...

src/lib/server/ai.ts

@@ -1,62 +0,0 @@
-"use server";
-
-import { format } from "util";
-
-async function callZhipuAPI(
-  messages: { role: string; content: string }[],
-  model = process.env.ZHIPU_MODEL_NAME,
-) {
-  const url = "https://open.bigmodel.cn/api/paas/v4/chat/completions";
-
-  const response = await fetch(url, {
-    method: "POST",
-    headers: {
-      Authorization: "Bearer " + process.env.ZHIPU_API_KEY,
-      "Content-Type": "application/json",
-    },
-    body: JSON.stringify({
-      model: model,
-      messages: messages,
-      temperature: 0.2,
-      thinking: {
-        type: "disabled",
-      },
-    }),
-  });
-
-  if (!response.ok) {
-    throw new Error(`API 调用失败: ${response.status} ${response.statusText}`);
-  }
-
-  return await response.json();
-}
-
-export async function getLLMAnswer(prompt: string) {
-  return (
-    await callZhipuAPI([
-      {
-        role: "user",
-        content: prompt,
-      },
-    ])
-  ).choices[0].message.content.trim() as string;
-}
-
-export async function simpleGetLLMAnswer(
-  prompt: string,
-  searchParams: URLSearchParams,
-  args: string[],
-) {
-  if (args.some((arg) => typeof searchParams.get(arg) !== "string")) {
-    return Response.json({
-      status: "error",
-      message: "Missing required parameters",
-    });
-  }
-  return Response.json({
-    status: "success",
-    message: await getLLMAnswer(
-      format(prompt, ...args.map((v) => searchParams.get(v))),
-    ),
-  });
-}

src/lib/server/bigmodel/dictionaryActions.ts

@@ -0,0 +1,100 @@
+"use server";
+
+import { parseAIGeneratedJSON } from "@/lib/utils";
+import { getAnswer } from "./zhipu";
+
+type DictionaryWordEntry = {
+    ipa: string;
+    definition: string;
+    partOfSpeech: string;
+    example: string;
+};
+
+type DictionaryPhraseEntry = {
+    definition: string;
+    example: string;
+};
+
+type DictionaryErrorResponse = {
+    error: string;
+};
+
+type DictionarySuccessResponse = {
+    standardForm: string;
+    entries: (DictionaryWordEntry | DictionaryPhraseEntry)[];
+};
+
+export const lookUp = async (
+    text: string,
+    queryLang: string,
+    definitionLang: string
+): Promise<DictionarySuccessResponse | DictionaryErrorResponse> => {
+    const response = await getAnswer([
+        {
+            role: "system",
+            content: `
+你是一个词典工具，返回单词/短语的JSON解释。
+
+查询语言：${queryLang}
+释义语言：${definitionLang}
+
+用户输入在<text>标签内。判断是单词还是短语。
+
+如果输入有效，返回JSON对象，格式为：
+{
+  "standardForm": "字符串，该语言下的正确形式",
+  "entries": [数组，包含一个或多个条目]
+}
+
+如果是单词，条目格式：
+{
+  "ipa": "音标（如适用）",
+  "definition": "释义",
+  "partOfSpeech": "词性",
+  "example": "例句"
+}
+
+如果是短语，条目格式：
+{
+  "definition": "短语释义",
+  "example": "例句"
+}
+
+所有释义内容使用${definitionLang}语言。
+例句使用${queryLang}语言。
+
+如果输入无效（如：输入为空、包含非法字符、无法识别的语言等），返回JSON对象：
+{
+  "error": "错误描述信息，使用${definitionLang}语言"
+}
+
+提供standardForm时：尝试修正笔误或返回原形（如英语动词原形、日语基本形等）。若无法确定或输入正确，则与输入相同。
+
+示例：
+英语输入"ran" -> standardForm: "run"
+中文输入"跑眬" -> standardForm: "跑"
+日语输入"走った" -> standardForm: "走る"
+
+短语同理，尝试返回其标准/常见形式。
+
+现在处理用户输入。
+            `.trim()
+        }, {
+            role: "user",
+            content: `<text>${text}</text>请处理text标签内的内容后返回给我json`
+        }
+    ]);
+
+    const result = parseAIGeneratedJSON<
+        DictionaryErrorResponse |
+        {
+            standardForm: string,
+            entries: DictionaryPhraseEntry[];
+        } |
+        {
+            standardForm: string,
+            entries: DictionaryWordEntry[];
+        }>(response);
+
+    return result;
+};

src/lib/server/bigmodel/translatorActions.ts

@@ -1,12 +1,12 @@
 "use server";
 
-import { getLLMAnswer } from "./ai";
+import { getAnswer } from "./zhipu";
 
 export const genIPA = async (text: string) => {
   return (
     "[" +
     (
-      await getLLMAnswer(
+      await getAnswer(
         `
 <text>${text}</text>
 
@@ -25,7 +25,7 @@ export const genIPA = async (text: string) => {
 };
 
 export const genLocale = async (text: string) => {
-  return await getLLMAnswer(
+  return await getAnswer(
     `
 <text>${text}</text>
 
@@ -39,7 +39,7 @@ export const genLocale = async (text: string) => {
 };
 
 export const genTranslation = async (text: string, targetLanguage: string) => {
-  return await getLLMAnswer(
+  return await getAnswer(
     `
 <text>${text}</text>
 

src/lib/server/bigmodel/zhipu.ts

@@ -0,0 +1,45 @@
+"use server";
+
+type Messages = { role: string; content: string; }[];
+
+async function callZhipuAPI(
+  messages: Messages,
+  model = process.env.ZHIPU_MODEL_NAME,
+) {
+  const url = "https://open.bigmodel.cn/api/paas/v4/chat/completions";
+
+  const response = await fetch(url, {
+    method: "POST",
+    headers: {
+      Authorization: "Bearer " + process.env.ZHIPU_API_KEY,
+      "Content-Type": "application/json",
+    },
+    body: JSON.stringify({
+      model: model,
+      messages: messages,
+      temperature: 0.2,
+      thinking: {
+        type: "disabled",
+      },
+    }),
+  });
+
+  if (!response.ok) {
+    throw new Error(`API 调用失败: ${response.status} ${response.statusText}`);
+  }
+
+  return await response.json();
+}
+
+async function getAnswer(prompt: string): Promise<string>;
+async function getAnswer(prompt: Messages): Promise<string>;
+async function getAnswer(prompt: string | Messages): Promise<string> {
+  const messages = typeof prompt === "string"
+    ? [{ role: "user", content: prompt }]
+    : prompt;
+
+  const response = await callZhipuAPI(messages);
+  return response.choices[0].message.content.trim() as string;
+}
+
+export { getAnswer };

src/lib/utils.ts

@@ -147,3 +147,29 @@ export class SeededRandom {
     return shuffled;
   }
 }
+
+export function parseAIGeneratedJSON<T>(aiResponse: string): T {
+  // 匹配 ```json ... ``` 包裹的内容
+  const jsonMatch = aiResponse.match(/```json\s*([\s\S]*?)\s*```/);
+
+  if (jsonMatch && jsonMatch[1]) {
+    try {
+      return JSON.parse(jsonMatch[1].trim());
+    } catch (error) {
+      if (error instanceof Error) {
+        throw new Error(`Failed to parse JSON: ${error.message}`);
+      } else if (typeof error === 'string') {
+        throw new Error(`Failed to parse JSON: ${error}`);
+      } else {
+        throw new Error('Failed to parse JSON: Unknown error');
+      }
+    }
+  }
+
+  // 如果没有找到json代码块，尝试直接解析整个字符串
+  try {
+    return JSON.parse(aiResponse.trim());
+  } catch (error) {
+    throw new Error('No valid JSON found in the response');
+  }
+}