredUploadedImage(imageUrl, {
providerType: "stepfun-image",
});
if (deferred) return deferred;
const response = await fetch(imageUrl, { cache: "no-store" });
if (!response.ok) {
throw new Error(`Failed to download StepFun generated image: ${response.status}`);
}
const buffer = Buffer.from(await response.arrayBuffer());
const extension = detectImageExtension(imageUrl, response.headers.get("content-type"));
const mimeType = response.headers.get("content-type") || `image/${extension === "jpg" ? "jpeg" : extension}`;
return uploadGeneratedBuffer(buffer, extension, mimeType);
}
async function uploadBase64ToS3(base64Data: string, mimeType: string) {
const buffer = Buffer.from(base64Data, "base64");
const extension = detectImageExtension("", mimeType);
return uploadGeneratedBuffer(
buffer,
extension,
mimeType || `image/${extension === "jpg" ? "jpeg" : extension}`
);
}
function extractPromptAndImages(messages: Array<{ role: string; content: any }>) {
const lastUserMessage = messages.filter((message) => message.role === "user").pop();
if (!lastUserMessage) {
throw new Error("No user message found");
}
let prompt = "";
const imageUrls: string[] = [];
const pushImageUrl = (value?: string) => {
if (!value) return;
const normalized = String(value).trim();
if (!normalized || imageUrls.includes(normalized)) return;
imageUrls.push(normalized);
};
if (typeof lastUserMessage.content === "string") {
prompt = lastUserMessage.content.trim();
} else if (Array.isArray(lastUserMessage.content)) {
for (const part of lastUserMessage.content) {
if (part?.type === "text" && typeof part.text === "string") {
prompt = `${prompt} ${part.text}`.trim();
} else if (part?.type === "image_url" && part.image_url?.url) {
pushImageUrl(part.image_url.url);
} else if (part?.type === "file") {
pushImageUrl(part.url || part.data);
} else if (part?.type === "image") {
pushImageUrl(part.image || part.url);
}
}
}
if (!prompt) {
throw new Error("No prompt found in user message");
}
return { prompt: normalizePrompt(prompt), imageUrls };
}
async function loadInputImage(source: string) {
const normalized = String(source || "").trim();
if (!normalized) {
throw new Error("输入图片地址为空");
}
if (normalized.startsWith("data:")) {
const match = normalized.match(/^data:([A-Za-z0-9.+/-]+);base64,(.+)$/);
if (!match) {
throw new Error("不支持的 Base64 图片格式");
}
const mimeType = match[1] || "image/png";
const buffer = Buffer.from(match[2], "base64");
const extension = detectImageExtension("", mimeType);
return {
buffer,
mimeType,
filename: generateFilename("stepfun-image-edit-input", extension),
};
}
const response = await fetch(normalized, { cache: "no-store" });
if (!response.ok) {
throw new Error(`Failed to fetch StepFun input image: ${response.status}`);
}
const buffer = Buffer.from(await response.arrayBuffer());
const mimeType = response.headers.get("content-type") || "image/png";
const extension = detectImageExtension(normalized, mimeType);
return {
buffer,
mimeType,
filename: generateFilename("stepfun-image-edit-input", extension),
};
}
function normalizeSeed(seed?: number) {
if (typeof seed !== "number" || !Number.isFinite(seed)) return undefined;
return Math.max(0, Math.floor(seed));
}
function extractErrorMessage(payload: any) {
if (!payload) return "StepFun Images 请求失败";
if (typeof payload === "string") return payload;
if (payload.error?.message) return String(payload.error.message);
if (payload.message) return String(payload.message);
try {
return JSON.stringify(payload);
} catch {
return "StepFun Images 请求失败";
}
}
async function parseJsonResponse(response: Response) {
const rawText = await response.text();
try {
return JSON.parse(rawText);
} catch {
return rawText;
}
}
async function requestStepfunImage(params: {
baseURL: string;
apiKey: string;
model: string;
prompt: string;
size?: string;
imageUrls: string[];
seed?: number;
}) {
const { baseURL, apiKey, model, prompt, size, imageUrls, seed } = params;
const controller = new AbortController();
const timeoutId = setTimeout(() => controller.abort(), DEFAULT_TIMEOUT_MS);
try {
if (imageUrls.length > 0) {
const endpoint = joinEndpoint(baseURL, "/images/edits");
const formData = new FormData();
formData.append("model", model);
formData.append("prompt", prompt);
formData.append("response_format", "b64_json");
formData.append("cfg_scale", String(DEFAULT_CFG_SCALE));
formData.append("steps", String(DEFAULT_STEPS));
formData.append("text_mode", String(DEFAULT_TEXT_MODE));
const normalizedSeed = normalizeSeed(seed);
if (normalizedSeed !== undefined) formData.append("seed", String(normalizedSeed));
for (const source of imageUrls.slice(0, 1)) {
const image = await loadInputImage(source);
formData.append("image", new Blob([image.buffer], { type: image.mimeType }), image.filename);
}
const response = await fetch(endpoint, {
method: "POST",
headers: {
Authorization: `Bearer ${apiKey}`,
},
body: formData,
signal: controller.signal,
});
const payload = await parseJsonResponse(response);
if (!response.ok) {
throw new Error(`${extractErrorMessage(payload)} (HTTP ${response.status})`);
}
return payload;
}
const endpoint = joinEndpoint(baseURL, "/images/generations");
const body: Record<string, unknown> = {
model,
prompt,
response_format: "b64_json",
cfg_scale: DEFAULT_CFG_SCALE,
steps: DEFAULT_STEPS,
text_mode: DEFAULT_TEXT_MODE,
...(size ? { size } : {}),
};
const normalizedSeed = normalizeSeed(seed);
if (normalizedSeed !== undefined) body.seed = normalizedSeed;
const response = await fetch(endpoint, {
method: "POST",
headers: {
Authorization: `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify(body),
signal: controller.signal,
});
const payload = await parseJsonResponse(response);
if (!response.ok) {
throw new Error(`${extractErrorMessage(payload)} (HTTP ${response.status})`);
}
return payload;
} finally {
clearTimeout(timeoutId);
}
}
async function extractUploadedImages(payload: any): Promise<UploadedImage[]> {
const data = Array.isArray(payload?.data) ? payload.data : [];
const uploadedImages: UploadedImage[] = [];
for (const item of data) {
if (item?.url && typeof item.url === "string") {
uploadedImages.push(await downloadAndUploadImage(item.url));
continue;
}
if (item?.b64_json && typeof item.b64_json === "string") {
uploadedImages.push(await uploadBase64ToS3(item.b64_json, "image/png"));
}
}
return uploadedImages;
}
function formatMarkdown(images: UploadedImage[], imageSize: string) {
return images
.map((image) => `![thumb|||${image.original}|||${imageSize}](${image.thumbnail})`)
.join("\n\n");
}
export function createStepfunImage({ apiKey, baseURL }: StepfunImageConfig) {
return {
provider: "stepfun-image",
chat: (modelId: string) => ({
provider: "stepfun-image",
doGenerate: async (options: {
messages: Array<{ role: string; content: any }>;
imageParams?: StepfunImageParams;
overrideModelId?: string;
}) => {
const { prompt, imageUrls } = extractPromptAndImages(options.messages);
const activeModelId = options.overrideModelId || modelId;
const size =
imageUrls.length > 0
? undefined
: resolveStepfunSize(options.imageParams?.aspectRatio, options.imageParams?.size);
console.log("[StepFun Image] Submitting request", {
model: activeModelId,
size,
imageCount: imageUrls.length,
baseURL: normalizeBaseURL(baseURL),
});
const payload = await requestStepfunImage({
baseURL,
apiKey,
model: activeModelId,
prompt,
size,
imageUrls,
seed: options.imageParams?.seed,
});
const uploadedImages = await extractUploadedImages(payload);
if (uploadedImages.length === 0) {
throw new Error("StepFun Images 未返回可用图片");
}
const text = formatMarkdown(uploadedImages, options.imageParams?.imageSize || "1K");
return {
text,
finishReason: "stop" as const,
usage: {
promptTokens: 0,
completionTokens: text.length,
},
};
},
doStream: async function* (options: {
messages: Array<{ role: string; content: any }>;
imageParams?: StepfunImageParams;
overrideModelId?: string;
}) {
const result = await this.doGenerate(options);
yield {
type: "text-delta",
textDelta: result.text,
};
},
}),
};
}