新增图片生成与上传执行管线：nano-banana-2真实出图→上传→公网URL回填→上传后二次生成API调用稿

- 新增 image_generation_upload_rules.md、post_upload_call_draft_rules.md 规则文件，scripts/ 脚本目录 - 工作流新增阶段 5.1 图片生成与上传、5.2 上传后调用稿分支，调整原有步骤编号 - 所有模板和规则强制要求：API 图片输入使用上传后的公网 URL / asset:// URI，禁止本地路径或占位符 - 官网 Prompt 模板强制要求使用 @官网上传名，绑定已上传资产 - 附件/API 资产清单新增状态追踪列（pending_generation / pending_upload / generated_uploaded_ready 等）和 uploaded_assets.json 回填规则 - api_payload_rules.md 新增"上传后二次生成硬约束"，要求 JSONL 必须在图片上传完成后基于真实 URL 重新生成 - image_model_provider_rules.md 明确 nano-banana-2 为默认执行资源（非仅提示词名称），新增图片生成/上传执行标记 --- 核心变更概括：工作流从"只写提示词"升级为"提示词→真实出图→上传→获取公网 URL→回填→二次生成调用稿"的完整资产管线。
2026-05-26 15:45:46 +08:00
parent eb8e8b5ce9
commit 2eb629fe4b
13 changed files with 664 additions and 17 deletions
@@ -0,0 +1,208 @@
+#!/usr/bin/env node
+
+import { mkdir, readFile, writeFile } from "node:fs/promises";
+import path from "node:path";
+
+const DEFAULT_UPLOAD_URL =
+  "https://lms.laitool.cn/lms/FileUpload/FileUpload/01564ca6c907eab817058e5356bb40b57cd3f3171adbbc9ea49be0de448cc68e";
+
+function argValue(name, fallback = undefined) {
+  const index = process.argv.indexOf(name);
+  if (index === -1 || index + 1 >= process.argv.length) return fallback;
+  return process.argv[index + 1];
+}
+
+function requireArg(name) {
+  const value = argValue(name);
+  if (!value) {
+    throw new Error(`Missing required argument: ${name}`);
+  }
+  return value;
+}
+
+async function readJson(filePath) {
+  return JSON.parse(await readFile(filePath, "utf8"));
+}
+
+function sanitizeName(value) {
+  return String(value)
+    .trim()
+    .replace(/[\\/:*?"<>|]+/g, "_")
+    .replace(/\s+/g, "_")
+    .slice(0, 120);
+}
+
+function extensionFromMime(contentType) {
+  if (contentType === "image/png") return ".png";
+  if (contentType === "image/webp") return ".webp";
+  return ".jpg";
+}
+
+function extractInlineImage(response) {
+  const candidates = response?.candidates ?? [];
+  for (const candidate of candidates) {
+    const parts = candidate?.content?.parts ?? [];
+    for (const part of parts) {
+      const inlineData = part.inlineData ?? part.inline_data;
+      if (inlineData?.data) {
+        return {
+          base64: inlineData.data,
+          contentType: inlineData.mimeType ?? inlineData.mime_type ?? "image/jpeg",
+        };
+      }
+    }
+  }
+  throw new Error("Image model response did not contain inline image data.");
+}
+
+function extractUploadUrl(resultText) {
+  try {
+    const json = JSON.parse(resultText);
+    return (
+      json.url ??
+      json.fileUrl ??
+      json.fileURL ??
+      json.data?.url ??
+      json.data?.fileUrl ??
+      json.data?.fileURL ??
+      json.data?.path ??
+      json.result?.url ??
+      json.result?.fileUrl ??
+      ""
+    );
+  } catch {
+    const match = resultText.match(/https?:\/\/[^\s"'<>]+/);
+    return match?.[0] ?? "";
+  }
+}
+
+async function generateImage({ prompt, model, apiKey, aspectRatio, contentType }) {
+  const endpoint = `https://magic666.top/v1beta/models/${encodeURIComponent(
+    model,
+  )}:generateContent?key=${encodeURIComponent(apiKey)}`;
+
+
+  const response = await fetch(endpoint, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({
+      contents: [{ role: "user", parts: [{ text: prompt }] }],
+      generationConfig: {
+        responseModalities: ["IMAGE"],
+        ...(aspectRatio ? { aspectRatio } : {}),
+      },
+    }),
+  });
+
+  const responseText = await response.text();
+  if (!response.ok) {
+    throw new Error(`Image generation failed: ${response.status} ${responseText}`);
+  }
+
+  const image = extractInlineImage(JSON.parse(responseText));
+  return {
+    base64: image.base64,
+    contentType: contentType ?? image.contentType,
+  };
+}
+
+async function uploadImage({ base64, fileName, contentType, uploadUrl }) {
+  const originalSize = Buffer.byteLength(Buffer.from(base64, "base64")).toString();
+  const response = await fetch(uploadUrl, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    redirect: "follow",
+    body: JSON.stringify({
+      file: base64,
+      fileName,
+      contentType,
+      metadata: {
+        uploadTime: new Date().toISOString(),
+        originalSize,
+      },
+    }),
+  });
+
+  const resultText = await response.text();
+  if (!response.ok) {
+    throw new Error(`Image upload failed: ${response.status} ${resultText}`);
+  }
+
+  return {
+    raw: resultText,
+    url: extractUploadUrl(resultText),
+  };
+}
+
+async function main() {
+  const jobsPath = requireArg("--jobs");
+  const outDir = path.resolve(argValue("--out-dir", "outputs/generated_assets"));
+  const manifestPath = path.resolve(argValue("--manifest", path.join(outDir, "uploaded_assets.json")));
+  // const apiKey = process.env.GEMINI_API_KEY ?? process.env.GOOGLE_API_KEY;
+
+  const apiKey = "sk-QLEqdjgAE457aFsxmvUHdoj0EnyBcFaX23I4DxCJ8bgnrJNw"
+  const model = argValue("--model", process.env.NANO_BANANA_MODEL ?? "nano-banana-2");
+  const uploadUrl = argValue("--upload-url", process.env.IMAGE_UPLOAD_URL ?? DEFAULT_UPLOAD_URL);
+
+  if (!apiKey) {
+    throw new Error("Set GEMINI_API_KEY or GOOGLE_API_KEY before running image generation.");
+  }
+  const jobs = await readJson(jobsPath);
+  if (!Array.isArray(jobs)) {
+    throw new Error("Jobs file must be a JSON array.");
+  }
+
+  await mkdir(outDir, { recursive: true });
+  const results = [];
+
+  for (const [index, job] of jobs.entries()) {
+    if (!job.prompt) {
+      throw new Error(`Job ${index + 1} is missing prompt.`);
+    }
+
+    const generated = await generateImage({
+      prompt: job.prompt,
+      model: "gemini-3-pro-image-preview",
+      apiKey,
+      aspectRatio: job.aspectRatio,
+      contentType: job.contentType,
+    });
+
+    const fileName =
+      job.fileName ??
+      `${String(index + 1).padStart(3, "0")}_${sanitizeName(job.internalRef ?? job.name ?? "asset")}${extensionFromMime(
+        generated.contentType,
+      )}`;
+    const localPath = path.join(outDir, fileName);
+    await writeFile(localPath, Buffer.from(generated.base64, "base64"));
+
+    const uploaded = await uploadImage({
+      base64: generated.base64,
+      fileName,
+      contentType: generated.contentType,
+      uploadUrl,
+    });
+
+    results.push({
+      internalRef: job.internalRef ?? "",
+      type: job.type ?? "",
+      promptName: job.promptName ?? job.name ?? "",
+      fileName,
+      localPath,
+      contentType: generated.contentType,
+      publicUrl: uploaded.url,
+      uploadRawResponse: uploaded.raw,
+      jimengUploadName: job.jimengUploadName ?? path.parse(fileName).name,
+      referenceDuty: job.referenceDuty ?? "",
+      status: uploaded.url ? "uploaded" : "uploaded_url_unparsed",
+    });
+  }
+
+  await writeFile(manifestPath, `${JSON.stringify(results, null, 2)}\n`, "utf8");
+  console.log(`Wrote ${results.length} uploaded asset records to ${manifestPath}`);
+}
+
+main().catch((error) => {
+  console.error(error);
+  process.exitCode = 1;
+});