feat(app): lint & beautify

ui/app/settings/page.tsx

@@ -187,16 +187,13 @@ const Page = () => {
         [key]: value,
       } as SettingsType;
 
-      const response = await fetch(
-        `/api/config`,
-        {
-          method: 'POST',
-          headers: {
-            'Content-Type': 'application/json',
-          },
-          body: JSON.stringify(updatedConfig),
+      const response = await fetch(`/api/config`, {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
         },
-      );
+        body: JSON.stringify(updatedConfig),
+      });
 
       if (!response.ok) {
         throw new Error('Failed to update config');

ui/lib/providers/openai.ts

@@ -1,6 +1,6 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai'
-import { getOpenaiApiKey } from '../config'
-import { ChatModelProvider, EmbeddingModelProvider } from '.'
+import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
+import { getOpenaiApiKey } from '../config';
+import { ChatModel, EmbeddingModel } from '.';
 
 const openaiChatModels: Record<string, string>[] = [
   {
@@ -22,67 +22,67 @@ const openaiChatModels: Record<string, string>[] = [
   {
     displayName: 'GPT-4 omni mini',
     key: 'gpt-4o-mini',
-  }
-]
+  },
+];
 
 const openaiEmbeddingModels: Record<string, string>[] = [
-    {
-        displayName: 'Text Embedding 3 Small',
-        key: 'text-embedding-3-small',
-    }, 
-    {
-        displayName: 'Text Embedding 3 Large',
-        key: 'text-embedding-3-large',
-    }
-]
+  {
+    displayName: 'Text Embedding 3 Small',
+    key: 'text-embedding-3-small',
+  },
+  {
+    displayName: 'Text Embedding 3 Large',
+    key: 'text-embedding-3-large',
+  },
+];
 
 export const loadOpenAIChatModels = async () => {
-    const openaiApiKey = getOpenaiApiKey()
+  const openaiApiKey = getOpenaiApiKey();
 
-    if (!openaiApiKey) return {}
+  if (!openaiApiKey) return {};
 
-    try {
-        const chatModels: Record<string, ChatModelProvider> = {}
+  try {
+    const chatModels: Record<string, ChatModel> = {};
 
-        openaiChatModels.forEach(model => {
-            chatModels[model.key] = {
-                displayName: model.displayName,
-                model: new ChatOpenAI({
-                    openAIApiKey: openaiApiKey,
-                    modelName: model.key,
-                    temperature: 0.7
-                })
-            }
-        })
+    openaiChatModels.forEach((model) => {
+      chatModels[model.key] = {
+        displayName: model.displayName,
+        model: new ChatOpenAI({
+          openAIApiKey: openaiApiKey,
+          modelName: model.key,
+          temperature: 0.7,
+        }),
+      };
+    });
 
-        return chatModels
-    } catch(err) {
-        console.error(`Error loading OpenAI models: ${err}`)
-        return {}
-    }
-}
+    return chatModels;
+  } catch (err) {
+    console.error(`Error loading OpenAI models: ${err}`);
+    return {};
+  }
+};
 
 export const loadOpenAIEmbeddingModels = async () => {
-    const openaiApiKey = getOpenaiApiKey()
+  const openaiApiKey = getOpenaiApiKey();
 
-    if (!openaiApiKey) return {}
+  if (!openaiApiKey) return {};
 
-    try {
-        const embeddingModels: Record<string, EmbeddingModelProvider> = {}
+  try {
+    const embeddingModels: Record<string, EmbeddingModel> = {};
 
-        openaiEmbeddingModels.forEach(model => {
-            embeddingModels[model.key] = {
-                displayName: model.displayName,
-                model: new OpenAIEmbeddings({
-                    openAIApiKey: openaiApiKey,
-                    modelName: model.key,
-                })
-            }
-        })
+    openaiEmbeddingModels.forEach((model) => {
+      embeddingModels[model.key] = {
+        displayName: model.displayName,
+        model: new OpenAIEmbeddings({
+          openAIApiKey: openaiApiKey,
+          modelName: model.key,
+        }),
+      };
+    });
 
-        return embeddingModels
-    } catch(err) {
-        console.error(`Error loading OpenAI embeddings models: ${err}`)
-        return {}
-    }
-}
+    return embeddingModels;
+  } catch (err) {
+    console.error(`Error loading OpenAI embeddings models: ${err}`);
+    return {};
+  }
+};

ui/lib/search/metaSearchAgent.ts

@@ -414,7 +414,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
       return sortedDocs;
     }
 
-    return []
+    return [];
   }
 
   private processDocs(docs: Document[]) {

ui/lib/types/compute-dot.d.ts

@@ -1,5 +1,5 @@
 declare function computeDot(vectorA: number[], vectorB: number[]): number;
 
-declare module "compute-dot" {
+declare module 'compute-dot' {
   export default computeDot;
 }

ui/lib/utils/documents.ts

@@ -79,7 +79,10 @@ export const getDocumentsFromLinks = async ({ links }: { links: string[] }) => {
 
         docs.push(...linkDocs);
       } catch (err) {
-        console.error("An error occurred while getting documents from links: ", err);
+        console.error(
+          'An error occurred while getting documents from links: ',
+          err,
+        );
         docs.push(
           new Document({
             pageContent: `Failed to retrieve content from the link: ${err}`,

ui/next.config.mjs

@@ -7,7 +7,7 @@ const nextConfig = {
       },
     ],
   },
-  serverExternalPackages: ['pdf-parse']
+  serverExternalPackages: ['pdf-parse'],
 };
 
 export default nextConfig;