Merge branch 'develop' of https://github.com/HBAI-Ltd/Toonflow-app into develop

backup/agents/storyboard/generateImagePromptsTool.ts

@@ -104,9 +104,7 @@ async function generateGridPrompt(options: GridPromptOptions): Promise<GridPromp
 
   if (!mainPrompts) return { prompt: errData, gridLayout: layout };
 
-  const chatModel = await u.ai.text({});
-
-  const result = await chatModel!.invoke({
+  const result = await u.ai.text.invoke({
     messages: [
       {
         role: "system",

backup/agents/storyboard/generateImageTool.ts

@@ -215,8 +215,7 @@ async function filterRelevantAssets(prompts: string[], allResources: ResourceIte
     return availableImages;
   }
 
-  const chatModel = await u.ai.text({});
-  const result = await chatModel!.invoke({
+  const result = await u.ai.text.invoke({
     messages: [
       {
         role: "user",
@@ -231,23 +230,24 @@ ${availableResources.map((r) => `- ${r.name}：${r.intro}`).join("\n")}
 请仅选择在分镜中明确出现或被提及的角色、场景、道具。不要选择与分镜内容无关的资产。`,
       },
     ],
-    responseFormat: {
-      type: "json_schema",
-      jsonSchema: {
-        name: "filteredAssets",
-        strict: true,
-        schema: z.toJSONSchema(filteredAssetsSchema),
-      },
+    output: {
+      relevantAssets: z
+        .array(
+          z.object({
+            name: z.string().describe("资产名称"),
+            reason: z.string().describe("选择该资产的原因"),
+          }),
+        )
+        .describe("与分镜内容相关的资产列表"),
     },
   });
 
-  const data = result?.json as z.infer<typeof filteredAssetsSchema>;
 
-  if (!data?.relevantAssets || data.relevantAssets.length === 0) {
+  if (!result?.relevantAssets || result.relevantAssets.length === 0) {
     return availableImages;
   }
 
-  const relevantNames = new Set(data.relevantAssets.map((a) => a.name));
+  const relevantNames = new Set(result.relevantAssets.map((a) => a.name));
   const filteredImages = availableImages.filter((img) => relevantNames.has(img.name));
 
   return filteredImages.length > 0 ? filteredImages : availableImages;
@@ -318,7 +318,7 @@ export default async (cells: { prompt: string }[], scriptId: number, projectId:
 
   const processedImages = await processImages(filteredImages);
 
-  const contentStr = await u.ai.generateImage({
+  const contentStr = await u.ai.image({
     systemPrompt: resourcesMapPrompts,
     prompt: prompts,
     size: "4K",

src/agents/storyboard/generateImageTool.ts

@@ -343,7 +343,7 @@ export default async (cells: { prompt: string }[], scriptId: number, projectId:
 
   const processedImages = await processImages(filteredImages);
 
-  const contentStr = await u.ai.generateImage({
+  const contentStr = await u.ai.image({
     systemPrompt: resourcesMapPrompts,
     prompt: prompts,
     size: "4K",

src/env.ts

@@ -1,13 +1,18 @@
-import { readFileSync, existsSync } from "fs";
+import { readFileSync, existsSync, writeFileSync } from "fs";
+
+function createDefaultEnvFile(path: string) {
+  const defaultContent = ["# 环境变量配置", "NODE_ENV=dev"].join("\n");
+  writeFileSync(path, defaultContent, { encoding: "utf8" });
+  console.log(`[环境变量]: 已创建默认的 ${path}`);
+}
 
 function loadDotenvESM(envPath = ".env.local") {
-  // 尝试从 userData 目录读取环境变量，如果不存在则使用当前目录
   let finalPath: string;
 
   if (typeof process.versions?.electron !== "undefined") {
     const { app } = require("electron");
-    finalPath = app.getPath("userData");
-    // 如果 userData 目录中不存在，尝试使用当前目录
+    finalPath = app.getPath("userData") + `/${envPath}`;
+    // 如果 userData 目录下的 env 文件不存在，则尝试当前目录
     if (!existsSync(finalPath)) {
       finalPath = envPath;
     }
@@ -15,9 +20,9 @@ function loadDotenvESM(envPath = ".env.local") {
     finalPath = envPath;
   }
 
+  // 若文件不存在，自动创建一个带默认内容的环境变量文件
   if (!existsSync(finalPath)) {
-    console.log(`[环境变量]: ${envPath} 文件不存在`);
-    return;
+    createDefaultEnvFile(finalPath);
   }
 
   const text = readFileSync(finalPath, "utf8");
@@ -25,7 +30,8 @@ function loadDotenvESM(envPath = ".env.local") {
     const idx = line.indexOf("=");
     if (idx > 0) process.env[line.slice(0, idx).trim()] = line.slice(idx + 1).trim();
   }
-  console.log(`[环境变量]: ${finalPath}`);
+  console.log(`[环境变量]: 已加载 ${finalPath}`);
 }
 
+// 若非 Electron 环境，则加载 .env.local
 if (typeof process.versions?.electron == "undefined") loadDotenvESM(".env.local");

src/routes/assets/generateAssets.ts

@@ -124,7 +124,7 @@ export default router.post(
       assetsId: id,
     });
 
-    const contentStr = await u.ai.generateImage({
+    const contentStr = await u.ai.image({
       systemPrompt,
       prompt: userPrompt,
       imageBase64: base64 ? [base64] : [],

src/routes/storyboard/batchSuperScoreImage.ts

@@ -22,7 +22,7 @@ async function superResolutionAndSave(
   projectId: number,
   videoRatio: string,
 ): Promise<{ ossPath: string; base64: string }> {
-  const contentStr = await u.ai.generateImage({
+  const contentStr = await u.ai.image({
     aspectRatio: videoRatio,
     size: "1K",
     resType: "b64",

src/routes/storyboard/chatStoryboard.ts

@@ -8,7 +8,6 @@ expressWs(router as unknown as Application);
 router.ws("/", async (ws, req) => {
   let agent: Storyboard;
 
-  const config = await u.getConfig("language");
 
   const projectId = req.query.projectId;
   const scriptId = req.query.scriptId;
@@ -20,10 +19,6 @@ router.ws("/", async (ws, req) => {
 
   agent = new Storyboard(Number(projectId), Number(scriptId));
 
-  agent.modelName = config.model ?? "";
-  agent.baseURL = config.baseURL ?? "";
-  agent.apiKey = config.apiKey ?? "";
-
   const existing = await u
     .db("t_chatHistory")
     .where({ projectId: Number(projectId) })

src/routes/video/addVideoConfig.ts

@@ -6,11 +6,13 @@ import { z } from "zod";
 const router = express.Router();
 
 // 图片项schema
-const imageItemSchema = z.object({
+const imageItemSchema = z
+  .object({
     id: z.number(),
     filePath: z.string(),
     prompt: z.string().optional(),
-}).nullable();
+  })
+  .nullable();
 
 // 新增视频配置
 export default router.post(
@@ -22,31 +24,24 @@ export default router.post(
     mode: z.enum(["startEnd", "multi", "single"]),
     startFrame: imageItemSchema.optional(),
     endFrame: imageItemSchema.optional(),
-    images: z.array(z.object({
+    images: z
+      .array(
+        z.object({
           id: z.number(),
           filePath: z.string(),
           prompt: z.string().optional(),
-    })).optional(),
+        }),
+      )
+      .optional(),
     resolution: z.string(),
     duration: z.number(),
     prompt: z.string().optional(),
   }),
   async (req, res) => {
-    const { 
-      scriptId, 
-      projectId, 
-      manufacturer, 
-      mode, 
-      startFrame, 
-      endFrame, 
-      images, 
-      resolution, 
-      duration, 
-      prompt 
-    } = req.body;
+    const { scriptId, projectId, manufacturer, mode, startFrame, endFrame, images, resolution, duration, prompt } = req.body;
 
     // 生成新ID
-    const maxIdResult = await u.db("t_videoConfig").max("id as maxId").first();
+    const maxIdResult: any = await u.db("t_videoConfig").max("id as maxId").first();
     const newId = (maxIdResult?.maxId || 0) + 1;
     const now = Date.now();
 
@@ -68,7 +63,8 @@ export default router.post(
       updateTime: now,
     });
 
-    res.status(200).send(success({ 
+    res.status(200).send(
+      success({
         message: "新增视频配置成功",
         data: {
           id: newId,
@@ -84,7 +80,8 @@ export default router.post(
           prompt: prompt || "",
           selectedResultId: null,
           createdAt: new Date(now).toISOString(),
-      }
-    }));
+        },
+      }),
+    );
   },
 );

src/routes/video/generateVideo.ts

@@ -149,17 +149,14 @@ ${prompt}
 3. 关键人物在画面中全部清晰显示，不得被遮挡、缺失或省略
 4. 画面真实、细致，无畸形、无模糊、无杂物、无多余人物、无文字、水印、logo
 `;
-
-    const videoPath = await u.ai.generateVideo(
-      {
+    const videoPath = await u.ai.video({
       imageBase64,
       savePath,
       prompt: inputPrompt,
       duration: duration as any,
       aspectRatio: resolution as any,
-      },
-      type!,
-    );
+      resolution: resolution as any,
+    });
 
     if (videoPath) {
       // 生成成功，更新状态为 1

src/routes/video/upDateVideoConfig.ts

@@ -47,8 +47,9 @@ export default router.post(
 
     // 获取更新后的数据
     const updatedConfig = await u.db("t_videoConfig").where({ id }).first();
-
-    res.status(200).send(success({ 
+    if (updatedConfig) {
+      res.status(200).send(
+        success({
           message: "更新视频配置成功",
           data: {
             id: updatedConfig.id,
@@ -63,8 +64,12 @@ export default router.post(
             duration: updatedConfig.duration,
             prompt: updatedConfig.prompt,
             selectedResultId: updatedConfig.selectedResultId,
-        createdAt: new Date(updatedConfig.createTime).toISOString(),
+            createdAt: new Date(updatedConfig.createTime!).toISOString(),
+          },
+        }),
+      );
+    } else {
+      res.status(200).send(error("更新配置失败"));
     }
-    }));
   },
 );

src/utils/ai/image/index.ts

@@ -63,5 +63,5 @@ export default async (input: ImageConfig, config?: AIConfig) => {
   let imageUrl = await manufacturerFn(input, { model, apiKey, baseURL });
   if (!input.resType) input.resType = "b64";
   if (input.resType === "b64" && imageUrl.startsWith("http")) imageUrl = await urlToBase64(imageUrl);
-  return input;
+  return imageUrl;
 };

src/utils/ai/text/index.ts

@@ -45,14 +45,14 @@ const buildOptions = async (input: AIInput<any>, config: AIConfig) => {
     },
   };
 
-  const output = input.output ? outputBuilders[owned.responseFormat]?.(input.output) ?? null : null;
+  const output = input.output ? (outputBuilders[owned.responseFormat]?.(input.output) ?? null) : null;
 
   return {
     config: {
       model:
         process.env.NODE_ENV === "dev"
           ? wrapLanguageModel({
-              model: modelInstance(model!) as any,
+              model: modelInstance.chat(model!) as any,
               middleware: devToolsMiddleware(),
             })
           : (modelInstance(model!) as LanguageModel),

src/utils/ai/text/modelList.ts

@@ -4,6 +4,7 @@ import { createZhipu } from "zhipu-ai-provider";
 import { createQwen } from "qwen-ai-provider";
 import { createGoogleGenerativeAI } from "@ai-sdk/google";
 import { createAnthropic } from "@ai-sdk/anthropic";
+import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
 
 interface Owned {
   manufacturer: string;
@@ -18,7 +19,8 @@ interface Owned {
     | typeof createZhipu
     | typeof createQwen
     | typeof createGoogleGenerativeAI
-    | typeof createAnthropic;
+    | typeof createAnthropic
+    | typeof createOpenAICompatible;
 }
 
 const modelList: Owned[] = [
@@ -409,6 +411,15 @@ const modelList: Owned[] = [
     instance: createAnthropic,
     tool: true,
   },
+  {
+    manufacturer: "other",
+    model: "gpt-4.1",
+    responseFormat: "schema",
+    image: true,
+    think: false,
+    instance: createOpenAICompatible,
+    tool: true,
+  },
 ];
 
 export default modelList;

src/utils/editImage.ts

@@ -79,7 +79,7 @@ async function convertDirectiveAndImages(images: Record<string, string>, directi
  */
 export default async (images: Record<string, string>, directive: string, projectId: number) => {
   const { prompt, images: base64Images } = await convertDirectiveAndImages(images, directive);
-  const contentStr = await u.ai.generateImage({
+  const contentStr = await u.ai.image({
     systemPrompt: "根据用户提供的具体修改指令，对上传的图片进行智能编辑。",
     prompt: prompt,
     imageBase64: base64Images,