mirror of
https://github.com/basketikun/infinite-canvas.git
synced 2026-07-28 02:34:28 +08:00
hengmaoqing
51ea17e8d9
- 新增 QUALITY_BASE 配置对象定义低中高质量的基础像素值 - 实现 resolveSize 函数将质量等级与宽高比转换为精确像素尺寸 - 在图像生成请求中集成像素尺寸解析逻辑 - 更新图像编辑功能以支持动态像素尺寸设置 - 优化 API 请求参数传递方式使用展开运算符 - 调整页面组件中的质量选项显示标签增加像素信息
249 lines
9.2 KiB
TypeScript
249 lines
9.2 KiB
TypeScript
import axios from "axios";
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import { buildApiUrl, type AiConfig } from "@/stores/use-config-store";
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import { nanoid } from "nanoid";
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import { dataUrlToFile } from "@/lib/image-utils";
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import { imageToDataUrl } from "@/services/image-storage";
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import type { ReferenceImage } from "@/types/image";
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export type ChatCompletionMessage = {
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role: "system" | "user" | "assistant";
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content: string | Array<{ type: "text"; text: string } | { type: "image_url"; image_url: { url: string } }>;
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};
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type ImageApiResponse = {
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data?: Array<Record<string, unknown>>;
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error?: { message?: string };
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code?: number;
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msg?: string;
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};
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const QUALITY_BASE: Record<string, number> = {
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low: 1024,
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medium: 2048,
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high: 2880,
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};
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/** Map "quality + ratio" to an explicit pixel dimension like "3840x2160". Returns undefined when quality is auto. */
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function resolveSize(quality: string, ratio: string): string | undefined {
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const basePixels = QUALITY_BASE[quality];
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if (!basePixels || ratio === "auto" || !ratio) return undefined;
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const parts = ratio.split(":");
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if (parts.length !== 2) return undefined;
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const w = Number(parts[0]);
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const h = Number(parts[1]);
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if (!w || !h) return undefined;
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const targetPixels = basePixels * basePixels;
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const isLandscape = w >= h;
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const longRatio = isLandscape ? w / h : h / w;
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const longSideRaw = Math.sqrt(targetPixels * longRatio);
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const longSide = Math.floor(longSideRaw / 16) * 16;
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const shortSide = Math.round((longSide / longRatio) / 16) * 16;
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const width = isLandscape ? longSide : shortSide;
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const height = isLandscape ? shortSide : longSide;
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return `${width}x${height}`;
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}
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function resolveImageDataUrl(item: Record<string, unknown>) {
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if (typeof item.b64_json === "string" && item.b64_json) {
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return `data:image/png;base64,${item.b64_json}`;
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}
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if (typeof item.url === "string" && item.url) {
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return item.url;
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}
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return null;
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}
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function parseImagePayload(payload: ImageApiResponse) {
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if (typeof payload.code === "number" && payload.code !== 0) {
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throw new Error(payload.msg || "请求失败");
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}
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const images =
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payload.data
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?.map(resolveImageDataUrl)
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.filter((value): value is string => Boolean(value))
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.map((dataUrl) => ({ id: nanoid(), dataUrl })) || [];
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if (images.length === 0) {
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throw new Error("接口没有返回图片");
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}
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return images;
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}
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function readAxiosError(error: unknown, fallback: string) {
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if (axios.isAxiosError<{ error?: { message?: string }; msg?: string; code?: number }>(error)) {
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const responseData = error.response?.data;
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return responseData?.msg || responseData?.error?.message || (error.response?.status ? `${fallback}：${error.response.status}` : fallback);
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}
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return error instanceof Error ? error.message : fallback;
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}
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function parseStreamChunk(chunk: string, onDelta: (value: string) => void) {
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let deltaText = "";
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for (const eventBlock of chunk.split("\n\n")) {
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const data = eventBlock
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.split("\n")
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.find((line) => line.startsWith("data: "))
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?.slice(6);
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if (!data || data === "[DONE]") continue;
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const delta = (JSON.parse(data) as { choices?: Array<{ delta?: { content?: string } }> }).choices?.[0]?.delta?.content || "";
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deltaText += delta;
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}
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if (deltaText) onDelta(deltaText);
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}
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function withSystemPrompt(config: AiConfig, prompt: string) {
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const systemPrompt = config.systemPrompt.trim();
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return systemPrompt ? `${systemPrompt}\n\n${prompt}` : prompt;
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}
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function aiApiUrl(config: AiConfig, path: string) {
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return config.channelMode === "remote" ? `/api/v1${path}` : buildApiUrl(config.baseUrl, path);
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}
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function aiHeaders(config: AiConfig, contentType?: string) {
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return config.channelMode === "remote"
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? contentType
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? { "Content-Type": contentType }
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: undefined
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: {
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Authorization: `Bearer ${config.apiKey}`,
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...(contentType ? { "Content-Type": contentType } : {}),
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};
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}
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function withSystemMessage(config: AiConfig, messages: ChatCompletionMessage[]) {
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const systemPrompt = config.systemPrompt.trim();
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return systemPrompt ? [{ role: "system" as const, content: systemPrompt }, ...messages] : messages;
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}
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export async function requestGeneration(config: AiConfig, prompt: string) {
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const n = Math.max(1, Math.min(15, Math.floor(Math.abs(Number(config.count)) || 1)));
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const pixelSize = resolveSize(config.quality, config.size);
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try {
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const response = await axios.post<ImageApiResponse>(
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aiApiUrl(config, "/images/generations"),
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{
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model: config.model,
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prompt: withSystemPrompt(config, prompt),
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n,
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...(pixelSize ? { quality: config.quality, size: pixelSize } : {}),
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response_format: "b64_json",
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},
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{
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headers: aiHeaders(config, "application/json"),
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},
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);
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return parseImagePayload(response.data);
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} catch (error) {
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throw new Error(readAxiosError(error, "请求失败"));
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}
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}
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export async function requestEdit(config: AiConfig, prompt: string, references: ReferenceImage[]) {
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const n = Math.max(1, Math.min(15, Math.floor(Math.abs(Number(config.count)) || 1)));
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const pixelSize = resolveSize(config.quality, config.size);
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const formData = new FormData();
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formData.set("model", config.model);
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formData.set("prompt", withSystemPrompt(config, prompt));
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formData.set("n", String(n));
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formData.set("response_format", "b64_json");
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if (pixelSize) {
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formData.set("quality", config.quality);
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formData.set("size", pixelSize);
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}
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const files = await Promise.all(references.map(async (image) => dataUrlToFile({ ...image, dataUrl: await imageToDataUrl(image) })));
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files.forEach((file) => formData.append("image", file));
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try {
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const response = await axios.post<ImageApiResponse>(aiApiUrl(config, "/images/edits"), formData, { headers: aiHeaders(config) });
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return parseImagePayload(response.data);
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} catch (error) {
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throw new Error(readAxiosError(error, "请求失败"));
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}
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}
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export async function requestImageQuestion(config: AiConfig, messages: ChatCompletionMessage[], onDelta: (text: string) => void) {
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let buffer = "";
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let answer = "";
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let processedLength = 0;
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try {
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const response = await axios.post(
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aiApiUrl(config, "/chat/completions"),
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{
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model: config.model,
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messages: withSystemMessage(config, messages),
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stream: true,
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},
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{
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headers: {
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...aiHeaders(config, "application/json"),
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} as Record<string, string>,
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responseType: "text",
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onDownloadProgress: (event) => {
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const responseText = String(event.event?.target?.responseText || "");
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const nextText = responseText.slice(processedLength);
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processedLength = responseText.length;
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buffer += nextText;
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const chunks = buffer.split("\n\n");
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buffer = chunks.pop() || "";
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for (const chunk of chunks) {
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parseStreamChunk(chunk, (delta) => {
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answer += delta;
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onDelta(answer);
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});
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}
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},
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},
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);
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if (typeof response.data === "object" && response.data && "code" in response.data && (response.data as { code?: number; msg?: string }).code !== 0) {
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throw new Error((response.data as { msg?: string }).msg || "请求失败");
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}
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if (typeof response.data === "string") {
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let apiError = "";
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try {
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const payload = JSON.parse(response.data) as { code?: number; msg?: string };
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if (typeof payload.code === "number" && payload.code !== 0) {
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apiError = payload.msg || "请求失败";
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}
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} catch {
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// ignore plain text stream content
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}
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if (apiError) throw new Error(apiError);
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}
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if (buffer) {
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parseStreamChunk(buffer, (delta) => {
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answer += delta;
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onDelta(answer);
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});
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}
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} catch (error) {
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throw new Error(readAxiosError(error, "请求失败"));
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}
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return answer || "没有返回内容";
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}
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export async function fetchImageModels(config: AiConfig) {
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if (config.channelMode === "remote") return config.models;
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try {
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const response = await axios.get<{ data?: Array<{ id?: string }>; error?: { message?: string } }>(buildApiUrl(config.baseUrl, "/models"), {
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headers: {
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Authorization: `Bearer ${config.apiKey}`,
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},
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});
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return (response.data.data || [])
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.map((model) => model.id)
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.filter((id): id is string => Boolean(id))
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.sort((a, b) => a.localeCompare(b));
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} catch (error) {
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throw new Error(readAxiosError(error, "读取模型失败"));
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}
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}
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