所有ai 分模块接入，待测试

src/agents/outlineScript/index.ts

@@ -611,35 +611,18 @@ ${task}
     this.log(`Sub-Agent 调用`, agentType);
 
     const promptsList = await u.db("t_prompts").where("code", "in", ["outlineScript-a1", "outlineScript-a2", "outlineScript-director"]);
-    const promptConfig = await u.getPromptAi(promptsList.map((i) => i.id) as number[]);
+    const promptConfig = await u.getPromptAi("outlineScriptAgent");
 
     const errPrompts = "不论用户说什么，请直接输出Agent配置异常";
 
     const getAiPromptConfig = (code: string) => {
       const item = promptsList.find((p) => p.code === code);
-      const subConfig = promptConfig.find((sub) => sub?.promptsId == item?.id);
+      return item?.customValue || item?.defaultValue || errPrompts;
-      if (subConfig) {
-        return {
-          prompt: item?.customValue || item?.defaultValue || errPrompts,
-          apiConfig: { ...subConfig },
-        };
-      } else {
-        return {
-          prompt: item?.customValue || item?.defaultValue || errPrompts,
-          apiConfig: {},
-        };
-      }
     };
     const a1Prompt = getAiPromptConfig("outlineScript-a1");
     const a2Prompt = getAiPromptConfig("outlineScript-a2");
     const directorPrompt = getAiPromptConfig("outlineScript-director");
-    const SYSTEM_PROMPTS: Record<
+    const SYSTEM_PROMPTS = {
-      AgentType,
-      {
-        prompt: string;
-        apiConfig: Object;
-      }
-    > = {
       AI1: a1Prompt,
       AI2: a2Prompt,
       director: directorPrompt,
@@ -649,12 +632,12 @@ ${task}
 
     const { fullStream } = await u.ai.text.stream(
       {
-        system: SYSTEM_PROMPTS[agentType].prompt,
+        system: SYSTEM_PROMPTS[agentType],
         tools: this.getSubAgentTools(),
         messages: [{ role: "user", content: context }],
         maxStep: 100,
       },
-      SYSTEM_PROMPTS[agentType].apiConfig,
+      promptConfig,
     );
 
     let fullResponse = "";
@@ -717,7 +700,9 @@ ${task}
     const envContext = await this.buildEnvironmentContext();
 
     const prompts = await u.db("t_prompts").where("code", "outlineScript-main").first();
-    const promptConfig = await u.getPromptAi(prompts?.id);
+    console.log("%c Line:703 🍭 prompts", "background:#f5ce50", prompts);
+    const promptConfig = await u.getPromptAi("outlineScriptAgent");
+
     const mainPrompts = prompts?.customValue || prompts?.defaultValue || "不论用户说什么，请直接输出Agent配置异常";
 
     const { fullStream } = await u.ai.text.stream(

src/agents/storyboard/generateImagePromptsTool.ts

@@ -98,7 +98,7 @@ async function generateGridPrompt(options: GridPromptOptions): Promise<GridPromp
       : "";
 
   const promptsData = await u.db("t_prompts").where("code", "generateImagePrompts").first();
-  const promptAiConfig = await u.getPromptAi(promptsData?.id);
+  const promptAiConfig = await u.getPromptAi("storyboardAgent");
   const mainPrompts = promptsData?.customValue || promptsData?.defaultValue;
   const errData = `请输出${options.prompts.length}张图片\n提示词如下:\n${options.prompts.map((p, i) => `第${i + 1}格: ${p}`).join("\n")}`;
 

src/agents/storyboard/generateImageTool.ts

@@ -215,11 +215,13 @@ async function filterRelevantAssets(prompts: string[], allResources: ResourceIte
     return availableImages;
   }
 
-  const { relevantAssets } = await u.ai.text.invoke({
+  const apiConfig = await u.getPromptAi("storyboardAgent");
-    messages: [
+  const { relevantAssets } = await u.ai.text.invoke(
-      {
+    {
-        role: "user",
+      messages: [
-        content: `请分析以下分镜描述，从可用资产中筛选出与分镜内容直接相关的资产。
+        {
+          role: "user",
+          content: `请分析以下分镜描述，从可用资产中筛选出与分镜内容直接相关的资产。
 
 分镜描述：
 ${prompts.map((p, i) => `${i + 1}. ${p}`).join("\n")}
@@ -228,45 +230,21 @@ ${prompts.map((p, i) => `${i + 1}. ${p}`).join("\n")}
 ${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。`,
+        },
+      ],
+      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"),
       },
-    ],
-    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"),
     },
-  });
+    apiConfig,
-  //   const result = await chatModel!.invoke({
+  );
-  //     messages: [
-  //       {
-  //         role: "user",
-  //         content: `请分析以下分镜描述，从可用资产中筛选出与分镜内容直接相关的资产。
-
-  // 分镜描述：
-  // ${prompts.map((p, i) => `${i + 1}. ${p}`).join("\n")}
-
-  // 可用资产列表：
-  // ${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),
-  //       },
-  //     },
-  //   });
-
-  // const data = result?.json as z.infer<typeof filteredAssetsSchema>;
 
   if (!relevantAssets || relevantAssets.length === 0) {
     return availableImages;
@@ -342,14 +320,18 @@ export default async (cells: { prompt: string }[], scriptId: number, projectId:
   console.log("====润色后：", prompts);
 
   const processedImages = await processImages(filteredImages);
+  const apiConfig = await u.getPromptAi("storyboardImage");
 
-  const contentStr = await u.ai.image({
+  const contentStr = await u.ai.image(
-    systemPrompt: resourcesMapPrompts,
+    {
-    prompt: prompts,
+      systemPrompt: resourcesMapPrompts,
-    size: "4K",
+      prompt: prompts,
-    aspectRatio: projectInfo?.videoRatio ? (projectInfo.videoRatio as any) : "16:9",
+      size: "4K",
-    imageBase64: processedImages.map((buf) => buf.toString("base64")),
+      aspectRatio: projectInfo?.videoRatio ? (projectInfo.videoRatio as any) : "16:9",
-  });
+      imageBase64: processedImages.map((buf) => buf.toString("base64")),
+    },
+    apiConfig,
+  );
 
   const match = contentStr.match(/base64,([A-Za-z0-9+/=]+)/);
   const base64Str = match?.[1] ?? contentStr;

src/agents/storyboard/index.ts

@@ -63,9 +63,6 @@ export default class Storyboard {
 
   // 更新shopts
   public updatePreShots(segmentId: number, cellId: number, cell: { src?: string; prompt?: string; id?: string }) {
-    console.log("%c Line:76 🍤 segmentId", "background:#465975", segmentId);
-    console.log("%c Line:76 🍷 cellId", "background:#ffdd4d", cellId);
-    console.log("%c Line:76 🍢 cell", "background:#ffdd4d", cell);
     const shotIndex = this.shots.findIndex((item) => item.segmentId === segmentId);
     if (shotIndex === -1) {
       return `分镜 ${segmentId} 不存在，请检查分镜ID是否正确`;
@@ -594,34 +591,17 @@ ${task}
     this.log(`Sub-Agent 调用`, agentType);
 
     const promptsList = await u.db("t_prompts").where("code", "in", ["storyboard-segment", "storyboard-shot"]);
-    const promptConfig = await u.getPromptAi(promptsList.map((i) => i.id) as number[]);
+    const promptConfig = await u.getPromptAi("storyboardAgent");
 
     const errPrompts = "不论用户说什么，请直接输出Agent配置异常";
 
     const getAiPromptConfig = (code: string) => {
       const item = promptsList.find((p) => p.code === code);
-      const subConfig = promptConfig.find((sub) => sub?.promptsId == item?.id);
+      return item?.customValue || item?.defaultValue || errPrompts;
-      if (subConfig) {
-        return {
-          prompt: item?.customValue || item?.defaultValue || errPrompts,
-          apiConfig: { ...subConfig },
-        };
-      } else {
-        return {
-          prompt: item?.customValue || item?.defaultValue || errPrompts,
-          apiConfig: {},
-        };
-      }
     };
     const segmentAgent = getAiPromptConfig("storyboard-segment");
     const shotAgent = getAiPromptConfig("storyboard-shot");
-    const SYSTEM_PROMPTS: Record<
+    const SYSTEM_PROMPTS = {
-      AgentType,
-      {
-        prompt: string;
-        apiConfig: Object;
-      }
-    > = {
       segmentAgent: segmentAgent,
       shotAgent: shotAgent,
     };
@@ -630,12 +610,12 @@ ${task}
 
     const { fullStream } = await u.ai.text.stream(
       {
-        system: SYSTEM_PROMPTS[agentType].prompt,
+        system: SYSTEM_PROMPTS[agentType],
         tools: this.getSubAgentTools(agentType),
         messages: [{ role: "user", content: context }],
         maxStep: 100,
       },
-      SYSTEM_PROMPTS[agentType].apiConfig,
+      promptConfig,
     );
 
     let fullResponse = "";
@@ -700,7 +680,7 @@ ${task}
     const envContext = await this.buildEnvironmentContext();
 
     const prompts = await u.db("t_prompts").where("code", "storyboard-main").first();
-    const promptConfig = await u.getPromptAi(prompts?.id);
+    const promptConfig = await u.getPromptAi("storyboardAgent");
 
     const mainPrompts = prompts?.customValue || prompts?.defaultValue || "不论用户说什么，请直接输出Agent配置异常";
 

src/routes/assets/generateAssets.ts

@@ -123,14 +123,18 @@ export default router.post(
       state: "生成中",
       assetsId: id,
     });
+    const apiConfig = await u.getPromptAi("assetsImage");
 
-    const contentStr = await u.ai.image({
+    const contentStr = await u.ai.image(
-      systemPrompt,
+      {
-      prompt: userPrompt,
+        systemPrompt,
-      imageBase64: base64 ? [base64] : [],
+        prompt: userPrompt,
-      size: "2K",
+        imageBase64: base64 ? [base64] : [],
-      aspectRatio: "16:9",
+        size: "2K",
-    });
+        aspectRatio: "16:9",
+      },
+      apiConfig,
+    );
 
     let insertType;
     const match = contentStr.match(/base64,([A-Za-z0-9+/=]+)/);

src/routes/assets/polishPrompt.ts

@@ -88,31 +88,16 @@ export default router.post(
     const result: ResultItem[] = Object.values(itemMap);
 
     const promptsList = await u.db("t_prompts").where("code", "in", ["role-polish", "scene-polish", "storyboard-polish", "tool-polish"]);
-    const propmptIds = promptsList.map((i) => i.id);
+    const apiConfigData = await u.getPromptAi("assetsPrompt");
-    const mapList = await u
-      .db("t_aiModelMap")
-      .leftJoin("t_config", "t_config.id", "t_aiModelMap.configId")
-      .whereIn("t_aiModelMap.promptsId", propmptIds as number[])
-      .select("t_config.model", "t_config.apiKey", "t_config.baseUrl", "t_config.manufacturer", "t_aiModelMap.promptsId");
     const errPrompts = "不论用户说什么，请直接输出AI配置异常";
     const getPromptValue = (code: string) => {
       const item = promptsList.find((p) => p.code === code);
-      if (item) {
+      return item?.customValue ?? item?.defaultValue ?? errPrompts;
-        const apiData = mapList.find((i) => i.promptsId == item.id);
-        if (apiData) delete apiData?.promptsId;
-        return { prompt: item?.customValue ?? item?.defaultValue ?? errPrompts, apiData: { ...(apiData ?? {}) } };
-      } else {
-        return {
-          prompt: errPrompts,
-          apiData: {},
-        };
-      }
     };
     const role = getPromptValue("role-polish");
     const scene = getPromptValue("scene-polish");
     const tool = getPromptValue("tool-polish");
     const storyboard = getPromptValue("storyboard-polish");
-    let apiConfig = {};
     let systemPrompt = "";
     let userPrompt = "";
     if (type == "role") {
@@ -120,8 +105,7 @@ export default router.post(
       const chapterRange = Array.isArray(data?.chapterRange) ? data.chapterRange : [data?.chapterRange];
       const novelData = (await u.db("t_novel").whereIn("chapterIndex", chapterRange).select("*")) as NovelChapter[];
       const results: string = mergeNovelText(novelData);
-      systemPrompt = role.prompt;
+      systemPrompt = role;
-      apiConfig = role.apiData;
       userPrompt = `
       请根据以下参数生成角色标准四视图提示词：
   
@@ -144,8 +128,7 @@ export default router.post(
       const chapterRange = Array.isArray(data?.chapterRange) ? data.chapterRange : [data?.chapterRange];
       const novelData = (await u.db("t_novel").whereIn("chapterIndex", chapterRange).select("*")) as NovelChapter[];
       const results: string = mergeNovelText(novelData);
-      systemPrompt = scene.prompt;
+      systemPrompt = scene;
-      apiConfig = scene.apiData;
       userPrompt = `
       请根据以下参数生成场景图提示词：
   
@@ -168,8 +151,7 @@ export default router.post(
       const chapterRange = Array.isArray(data?.chapterRange) ? data.chapterRange : [data?.chapterRange];
       const novelData = (await u.db("t_novel").whereIn("chapterIndex", chapterRange).select("*")) as NovelChapter[];
       const results: string = mergeNovelText(novelData);
-      systemPrompt = tool.prompt;
+      systemPrompt = tool;
-      apiConfig = tool.apiData;
       userPrompt = `
       请根据以下参数生成道具图提示词：
   
@@ -188,8 +170,7 @@ export default router.post(
       `;
     }
     if (type == "storyboard") {
-      systemPrompt = storyboard.prompt;
+      systemPrompt = storyboard;
-      apiConfig = storyboard.apiData;
       userPrompt = `
       请根据以下参数生成分镜图提示词：
   
@@ -207,7 +188,6 @@ export default router.post(
       `;
     }
     async function generatePrompt() {
-      apiConfig = {};
       const result = await u.ai.text.invoke(
         {
           messages: [
@@ -224,9 +204,7 @@ export default router.post(
             prompt: zod.string().describe("提示词"),
           },
         },
-        {
+        apiConfigData,
-          ...apiConfig,
-        },
       );
       // const result = await model.invoke({
       //   messages: [
@@ -256,7 +234,6 @@ export default router.post(
 
       res.status(200).send(success({ prompt: prompt, assetsId }));
     } catch (e: any) {
-      console.log("%c Line:235 🥚 e", "background:#33a5ff", e);
       return res.status(500).send(error(e?.data?.error?.message ?? e?.message ?? "生成失败"));
     }
   },

src/routes/other/testAI.ts

@@ -13,12 +13,12 @@ export default router.post(
     modelName: z.string(),
     apiKey: z.string(),
     baseURL: z.string().optional(),
+    manufacturer: z.string(),
   }),
   async (req, res) => {
-    const { modelName, apiKey, baseURL } = req.body;
+    const { modelName, apiKey, baseURL, manufacturer } = req.body;
 
     const getWeatherTool = tool({
-      // strict: true,
       description: "Get the weather in a location",
       inputSchema: z.object({
         location: z.string().describe("The location to get the weather for"),
@@ -43,6 +43,7 @@ export default router.post(
           model: modelName,
           apiKey,
           baseURL,
+          manufacturer,
         },
       );
       res.status(200).send(success(reply));

src/routes/other/testImage.ts

@@ -17,13 +17,21 @@ export default router.post(
   async (req, res) => {
     const { modelName, apiKey, baseURL, manufacturer } = req.body;
     try {
-      const image = await u.ai.image({
+      const image = await u.ai.image(
-        prompt:
+        {
-          "一张16:9比例的图片，完美等分为2x2四宫格布局，各区域无缝衔接：\n左上宫格：一只可爱的猫，毛发蓬松，眼睛明亮，姿态俏皮\n右上宫格：一只友善的狗，金毛犬，表情愉悦，摇着尾巴\n左下宫格：一头健壮的牛，田园背景，目光温和，皮毛光泽\n右下宫格：一匹骏马，姿态优雅，鬃毛飘逸，肌肉健美\n风格要求：四个宫格风格统一，色彩鲜艳饱和，高清画质，细节清晰锐利，专业插画风格，线条干净，统一的左上方光源，柔和阴影，和谐配色，卡通/半写实风格，宫格间用白色或浅灰细线分隔",
+          prompt:
-        imageBase64: [],
+            "一张16:9比例的图片，完美等分为2x2四宫格布局，各区域无缝衔接：\n左上宫格：一只可爱的猫，毛发蓬松，眼睛明亮，姿态俏皮\n右上宫格：一只友善的狗，金毛犬，表情愉悦，摇着尾巴\n左下宫格：一头健壮的牛，田园背景，目光温和，皮毛光泽\n右下宫格：一匹骏马，姿态优雅，鬃毛飘逸，肌肉健美\n风格要求：四个宫格风格统一，色彩鲜艳饱和，高清画质，细节清晰锐利，专业插画风格，线条干净，统一的左上方光源，柔和阴影，和谐配色，卡通/半写实风格，宫格间用白色或浅灰细线分隔",
-        aspectRatio: "16:9",
+          imageBase64: [],
-        size: "1K",
+          aspectRatio: "16:9",
-      });
+          size: "1K",
+        },
+        {
+          model: modelName,
+          apiKey,
+          baseURL,
+          manufacturer,
+        },
+      );
       res.status(200).send(success(image));
     } catch (err) {
       const msg = u.error(err).message;

src/routes/other/testVideo.ts

@@ -12,20 +12,28 @@ export default router.post(
     modelName: z.string().optional(),
     apiKey: z.string(),
     baseURL: z.string().optional(),
-    manufacturer: z.enum(["runninghub", "volcengine", "apimart", "gemini", "openAi"]),
+    manufacturer: z.string(),
   }),
   async (req, res) => {
     const { modelName, apiKey, baseURL, manufacturer } = req.body;
     try {
-      const videoPath = await u.ai.video({
+      const videoPath = await u.ai.video(
-        imageBase64: [],
+        {
-        savePath: "test.mp4",
+          imageBase64: [],
-        prompt: "stickman Dances",
+          savePath: "test.mp4",
-        duration: 4,
+          prompt: "stickman Dances",
-        resolution: "720p",
+          duration: 4,
-        aspectRatio: "16:9",
+          resolution: "720p",
-        audio: false,
+          aspectRatio: "16:9",
-      });
+          audio: false,
+        },
+        {
+          model: modelName,
+          apiKey,
+          baseURL,
+          manufacturer,
+        },
+      );
       const url = await u.oss.getFileUrl(videoPath);
       res.status(200).send(success(url));
     } catch (err: any) {

src/routes/setting/addModel.ts

@@ -8,23 +8,23 @@ const router = express.Router();
 export default router.post(
   "/",
   validateFields({
-    type: z.string(),
+    type: z.enum(["text", "video", "image"]),
-    name: z.string(),
     model: z.string(),
     baseUrl: z.string(),
     apiKey: z.string(),
+    modelType: z.string(),
     manufacturer: z.string(),
   }),
   async (req, res) => {
-    const { type, name, model, baseUrl, apiKey, manufacturer } = req.body;
+    const { type, model, baseUrl, apiKey, manufacturer, modelType } = req.body;
 
     await u.db("t_config").insert({
       type,
-      name,
       model,
       baseUrl,
       apiKey,
       manufacturer,
+      modelType,
       createTime: Date.now(),
       userId: 1,
     });

src/routes/setting/configurationModel.ts

@@ -8,20 +8,13 @@ const router = express.Router();
 export default router.post(
   "/",
   validateFields({
-    id: z.number().optional(),
+    id: z.number(),
-    promptsId: z.number(),
     configId: z.number(),
   }),
   async (req, res) => {
-    const { id, promptsId, configId } = req.body;
+    const { id, configId } = req.body;
     if (id) {
       await u.db("t_aiModelMap").where("id", id).update({
-        promptsId,
-        configId,
-      });
-    } else {
-      await u.db("t_aiModelMap").insert({
-        promptsId,
         configId,
       });
     }

src/routes/setting/getAiModelMap.ts

@@ -1,13 +1,13 @@
 import express from "express";
 import u from "@/utils";
 import { success } from "@/lib/responseFormat";
+
 const router = express.Router();
 
 export default router.post("/", async (req, res) => {
   const configData = await u
-    .db("t_prompts")
+    .db("t_aiModelMap")
-    .leftJoin("t_aiModelMap", "t_prompts.id", "t_aiModelMap.promptsId")
+    .leftJoin("t_config", "t_aiModelMap.configId", "t_config.id")
-    .leftJoin("t_config", "t_config.id", "t_aiModelMap.configId")
+    .select("t_aiModelMap.name", "t_config.model", "t_aiModelMap.id");
-    .select("t_prompts.id as promptsId", "t_prompts.code", "t_prompts.name", "t_config.model", "t_aiModelMap.id");
   res.status(200).send(success(configData));
 });

src/routes/setting/updeteModel.ts

@@ -9,23 +9,23 @@ export default router.post(
   "/",
   validateFields({
     id: z.number(),
-    type: z.string(),
+    type: z.enum(["text", "video", "image"]),
-    name: z.string(),
     model: z.string(),
     baseUrl: z.string(),
+    modelType: z.string(),
     apiKey: z.string(),
     manufacturer: z.string(),
   }),
   async (req, res) => {
-    const { id, type, name, model, baseUrl, apiKey, manufacturer } = req.body;
+    const { id, type, model, baseUrl, apiKey, manufacturer, modelType } = req.body;
 
     await u.db("t_config").where("id", id).update({
       type,
-      name,
       model,
       baseUrl,
       apiKey,
       manufacturer,
+      modelType,
     });
     res.status(200).send(success("编辑成功"));
   },

src/routes/storyboard/batchSuperScoreImage.ts

@@ -17,19 +17,19 @@ async function urlToBase64(imageUrl: string): Promise<string> {
 }
 
 // 超分并保存到 oss
-async function superResolutionAndSave(
+async function superResolutionAndSave(src: string, projectId: number, videoRatio: string): Promise<{ ossPath: string; base64: string }> {
-  src: string,
+  const apiConfig = await u.getPromptAi("storyboardImage");
-  projectId: number,
+  const contentStr = await u.ai.image(
-  videoRatio: string,
+    {
-): Promise<{ ossPath: string; base64: string }> {
+      aspectRatio: videoRatio,
-  const contentStr = await u.ai.image({
+      size: "1K",
-    aspectRatio: videoRatio,
+      resType: "b64",
-    size: "1K",
+      systemPrompt: "你的核心任务是将所给的图片超分到 1K ，不改变图片任何内容，仅改变分辨率",
-    resType: "b64",
+      prompt: "你的核心任务是将所给的图片超分到 1K ，不改变图片任何内容，仅改变分辨率",
-    systemPrompt: "你的核心任务是将所给的图片超分到 1K ，不改变图片任何内容，仅改变分辨率",
+      imageBase64: [await urlToBase64(src)],
-    prompt: "你的核心任务是将所给的图片超分到 1K ，不改变图片任何内容，仅改变分辨率",
+    },
-    imageBase64: [await urlToBase64(src)],
+    apiConfig,
-  });
+  );
   const match = contentStr.match(/base64,([A-Za-z0-9+/=]+)/);
   const base64Str = match ? match[1] : contentStr;
   const buffer = Buffer.from(base64Str, "base64");
@@ -50,9 +50,9 @@ export default router.post(
             id: z.string(),
             prompt: z.string().optional(),
             src: z.string(),
-          })
+          }),
         ),
-      })
+      }),
     ),
   }),
   async (req, res) => {
@@ -63,9 +63,7 @@ export default router.post(
     if (!projectData) return res.status(500).send(error("项目不存在"));
 
     // 遍历处理每个分镜段
-    const processSegment = async (
+    const processSegment = async (segment: { cells: { id: string; src: string }[] }) => {
-      segment: { cells: { id: string; src: string }[] }
-    ) => {
       // 超分所有 cell
       const cellsWithSuperscore = await Promise.all(
         segment.cells.map(async (cell) => {
@@ -76,9 +74,9 @@ export default router.post(
             scriptId,
             filePath: ossPath, // oss 路径（未签名）
             src: cell.src,
-            type: "分镜"
+            type: "分镜",
           };
-        })
+        }),
       );
       return cellsWithSuperscore;
     };
@@ -92,9 +90,9 @@ export default router.post(
         (item.value as any[]).map(async (cell) => ({
           ...cell,
           filePath: await u.oss.getFileUrl(cell.filePath ?? ""),
-        }))
+        })),
-      )
+      ),
     );
     res.status(200).send(success(flatList));
-  }
+  },
 );

src/routes/storyboard/generateVideoPrompt.ts

@@ -4,6 +4,7 @@ import { error, success } from "@/lib/responseFormat";
 import { validateFields } from "@/middleware/middleware";
 import { z } from "zod";
 import path from "path";
+import axios from "axios";
 
 const router = express.Router();
 
@@ -103,7 +104,12 @@ const prompt = `
 现在请根据我提供的分镜内容，严格按照以上规则输出 Motion Prompt JSON 对象。
 
 `;
-
+async function urlToBase64(imageUrl: string): Promise<string> {
+  const response = await axios.get(imageUrl, { responseType: "arraybuffer" });
+  const contentType = response.headers["content-type"] || "image/png";
+  const base64 = Buffer.from(response.data, "binary").toString("base64");
+  return `data:${contentType};base64,${base64}`;
+}
 // 生成单个分镜提示
 async function generateSingleVideoPrompt({
   scriptText,
@@ -114,19 +120,6 @@ async function generateSingleVideoPrompt({
   storyboardPrompt: string;
   ossPath: string;
 }): Promise<{ content: string; time: number; name: string }> {
-  let rootDir: string;
-  if (typeof process.versions?.electron !== "undefined") {
-    const { app } = require("electron");
-    const userDataDir: string = app.getPath("userData");
-    rootDir = path.join(userDataDir, "uploads");
-  } else {
-    rootDir = path.join(process.cwd(), "uploads");
-  }
-
-  let imagePath = ossPath;
-  if (ossPath.includes("http")) {
-    imagePath = new URL(ossPath).pathname;
-  }
   const messages: any[] = [
     {
       role: "system",
@@ -140,24 +133,27 @@ async function generateSingleVideoPrompt({
           text: `剧本内容:${scriptText}\n分镜提示词:${storyboardPrompt}`,
         },
         {
-          type: "local",
+          type: "image",
-          path: path.join(rootDir, imagePath),
+          image: await urlToBase64(ossPath),
         },
       ],
     },
   ];
 
   try {
-    const result = await u.ai.text.invoke({
+    const apiConfig = await u.getPromptAi("videoPrompt");
-      messages,
-      output: {
-        time: z.number().describe("时长,镜头时长 1-15"),
-        content: z.string().describe("提示词内容"),
-        name: z.string().describe("分镜名称"),
-      },
-    });
-    console.log("%c Line:156 🍩 result", "background:#33a5ff", result);
 
+    const result = await u.ai.text.invoke(
+      {
+        messages,
+        output: {
+          time: z.number().describe("时长,镜头时长 1-15"),
+          content: z.string().describe("提示词内容"),
+          name: z.string().describe("分镜名称"),
+        },
+      },
+      apiConfig,
+    );
     if (!result) {
       console.error("AI 返回结果为空:", result);
       throw new Error("AI 返回结果为空");

src/routes/video/addVideo.ts

@@ -42,5 +42,5 @@ export default router.post(
     });
 
     res.status(200).send(success({ message: "新增视频成功" }));
-  }
+  },
 );

src/routes/video/addVideoConfig.ts

@@ -1,6 +1,6 @@
 import express from "express";
 import u from "@/utils";
-import { success } from "@/lib/responseFormat";
+import { error, success } from "@/lib/responseFormat";
 import { validateFields } from "@/middleware/middleware";
 import { z } from "zod";
 const router = express.Router();
@@ -20,8 +20,8 @@ export default router.post(
   validateFields({
     scriptId: z.number(),
     projectId: z.number(),
-    manufacturer: z.string(),
+    configId: z.number(),
-    mode: z.enum(["startEnd", "multi", "single"]),
+    mode: z.enum(["startEnd", "multi", "single",'text','']),
     startFrame: imageItemSchema.optional(),
     endFrame: imageItemSchema.optional(),
     images: z
@@ -38,19 +38,21 @@ export default router.post(
     prompt: z.string().optional(),
   }),
   async (req, res) => {
-    const { scriptId, projectId, manufacturer, mode, startFrame, endFrame, images, resolution, duration, prompt } = req.body;
+    const { scriptId, projectId, configId, mode, startFrame, endFrame, images, resolution, duration, prompt } = req.body;
 
     // 生成新ID
     const maxIdResult: any = await u.db("t_videoConfig").max("id as maxId").first();
     const newId = (maxIdResult?.maxId || 0) + 1;
     const now = Date.now();
-
+    const configData = await u.db("t_config").where("id", configId).first();
+    if (!configData) return res.status(500).send(error("不存在的模型"));
     // 插入数据
     await u.db("t_videoConfig").insert({
       id: newId,
       scriptId,
       projectId,
-      manufacturer,
+      manufacturer: configData.manufacturer,
+      aiConfigId: configId,
       mode,
       startFrame: startFrame ? JSON.stringify(startFrame) : null,
       endFrame: endFrame ? JSON.stringify(endFrame) : null,
@@ -70,7 +72,9 @@ export default router.post(
           id: newId,
           scriptId,
           projectId,
-          manufacturer,
+          manufacturer: configData.manufacturer,
+          aiConfigId: configId,
+          model: configData.model,
           mode,
           startFrame,
           endFrame,

src/routes/video/generatePrompt.ts

@@ -1,6 +1,6 @@
 import express from "express";
 import u from "@/utils";
-import { success } from "@/lib/responseFormat";
+import { error, success } from "@/lib/responseFormat";
 import { validateFields } from "@/middleware/middleware";
 import { z } from "zod";
 
@@ -8,47 +8,26 @@ const router = express.Router();
 
 type GenerateMode = "startEnd" | "multi" | "single";
 
-const getSystemPrompt = async (mode: GenerateMode): Promise<{ prompt: string; apiConfig: Object }> => {
+const getSystemPrompt = async (mode: GenerateMode) => {
   const promptsList = await u.db("t_prompts").where("code", "in", ["video-startEnd", "video-multi", "video-single", "video-main"]);
 
-  const promptAiConfig = await u.getPromptAi(promptsList.map((i) => i.id) as number[]);
-
   const errPrompts = "不论用户说什么，请直接输出AI配置异常";
   const getPromptValue = (code: string) => {
     const item = promptsList.find((p) => p.code === code);
-    const subData = promptAiConfig.find((i) => i?.promptsId == item?.id);
+    return item?.customValue ?? item?.defaultValue ?? errPrompts;
-    const returnData = {
-      prompt: item?.customValue ?? item?.defaultValue ?? errPrompts,
-      apiConfig: {},
-    };
-    if (subData) {
-      returnData.apiConfig = { ...subData };
-      return returnData;
-    } else {
-      return returnData;
-    }
   };
   const startEnd = getPromptValue("video-startEnd");
   const multi = getPromptValue("video-multi");
   const single = getPromptValue("video-single");
   const main = getPromptValue("video-main");
 
-  const modeDescriptions: Record<
+  const modeDescriptions = {
-    GenerateMode,
-    {
-      prompt: string;
-      apiConfig: Object;
-    }
-  > = {
     startEnd: startEnd,
     multi: multi,
     single: single,
   };
   const modeData = modeDescriptions[mode];
-  return {
+  return `${main}\n\n${modeData}`;
-    prompt: `${main}\n\n${modeData.prompt}`,
-    apiConfig: modeData.apiConfig,
-  };
 };
 
 const getModeDescription = (mode: GenerateMode): string => {
@@ -82,16 +61,18 @@ export default router.post(
     const shotCount = images.length;
     const avgDuration = (parseFloat(duration) / shotCount).toFixed(1);
     const promptConfig = await getSystemPrompt(mode);
-    const result = await u.ai.text.invoke(
+    const promptAiConfig = await u.getPromptAi("videoPrompt");
-      {
+    try {
-        messages: [
+      const result = await u.ai.text.invoke(
-          {
+        {
-            role: "system",
+          messages: [
-            content: promptConfig.prompt,
+            {
-          },
+              role: "system",
-          {
+              content: promptConfig,
-            role: "user",
+            },
-            content: `Mode: ${getModeDescription(mode)}
+            {
+              role: "user",
+              content: `Mode: ${getModeDescription(mode)}
 
 Reference Images:
 ${imagePrompts}
@@ -105,12 +86,15 @@ Parameters:
 - Average Duration: ${avgDuration}s per shot
 
 Generate storyboard prompts:`,
-          },
+            },
-        ],
+          ],
-      },
+        },
-      promptConfig.apiConfig,
+        promptAiConfig,
-    );
+      );
 
-    res.status(200).send(success(result.text));
+      res.status(200).send(success(result.text));
+    } catch (e) {
+      return res.status(500).send(error(u.error(e).message));
+    }
   },
 );

src/routes/video/generateVideo.ts

@@ -4,6 +4,7 @@ import { z } from "zod";
 import { v4 as uuidv4 } from "uuid";
 import { error, success } from "@/lib/responseFormat";
 import { validateFields } from "@/middleware/middleware";
+import { t_config } from "@/types/database";
 
 const router = express.Router();
 
@@ -13,35 +14,52 @@ export default router.post(
   validateFields({
     projectId: z.number(),
     scriptId: z.number(),
-    configId: z.number().optional(), // 关联的视频配置ID
+    configId: z.number().optional(), // 关联的视频配 置ID
     type: z.string().optional(),
     resolution: z.string(),
+    aiConfigId: z.number(),
     filePath: z.array(z.string()),
     duration: z.number(),
     prompt: z.string(),
   }),
   async (req, res) => {
-    const { type, scriptId, projectId, configId, resolution, filePath, duration, prompt } = req.body;
+    const { type, scriptId, projectId, configId, aiConfigId, resolution, filePath, duration, prompt } = req.body;
 
-    // 参数校验
+    // // 参数校验
-    if (type === "volcengine") {
+    // if (type === "volcengine") {
-      if (duration < 4 || duration > 12) {
+    //   if (duration < 4 || duration > 12) {
-        return res.status(400).send(error("视频时长需在4-12秒之间"));
+    //     return res.status(400).send(error("视频时长需在4-12秒之间"));
-      }
+    //   }
-      if (!["480p", "720p", "1080p"].includes(resolution)) {
+    //   if (!["480p", "720p", "1080p"].includes(resolution)) {
-        return res.status(400).send(error("视频分辨率不正确"));
+    //     return res.status(400).send(error("视频分辨率不正确"));
-      }
+    //   }
+    // }
+
+    // if (type === "runninghub") {
+    //   if (duration !== 10 && duration !== 15) {
+    //     return res.status(400).send(error("视频时长只能是10秒或15秒"));
+    //   }
+    //   if (resolution !== "9:16" && resolution !== "16:9") {
+    //     return res.status(400).send(error("视频分辨率不正确"));
+    //   }
+    // }
+    const configData = await u.db("t_videoConfig").where("id", configId).first();
+    if (!configData) {
+      return res.status(500).send(error("视频配置不存在"));
     }
 
-    if (type === "runninghub") {
+    // 优先使用视频配置中的AI配置ID查询,查不到再使用传入的aiConfigId
-      if (duration !== 10 && duration !== 15) {
+    let aiConfigData = null;
-        return res.status(400).send(error("视频时长只能是10秒或15秒"));
+    if (configData.aiConfigId) {
-      }
+      aiConfigData = await u.db("t_config").where("id", configData.aiConfigId).first();
-      if (resolution !== "9:16" && resolution !== "16:9") {
+    }
-        return res.status(400).send(error("视频分辨率不正确"));
+    if (!aiConfigData) {
-      }
+      aiConfigData = await u.db("t_config").where("id", aiConfigId).first();
     }
 
+    if (!aiConfigData) {
+      return res.status(500).send(error("模型配置不存在"));
+    }
     // 过滤掉空值
     let fileUrl = filePath.filter((p: string) => p && p.trim() !== "");
 
@@ -103,7 +121,7 @@ export default router.post(
     res.status(200).send(success({ id: videoId, configId: configId || null }));
 
     // 异步生成视频
-    generateVideoAsync(videoId, projectId, fileUrl, savePath, prompt, duration, resolution, type);
+    generateVideoAsync(videoId, projectId, fileUrl, savePath, prompt, duration, resolution, aiConfigData);
   },
 );
 
@@ -116,7 +134,7 @@ async function generateVideoAsync(
   prompt: string,
   duration: number,
   resolution: string,
-  type?: string,
+  aiConfigData: t_config,
 ) {
   try {
     const projectData = await u.db("t_project").where("id", projectId).select("artStyle").first();
@@ -149,14 +167,22 @@ ${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.video({
+    const videoPath = await u.ai.video(
-      imageBase64,
+      {
-      savePath,
+        imageBase64,
-      prompt: inputPrompt,
+        savePath,
-      duration: duration as any,
+        prompt: inputPrompt,
-      aspectRatio: resolution as any,
+        duration: duration as any,
-      resolution: resolution as any,
+        aspectRatio: resolution as any,
-    });
+        resolution: resolution as any,
+      },
+      {
+        baseURL: aiConfigData?.baseUrl!,
+        model: aiConfigData?.model!,
+        apiKey: aiConfigData?.apiKey!,
+        manufacturer: aiConfigData?.manufacturer!,
+      },
+    );
 
     if (videoPath) {
       // 生成成功，更新状态为 1

src/routes/video/getManufacturer.ts

@@ -14,8 +14,8 @@ export default router.post(
   async (req, res) => {
     const { userId } = req.body;
 
-    const data = await u.db("t_config").where("userId", userId).select("manufacturer", "model");
+    const data = await u.db("t_config").where("type", "video").where("userId", userId).select("manufacturer", "model", "id");
 
     res.status(200).send(success(data));
-  }
+  },
 );

src/routes/video/getVideoConfigs.ts

@@ -15,16 +15,20 @@ export default router.post(
     const { scriptId } = req.body;
 
     // 查询该脚本下的所有视频配置
-    const configs = await u.db("t_videoConfig")
+    const configs = await u
+      .db("t_videoConfig")
+      .leftJoin("t_config", "t_config.id", "t_videoConfig.aiConfigId")
       .where({ scriptId })
-      .orderBy("createTime", "desc");
+      .orderBy("createTime", "desc")
-
+      .select("t_videoConfig.*", "t_config.manufacturer as manufacturer", "t_config.model");
     // 解析 JSON 字段
     const result = configs.map((config: any) => ({
       id: config.id,
       scriptId: config.scriptId,
       projectId: config.projectId,
+      aiConfigId: config.aiConfigId,
       manufacturer: config.manufacturer,
+      model: config.model,
       mode: config.mode,
       startFrame: config.startFrame ? JSON.parse(config.startFrame) : null,
       endFrame: config.endFrame ? JSON.parse(config.endFrame) : null,

src/types/database.d.ts

@@ -1,10 +1,11 @@
-// @db-hash e1460b0ace03f6aaed458653a32b6ffb
+// @db-hash 4cd44aef6bb6ffb02c4619525966496d
 //该文件由脚本自动生成，请勿手动修改
 
 export interface t_aiModelMap {
   'configId'?: number | null;
   'id'?: number;
-  'promptsId'?: number | null;
+  'key'?: string | null;
+  'name'?: string | null;
 }
 export interface t_assets {
   'duration'?: string | null;
@@ -37,7 +38,7 @@ export interface t_config {
   'id'?: number;
   'manufacturer'?: string | null;
   'model'?: string | null;
-  'name'?: string | null;
+  'modelType'?: string | null;
   'type'?: string | null;
   'userId'?: number | null;
 }
@@ -135,6 +136,7 @@ export interface t_video {
   'time'?: number | null;
 }
 export interface t_videoConfig {
+  'aiConfigId'?: number | null;
   'createTime'?: number | null;
   'duration'?: number | null;
   'endFrame'?: string | null;

src/utils/ai/image/index.ts

@@ -28,13 +28,16 @@ const modelInstance = {
   other,
 } as const;
 
-export default async (input: ImageConfig, config?: AIConfig) => {
+export default async (input: ImageConfig, config: AIConfig) => {
-  const sqlTextModelConfig = await u.getConfig("image");
+  const { model, apiKey, baseURL, manufacturer } = { ...config };
-  const { model, apiKey, baseURL, manufacturer } = { ...sqlTextModelConfig, ...config };
+  if (!config || !config?.model || !config?.apiKey || !config?.manufacturer) throw new Error("请检查模型配置是否正确");
+
   const manufacturerFn = modelInstance[manufacturer as keyof typeof modelInstance];
   if (!manufacturerFn) if (!manufacturerFn) throw new Error("不支持的图片厂商");
-  const owned = modelList.find((m) => m.model === model);
+  if (manufacturer !== "other") {
-  if (!owned) throw new Error("不支持的模型");
+    const owned = modelList.find((m) => m.model === model);
+    if (!owned) throw new Error("不支持的模型");
+  }
 
   // 补充图片的 base64 内容类型字符串
   if (input.imageBase64 && input.imageBase64.length > 0) {

src/utils/ai/image/owned/gemini.ts

@@ -3,14 +3,13 @@ import { createGoogleGenerativeAI } from "@ai-sdk/google";
 import { generateText } from "ai";
 
 export default async (input: ImageConfig, config: AIConfig): Promise<string> => {
-  console.log("%c Line:6 🌰 config", "background:#ffdd4d", config);
   if (!config.model) throw new Error("缺少Model名称");
   if (!config.apiKey) throw new Error("缺少API Key");
   if (!input.prompt) throw new Error("缺少提示词");
 
   const google = createGoogleGenerativeAI({
     apiKey: config.apiKey,
-    baseURL: config.baseURL,
+    baseURL: config?.baseURL ?? "https://generativelanguage.googleapis.com/v1beta",
   });
 
   // 构建完整的提示词

src/utils/ai/image/owned/other.ts

@@ -1,5 +1,5 @@
 import "../type";
-import { generateImage, generateText } from "ai";
+import { generateImage, generateText, ModelMessage } from "ai";
 import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
 
 export default async (input: ImageConfig, config: AIConfig): Promise<string> => {
@@ -27,9 +27,24 @@ export default async (input: ImageConfig, config: AIConfig): Promise<string> =>
   const fullPrompt = input.systemPrompt ? `${input.systemPrompt}\n\n${input.prompt}` : input.prompt;
   const model = config.model;
   if (model.includes("gemini") || model.includes("nano")) {
+    let promptData;
+    if (input.imageBase64 && input.imageBase64.length) {
+      promptData = [{ role: "system", content: fullPrompt + `请直接输出图片` }];
+      (promptData as ModelMessage[]).push({
+        role: "user",
+        content: input.imageBase64.map((i) => ({
+          type: "image",
+          image: i,
+        })),
+      });
+    } else {
+      promptData = fullPrompt + `请直接输出图片`;
+    }
+    console.log("%c Line:31 🍅 promptData", "background:#2eafb0", promptData);
+
     const result = await generateText({
       model: otherProvider.languageModel(model),
-      prompt: fullPrompt + `请直接输出图片`,
+      prompt: promptData as string | ModelMessage[],
       providerOptions: {
         google: {
           imageConfig: {

src/utils/ai/image/owned/vidu.ts

@@ -20,7 +20,6 @@ function template(replaceObj: Record<string, any>, url: string) {
 export default async (input: ImageConfig, config: AIConfig): Promise<string> => {
   if (!config.model) throw new Error("缺少Model名称");
   if (!config.apiKey) throw new Error("缺少API Key");
-
   const apiKey = "Token " + config.apiKey.replace(/Token\s+/g, "").trim();
   const viduq2Ratio = ["16:9", "9:16", "1:1", "3:4", "4:3", "21:9", "2:3", "3:2"];
   const viduq1Ratio = ["16:9", "9:16", "1:1", "3:4", "4:3"];
@@ -60,7 +59,8 @@ export default async (input: ImageConfig, config: AIConfig): Promise<string> =>
     ...(images.length && { images: images }),
   };
 
-  const urlObj = getApiUrl(config.baseURL!);
+  const urlObj = getApiUrl(config.baseURL! ?? "https://api.vidu.cn/ent/v2/reference2image|https://api.vidu.cn/ent/v2/tasks/{id}/creations");
+
   try {
     const { data } = await axios.post(urlObj.requestUrl, body, { headers: { Authorization: apiKey } });
 
@@ -69,17 +69,13 @@ export default async (input: ImageConfig, config: AIConfig): Promise<string> =>
     return await pollTask(async () => {
       const { data: queryData } = await axios.get(queryUrl, { headers: { Authorization: apiKey } });
 
-      if (queryData.state !== 0) {
+      const { state, err_code, creations } = queryData || {};
-        return { completed: false, error: queryData.message || "查询任务失败" };
-      }
-
-      const { state, err_code, creations } = queryData.data || {};
 
       if (state === "failed") {
         return { completed: false, error: err_code || "图片生成失败" };
       }
 
-      if (state === "succeed") {
+      if (state === "success") {
         return { completed: true, url: creations?.[0]?.url };
       }
 

src/utils/ai/text/index.ts

@@ -6,7 +6,6 @@ import { parse } from "best-effort-json-parser";
 import modelList from "./modelList";
 import { z } from "zod";
 import { OpenAIProvider } from "@ai-sdk/openai";
-
 interface AIInput<T extends Record<string, z.ZodTypeAny> | undefined = undefined> {
   system?: string;
   tools?: Record<string, Tool>;
@@ -23,10 +22,9 @@ interface AIConfig {
   manufacturer?: string;
 }
 
-const buildOptions = async (input: AIInput<any>, config: AIConfig) => {
+const buildOptions = async (input: AIInput<any>, config: AIConfig = {}) => {
-  let sqlTextModelConfig = {};
+  if (!config || !config?.model || !config?.apiKey || !config?.baseURL || !config?.manufacturer) throw new Error("请检查模型配置是否正确");
-  if (!config || !config?.model || !config?.apiKey || !config?.baseURL) sqlTextModelConfig = await u.getConfig("text");
+  const { model, apiKey, baseURL, manufacturer } = { ...config };
-  const { model, apiKey, baseURL, manufacturer } = { ...(sqlTextModelConfig as Awaited<ReturnType<typeof u.getConfig>>), ...config };
   let owned;
   if (manufacturer == "other") {
     owned = modelList.find((m) => m.manufacturer === manufacturer);
@@ -39,7 +37,9 @@ const buildOptions = async (input: AIInput<any>, config: AIConfig) => {
 
   const maxStep = input.maxStep ?? (input.tools ? Object.keys(input.tools).length * 5 : undefined);
   const outputBuilders: Record<string, (schema: any) => any> = {
-    schema: (s) => Output.object({ schema: z.object(s) }),
+    schema: (s) => {
+      return Output.object({ schema: z.object(s) });
+    },
     object: () => {
       const jsonSchemaPrompt = `\n请按照以下 JSON Schema 格式返回结果:\n${JSON.stringify(
         z.toJSONSchema(z.object(input.output)),
@@ -52,16 +52,11 @@ const buildOptions = async (input: AIInput<any>, config: AIConfig) => {
   };
 
   const output = input.output ? (outputBuilders[owned.responseFormat]?.(input.output) ?? null) : null;
-  const modelFn = owned.manufacturer == "doubao" ? (modelInstance as OpenAIProvider).chat(model!) : modelInstance(model!);
+  const chatModelManufacturer = ["doubao", "other", "openai"];
+  const modelFn = chatModelManufacturer.includes(owned.manufacturer) ? (modelInstance as OpenAIProvider).chat(model!) : modelInstance(model!);
   return {
     config: {
-      model:
+      model: modelFn as LanguageModel,
-        process.env.NODE_ENV === "dev"
-          ? wrapLanguageModel({
-              model: modelFn as any,
-              middleware: devToolsMiddleware(),
-            })
-          : (modelFn as LanguageModel),
       ...(input.system && { system: input.system }),
       ...(input.prompt ? { prompt: input.prompt } : { messages: input.messages! }),
       ...(input.tools && owned.tool && { tools: input.tools }),
@@ -79,7 +74,7 @@ const ai = Object.create({}) as {
   stream(input: AIInput, config?: AIConfig): Promise<ReturnType<typeof streamText>>;
 };
 
-ai.invoke = async (input: AIInput<any>, config: AIConfig = {}) => {
+ai.invoke = async (input: AIInput<any>, config: AIConfig) => {
   const options = await buildOptions(input, config);
   const result = await generateText(options.config);
   if (options.responseFormat === "object" && input.output) {
@@ -95,7 +90,7 @@ ai.invoke = async (input: AIInput<any>, config: AIConfig = {}) => {
   return result;
 };
 
-ai.stream = async (input: AIInput, config: AIConfig = {}) => {
+ai.stream = async (input: AIInput, config: AIConfig) => {
   const options = await buildOptions(input, config);
   return streamText(options.config);
 };

src/utils/ai/text/modelList.ts

@@ -417,7 +417,7 @@ const modelList: Owned[] = [
     responseFormat: "schema",
     image: true,
     think: false,
-    instance: createOpenAICompatible,
+    instance: createOpenAI,
     tool: true,
   },
 ];

src/utils/ai/video/index.ts

@@ -22,8 +22,10 @@ const modelInstance = {
 } as const;
 
 export default async (input: VideoConfig, config?: AIConfig) => {
-  const sqlTextModelConfig = await u.getConfig("video");
+  console.log("%c Line:25 🥛 config", "background:#2eafb0", config);
-  const { model, apiKey, baseURL, manufacturer } = { ...sqlTextModelConfig, ...config };
+  const { model, apiKey, baseURL, manufacturer } = { ...config };
+  if (!config || !config?.model || !config?.apiKey) throw new Error("请检查模型配置是否正确");
+
   const manufacturerFn = modelInstance[manufacturer as keyof typeof modelInstance];
   if (!manufacturerFn) if (!manufacturerFn) throw new Error("不支持的视频厂商");
   const owned = modelList.find((m) => m.model === model);

src/utils/ai/video/owned/volcengine.ts

@@ -47,6 +47,7 @@ export default async (input: VideoConfig, config: AIConfig) => {
   });
 
   const taskId = createResponse.data.id;
+
   if (!taskId) throw new Error("视频任务创建失败");
 
   // 轮询任务状态

src/utils/ai/video/type.ts

@@ -12,4 +12,5 @@ interface AIConfig {
   model?: string;
   apiKey?: string;
   baseURL?: string;
+  manufacturer?: string;
 }

src/utils/editImage.ts

@@ -79,13 +79,18 @@ 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.image({
+  const apiConfig = await u.getPromptAi("editImage");
-    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,
+  const contentStr = await u.ai.image(
-    imageBase64: base64Images,
+    {
-    aspectRatio: "16:9",
+      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。",
-    size: "1K",
+      prompt: prompt,
-  });
+      imageBase64: base64Images,
+      aspectRatio: "16:9",
+      size: "1K",
+    },
+    apiConfig,
+  );
   const match = contentStr.match(/base64,([A-Za-z0-9+/=]+)/);
   const buffer = Buffer.from(match && match.length >= 1 ? match[1]! : contentStr, "base64");
   const filePath = `/${projectId}/storyboard/${uuid()}.jpg`;

src/utils/generateScript.ts

@@ -127,7 +127,7 @@ ${episodePrompt}
 ${novelData}`;
 
   const prompts = await u.db("t_prompts").where("code", "script").first();
-  const promptConfig = await u.getPromptAi(prompts?.id);
+  const promptConfig = await u.getPromptAi("generateScript");
   const mainPrompts = prompts?.customValue || prompts?.defaultValue || "不论用户说什么，请直接输出AI配置异常";
 
   const result = await u.ai.text.invoke(

src/utils/getPromptAi.ts

@@ -1,26 +1,19 @@
 import { db } from "./db";
 interface AiConfig {
-  model: string;
+  model?: string;
   apiKey: string;
-  baseUrl: string;
+  baseURL?: string;
   manufacturer: string;
-  promptsId: number;
 }
 
-export default async function getPromptAi(promptsId: number | undefined): Promise<AiConfig | {}>;
+export default async function getPromptAi(key: string): Promise<AiConfig | {}> {
-export default async function getPromptAi(promptsId: number[]): Promise<AiConfig[]>;
+  const aiConfigData = await db("t_aiModelMap")
-
-export default async function getPromptAi(promptsId: number | number[] | undefined): Promise<AiConfig | AiConfig[] | {}> {
-  if (!promptsId) return {};
-  const ids = Array.isArray(promptsId) ? promptsId.filter(Boolean) : [promptsId];
-  const mapList = await db("t_aiModelMap")
     .leftJoin("t_config", "t_config.id", "t_aiModelMap.configId")
-    .whereIn("t_aiModelMap.promptsId", ids)
+    .where("t_aiModelMap.key", key)
-    .select("t_config.model", "t_config.apiKey", "t_config.baseUrl", "t_config.manufacturer", "t_aiModelMap.promptsId");
+    .select("t_config.model", "t_config.apiKey", "t_config.baseUrl as baseURL", "t_config.manufacturer")
+    .first();
 
-  if (Array.isArray(promptsId)) {
+  if (aiConfigData) {
-    return mapList as AiConfig[];
+    return aiConfigData as AiConfig;
-  } else {
+  } else return {};
-    return mapList[0] ? (mapList[0] as AiConfig) : {};
-  }
 }