ai-chatbot/lib/ai/canvas-agent-runtime/video-image-functions.ts

import sharp from "sharp";
import { uploadFile } from "@/lib/storage/service";
import { fetchImageBufferFromUrl } from "@/lib/ai/rmbg/service";
import { resolveCanvasRuntimeEndpoint } from "@/lib/canvas/capabilities/internal-endpoint";
import { requestLongTaskResult } from "@/lib/client/long-task";
import type { VideoCanvasFunctionDefinition } from "@/lib/video-canvas/config";

export async function processVideoCanvasImage(
  params: {
    userId: string;
    request: Request;
    definition: VideoCanvasFunctionDefinition;
    imageUrl: string;
    args: Record<string, unknown>;
    prompt: string;
    callId: string;
  },
  dependencies?: { upload?: typeof uploadFile; readImage?: (url: string) => Promise<Buffer> },
) {
  const { definition, imageUrl, args } = params;
  if (definition.key === "grid-split" || definition.key === "image-crop") {
    const bytes = await (dependencies?.readImage || fetchImageBufferFromUrl)(imageUrl),
      metadata = await sharp(bytes).metadata();
    if (!metadata.width || !metadata.height) throw new Error("源图片无法读取");
    const rows = definition.key === "grid-split" ? Number(args.rows) : 1,
      columns = definition.key === "grid-split" ? Number(args.columns || rows) : 1;
    if (
      ![rows, columns].every((value) => Number.isInteger(value) && value >= 1 && value <= 5) ||
      rows * columns > 25
    )
      throw new Error("宫格行列必须为 1–5，最多 25 张");
    const outputs: Array<{ url: string }> = [];
    for (let row = 0; row < rows; row++)
      for (let column = 0; column < columns; column++) {
        const left =
          definition.key === "grid-split"
            ? Math.floor((metadata.width * column) / columns)
            : Math.round(Number(args.x));
        const top =
          definition.key === "grid-split"
            ? Math.floor((metadata.height * row) / rows)
            : Math.round(Number(args.y));
        const width =
          definition.key === "grid-split"
            ? Math.floor((metadata.width * (column + 1)) / columns) - left
            : Math.round(Number(args.width));
        const height =
          definition.key === "grid-split"
            ? Math.floor((metadata.height * (row + 1)) / rows) - top
            : Math.round(Number(args.height));
        if (
          ![left, top, width, height].every(Number.isFinite) ||
          left < 0 ||
          top < 0 ||
          width < 1 ||
          height < 1 ||
          left + width > metadata.width ||
          top + height > metadata.height
        )
          throw new Error("裁剪坐标超出真实图片边界");
        const output = await sharp(bytes).extract({ left, top, width, height }).png().toBuffer();
        const result = await (dependencies?.upload || uploadFile)(
          `video-agent-${crypto.randomUUID()}.png`,
          new Uint8Array(output).buffer,
        );
        outputs.push({ url: result.url });
      }
    return outputs;
  }
  if (definition.route === "remove-bg") {
    const { executeRmbgJob } = await import("@/lib/ai/rmbg/service");
    const result = await executeRmbgJob({
      userId: params.userId,
      imageBuffer: await fetchImageBufferFromUrl(imageUrl),
      sourceImageUrl: imageUrl,
      prompt: params.prompt,
    });
    return [{ url: result.original_url }];
  }
  if (definition.route === "extend") {
    const { executeExtendJob } = await import("@/lib/ai/extend/service");
    const result = await executeExtendJob({
      userId: params.userId,
      imageUrl,
      sourceImageUrl: imageUrl,
      prompt: params.prompt,
      xScale: Number(args.xScale) || 1.5,
      yScale: Number(args.yScale) || 1.5,
      requestId: params.callId,
    });
    return [{ url: result.original_url }];
  }
  if (definition.route === "layer-split") {
    const { executeLayerSplitJob } = await import("@/lib/ai/layer-split/service");
    const result = await executeLayerSplitJob({
      userId: params.userId,
      imageUrl,
      prompt: params.prompt,
    });
    return result.layers.map((layer) => ({ url: layer.originalUrl }));
  }
  const cookie = params.request.headers.get("cookie");
  if (definition.route === "enhance") {
    const result = await requestLongTaskResult({
      endpoint: resolveCanvasRuntimeEndpoint("/api/enhance", params.request.url),
      payload: { imageUrl, scaleFactor: Number(args.scaleFactor) || 2 },
      headers: cookie ? { cookie } : undefined,
      timeoutMs: 10 * 60_000,
    });
    if (!result?.original_url) throw new Error("增强服务没有返回真实图片");
    return [{ url: String(result.original_url) }];
  }
  if (definition.route === "angle-edit") {
    const response = await fetch(
      resolveCanvasRuntimeEndpoint("/api/angle-edit", params.request.url),
      {
        method: "POST",
        headers: { "Content-Type": "application/json", ...(cookie ? { cookie } : {}) },
        body: JSON.stringify({
          image_url: imageUrl,
          horizontal_angle: Number(args.horizontalAngle) || 0,
          vertical_angle: Number(args.verticalAngle) || 0,
          zoom: Number(args.zoom) || 0,
        }),
      },
    );
    const result = await response.json();
    const url = result.image_url || result.original_url;
    if (!response.ok || !url) throw new Error("多角度编辑服务没有返回真实图片");
    return [{ url: String(url) }];
  }
  throw new Error("此功能需要在对应工具面板中配置后执行");
}