Auto-formatted the code using Prettier

Author: kevin-lann

course-matrix/backend/src/controllers/aiController.ts

@@ -35,7 +35,7 @@ const pinecone = new Pinecone({
 });
 
 const index: Index<RecordMetadata> = pinecone.Index(
-  process.env.PINECONE_INDEX_NAME!
+  process.env.PINECONE_INDEX_NAME!,
 );
 
 console.log("Connected to OpenAI API");
@@ -92,7 +92,7 @@ function analyzeQuery(query: string): {
       "prerequisites",
       "corequisites",
       "departments",
-      "programs"
+      "programs",
     );
   }
 
@@ -110,7 +110,7 @@ async function searchSelectedNamespaces(
   query: string,
   k: number,
   namespaces: string[],
-  filters?: Object
+  filters?: Object,
 ): Promise<Document[]> {
   let allResults: Document[] = [];
 
@@ -132,7 +132,7 @@ async function searchSelectedNamespaces(
       const results = await namespaceStore.similaritySearch(
         query,
         Math.max(k, namespaceToMinResults.get(namespace)),
-        namespace === "courses_v3" ? filters : undefined
+        namespace === "courses_v3" ? filters : undefined,
       );
       console.log(`Found ${results.length} results in namespace: ${namespace}`);
       allResults = [...allResults, ...results];
@@ -153,7 +153,7 @@ async function searchSelectedNamespaces(
 // Reformulate user query to make more concise query to database, taking into consideration context
 async function reformulateQuery(
   latestQuery: string,
-  conversationHistory: any[]
+  conversationHistory: any[],
 ): Promise<string> {
   try {
     const openai = new OpenAI({
@@ -244,7 +244,7 @@ function includeFilters(query: string) {
       if (keywords.some((keyword) => lowerQuery.includes(keyword))) {
         relaventBreadthRequirements.push(convertBreadthRequirement(namespace));
       }
-    }
+    },
   );
 
   Object.entries(YEAR_LEVEL_KEYWORDS).forEach(([namespace, keywords]) => {
@@ -309,7 +309,7 @@ export const chat = asyncHandler(async (req: Request, res: Response) => {
   // Use GPT-4o to reformulate the query based on conversation history
   const reformulatedQuery = await reformulateQuery(
     latestMessage,
-    conversationHistory.slice(-CHATBOT_MEMORY_THRESHOLD) // last K messages
+    conversationHistory.slice(-CHATBOT_MEMORY_THRESHOLD), // last K messages
   );
   console.log(">>>> Original query:", latestMessage);
   console.log(">>>> Reformulated query:", reformulatedQuery);
@@ -323,8 +323,8 @@ export const chat = asyncHandler(async (req: Request, res: Response) => {
   if (requiresSearch) {
     console.log(
       `Query requires knowledge retrieval, searching namespaces: ${relevantNamespaces.join(
-        ", "
-      )}`
+        ", ",
+      )}`,
     );
 
     const filters = includeFilters(reformulatedQuery);
@@ -335,7 +335,7 @@ export const chat = asyncHandler(async (req: Request, res: Response) => {
       reformulatedQuery,
       3,
       relevantNamespaces,
-      Object.keys(filters).length === 0 ? undefined : filters
+      Object.keys(filters).length === 0 ? undefined : filters,
     );
     // console.log("Search Results: ", searchResults);
 
@@ -403,15 +403,15 @@ export const testSimilaritySearch = asyncHandler(
     if (requiresSearch) {
       console.log(
         `Query requires knowledge retrieval, searching namespaces: ${relevantNamespaces.join(
-          ", "
-        )}`
+          ", ",
+        )}`,
       );
 
       // Search only the relevant namespaces
       const searchResults = await searchSelectedNamespaces(
         message,
         3,
-        relevantNamespaces
+        relevantNamespaces,
       );
       console.log("Search Results: ", searchResults);
 
@@ -421,11 +421,11 @@ export const testSimilaritySearch = asyncHandler(
       }
     } else {
       console.log(
-        "Query does not require knowledge retrieval, skipping search"
+        "Query does not require knowledge retrieval, skipping search",
       );
     }
 
     console.log("CONTEXT: ", context);
     res.status(200).send(context);
-  }
+  },
 );

course-matrix/backend/src/utils/embeddings.ts

@@ -51,7 +51,7 @@ async function processCoursesCSV(filePath: string, namespace: string) {
       source: fileName,
       row: index + 1,
       breadth_requirement: convertBreadthRequirement(
-        doc.pageContent.split("\n")[1].split(": ")[1]
+        doc.pageContent.split("\n")[1].split(": ")[1],
       ),
       year_level: doc.pageContent.split("\n")[10].split(": ")[1],
     },
@@ -101,7 +101,7 @@ async function processPDF(filePath: string, namespace: string) {
   // console.log("Sample split docs: ", splitDocs.slice(0, 6))
 
   console.log(
-    `Split into ${splitDocs.length} sections by "Calendar Section:" delimiter`
+    `Split into ${splitDocs.length} sections by "Calendar Section:" delimiter`,
   );
 
   // Store the split documents as embeddings