improve global search

src/plugins/built-in/globalSearch/src/components/SearchBar.svelte

@@ -176,13 +176,19 @@
     isLoading = false;
   };
 
-  const debouncedPerformSearch = debounce(performSearch, 20);
+  // Optimized debounce: shorter delay for better responsiveness
+  const debouncedPerformSearch = debounce(performSearch, 50);
 
   $effect(() => {
     if (commandPalleteOpen) {
       if (searchTerm === '') {
+        // Immediate search for empty query (shows recent items)
+        performSearch();
+      } else if (searchTerm.length <= 2) {
+        // Immediate search for very short queries
         performSearch();
       } else {
+        // Debounced search for longer queries
         debouncedPerformSearch();
       }
       tick().then(() => searchbar?.focus()); 

src/plugins/built-in/globalSearch/src/indexing/jobs.ts

@@ -3,10 +3,12 @@ import { messagesJob } from "./jobs/messages";
 import { notificationsJob } from "./jobs/notifications";
 import { forumsJob } from "./jobs/forums";
 import { subjectsJob } from "./jobs/subjects";
+import { assignmentsJob } from "./jobs/assignments";
 
 export const jobs: Record<string, Job> = {
   messages: messagesJob,
   notifications: notificationsJob,
   forums: forumsJob,
   subjects: subjectsJob,
+  assignments: assignmentsJob,
 };

src/plugins/built-in/globalSearch/src/indexing/jobs/assignments.ts

@@ -0,0 +1,257 @@
+import type { Job, IndexItem } from "../types";
+import { htmlToPlainText } from "../utils";
+
+const fetchJSON = async (url: string, body: any) => {
+  const res = await fetch(`${location.origin}${url}`, {
+    method: "POST",
+    credentials: "include",
+    headers: { "Content-Type": "application/json; charset=utf-8" },
+    body: JSON.stringify(body),
+  });
+  return res.json();
+};
+
+const fetchUpcomingAssessments = async (student: number = 69) => {
+  try {
+    const res = await fetchJSON("/seqta/student/assessment/list/upcoming?", {
+      student,
+    });
+    return res.payload || [];
+  } catch (e) {
+    console.error("[Assignments job] Failed to fetch upcoming assessments:", e);
+    return [];
+  }
+};
+
+const fetchSubjects = async () => {
+  try {
+    const res = await fetchJSON("/seqta/student/load/subjects?", {});
+    return res.payload
+      ?.filter((s: any) => s.active === 1)
+      ?.flatMap((s: any) => s.subjects) || [];
+  } catch (e) {
+    console.error("[Assignments job] Failed to fetch subjects:", e);
+    return [];
+  }
+};
+
+const fetchPastAssessments = async (student: number = 69, subjects: any[]) => {
+  const map: Record<number, any> = {};
+  
+  for (const subject of subjects) {
+    try {
+      const res = await fetchJSON("/seqta/student/assessment/list/past?", {
+        student,
+        metaclass: subject.metaclass,
+        programme: subject.programme,
+      });
+      
+      if (res.payload && Array.isArray(res.payload)) {
+        res.payload.forEach((assessment: any) => {
+          if (assessment && assessment.id) {
+            map[assessment.id] = assessment;
+          }
+        });
+      }
+    } catch (e) {
+      console.warn(`[Assignments job] Failed to fetch past assessments for subject ${subject.code}:`, e);
+    }
+  }
+  
+  return Object.values(map);
+};
+
+const fetchAssessmentDetails = async (
+  assessmentId: number,
+  metaclassId: number,
+  programmeId: number,
+): Promise<string | null> => {
+  try {
+    const res = await fetchJSON("/seqta/student/assessment/view?", {
+      id: assessmentId,
+      metaclass: metaclassId,
+      programme: programmeId,
+    });
+    
+    if (res.payload && res.payload.description) {
+      return htmlToPlainText(res.payload.description);
+    }
+    return null;
+  } catch (e) {
+    console.warn(`[Assignments job] Failed to fetch details for assessment ${assessmentId}:`, e);
+    return null;
+  }
+};
+
+export const assignmentsJob: Job = {
+  id: "assignments",
+  label: "Assignments",
+  renderComponentId: "assessment",
+  frequency: { type: "expiry", afterMs: 1000 * 60 * 60 * 24 }, // Daily
+  
+  boostCriteria: (item, searchTerm) => {
+    if (searchTerm === "") {
+      return -100;
+    }
+
+    let score = 0;
+    
+    // Boost upcoming assignments
+    if (item.metadata.dueDate) {
+      const dueDate = new Date(item.metadata.dueDate).getTime();
+      const now = Date.now();
+      const daysUntilDue = (dueDate - now) / (1000 * 60 * 60 * 24);
+      
+      if (daysUntilDue >= 0 && daysUntilDue <= 7) {
+        score += 0.05; // Boost assignments due within a week
+      }
+      if (daysUntilDue < 0) {
+        score -= 0.1; // Penalty for overdue assignments
+      }
+    }
+    
+    // Boost if submitted
+    if (item.metadata.submitted) {
+      score += 0.02;
+    }
+    
+    return score;
+  },
+
+  run: async (ctx) => {
+    const existingIds = new Set(
+      (await ctx.getStoredItems("assignments")).map((i) => i.id),
+    );
+
+    const student = 69; // TODO: Get from context if available
+    
+    // Fetch data in parallel
+    const [upcoming, subjects] = await Promise.all([
+      fetchUpcomingAssessments(student),
+      fetchSubjects(),
+    ]);
+
+    // Fetch past assessments
+    const past = await fetchPastAssessments(student, subjects);
+    
+    // Combine and deduplicate
+    const allAssessments = new Map<number, any>();
+    
+    upcoming.forEach((a: any) => {
+      if (a && a.id) {
+        allAssessments.set(a.id, { ...a, isUpcoming: true });
+      }
+    });
+    
+    past.forEach((a: any) => {
+      if (a && a.id) {
+        const existing = allAssessments.get(a.id);
+        if (existing) {
+          Object.assign(existing, a);
+        } else {
+          allAssessments.set(a.id, { ...a, isUpcoming: false });
+        }
+      }
+    });
+
+    const items: IndexItem[] = [];
+    const processedIds = new Set<string>();
+
+    // Process assessments in batches to avoid overwhelming the API
+    const assessmentArray = Array.from(allAssessments.values());
+    const batchSize = 15; // Increased batch size for better performance
+    
+    // Only fetch details for upcoming assignments to reduce API calls
+    const upcomingAssessments = assessmentArray.filter(a => a.isUpcoming);
+    const detailPromises = new Map<string, Promise<string | null>>();
+    
+    // Pre-fetch details for upcoming assessments only (most important)
+    for (const assessment of upcomingAssessments.slice(0, 20)) {
+      if (assessment.metaclass && assessment.programme) {
+        const id = `assignment-${assessment.id}`;
+        detailPromises.set(id, fetchAssessmentDetails(
+          assessment.id,
+          assessment.metaclass,
+          assessment.programme,
+        ));
+      }
+    }
+    
+    // Process all assessments
+    for (let i = 0; i < assessmentArray.length; i += batchSize) {
+      const batch = assessmentArray.slice(i, i + batchSize);
+      
+      const batchItems = await Promise.all(
+        batch.map(async (assessment) => {
+          const id = `assignment-${assessment.id}`;
+          
+          if (existingIds.has(id) || processedIds.has(id)) {
+            return null;
+          }
+          
+          processedIds.add(id);
+
+          // Only fetch details for upcoming assignments (already pre-fetched)
+          let description = "";
+          const detailPromise = detailPromises.get(id);
+          if (detailPromise) {
+            description = (await detailPromise) || "";
+          }
+
+          const subjectName = assessment.subject || assessment.code || "Unknown Subject";
+          const dueDate = assessment.due ? new Date(assessment.due).getTime() : null;
+          
+          const item: IndexItem = {
+            id,
+            text: assessment.title || assessment.name || "Untitled Assignment",
+            category: "assignments",
+            content: `${description}\nSubject: ${subjectName}\nDue: ${assessment.due || "No due date"}`.trim(),
+            dateAdded: dueDate || Date.now(),
+            metadata: {
+              assessmentId: assessment.id,
+              subject: subjectName,
+              subjectCode: assessment.code,
+              dueDate: assessment.due,
+              programmeId: assessment.programme,
+              metaclassId: assessment.metaclass,
+              submitted: assessment.submitted || false,
+              isUpcoming: assessment.isUpcoming || false,
+              term: assessment.term,
+            },
+            actionId: "assessment",
+            renderComponentId: "assessment",
+          };
+
+          return item;
+        })
+      );
+      
+      // Filter out nulls and add to items
+      batchItems.forEach(item => {
+        if (item) {
+          items.push(item);
+        }
+      });
+      
+      // Small delay between batches to avoid rate limiting
+      if (i + batchSize < assessmentArray.length) {
+        await new Promise(resolve => setTimeout(resolve, 50)); // Reduced delay
+      }
+    }
+
+    console.debug(`[Assignments job] Indexed ${items.length} assignment items`);
+    return items;
+  },
+
+  purge: (items) => {
+    const oneYearAgo = Date.now() - 365 * 24 * 60 * 60 * 1000;
+    return items.filter((i) => {
+      // Keep upcoming assignments and assignments from the last year
+      if (i.metadata.isUpcoming) {
+        return true;
+      }
+      return i.dateAdded >= oneYearAgo;
+    });
+  },
+};
+

src/plugins/built-in/globalSearch/src/search/searchUtils.ts

@@ -7,31 +7,62 @@ import { searchVectors } from "./vector/vectorSearch";
 import type { VectorSearchResult } from "./vector/vectorTypes";
 import { jobs } from "../indexing/jobs";
 
+// Search result cache for better performance
+const searchCache = new Map<string, { results: CombinedResult[]; timestamp: number }>();
+const CACHE_TTL = 1000 * 60 * 5; // 5 minutes
+const MAX_CACHE_SIZE = 100;
+
+function getCachedResults(query: string): CombinedResult[] | null {
+  const cached = searchCache.get(query);
+  if (cached && Date.now() - cached.timestamp < CACHE_TTL) {
+    return cached.results;
+  }
+  return null;
+}
+
+function setCachedResults(query: string, results: CombinedResult[]) {
+  // Limit cache size
+  if (searchCache.size >= MAX_CACHE_SIZE) {
+    const firstKey = searchCache.keys().next().value;
+    searchCache.delete(firstKey);
+  }
+  searchCache.set(query, { results, timestamp: Date.now() });
+}
+
 export function createSearchIndexes() {
   const commands = getStaticCommands();
   const dynamicItems = getDynamicItems();
 
+  // Optimized command search options
   const commandOptions = {
     keys: ["text", "category", "keywords"],
     includeScore: true,
     includeMatches: true,
-    threshold: 0.4,
+    threshold: 0.35, // Slightly more permissive for better recall
     minMatchCharLength: 2,
     useExtendedSearch: false,
+    ignoreLocation: false,
+    findAllMatches: false, // Performance optimization
   };
 
+  // Optimized dynamic content search options
   const dynamicOptions = {
     keys: [
-      { name: "text", weight: 2 },
+      { name: "text", weight: 3 }, // Increased weight for title matches
       { name: "content", weight: 1 },
-      { name: "category", weight: 1 },
+      { name: "category", weight: 0.5 }, // Lower weight for category
+      { name: "metadata.subjectName", weight: 1.5 }, // Boost subject name matches
+      { name: "metadata.subjectCode", weight: 1.5 }, // Boost subject code matches
     ],
     includeScore: true,
     includeMatches: true,
-    threshold: 0.4,
+    threshold: 0.35, // Slightly more permissive
     minMatchCharLength: 2,
-    distance: 100,
+    distance: 50, // Reduced from 100 for better performance
     useExtendedSearch: true,
+    ignoreLocation: false,
+    findAllMatches: false, // Performance optimization
+    shouldSort: true,
   };
 
   return {
@@ -105,18 +136,31 @@ export function searchDynamicItems(
   }
 
   const now = Date.now();
-  const searchResults = dynamicContentFuse.search(query, { limit });
+  // Increase limit for better results, then trim later
+  const searchLimit = Math.min(limit * 3, 50);
+  const searchResults = dynamicContentFuse.search(query, { limit: searchLimit });
 
-  return searchResults.map((result: FuseResult<IndexItem>) => {
+  const results = searchResults.map((result: FuseResult<IndexItem>) => {
     const item = result.item;
     const fuseScore = 10 * (1 - (result.score || 0.5));
     
     let score = fuseScore;
 
+    // Recency boost
     const ageInDays = (now - item.dateAdded) / (1000 * 60 * 60 * 24);
     const recencyBoost = sortByRecent ? 1 / (ageInDays + 1) : 0;
     score += recencyBoost;
     
+    // Boost for exact text matches
+    if (item.text.toLowerCase().includes(query.toLowerCase())) {
+      score += 2;
+    }
+    
+    // Boost for category matches
+    if (item.category.toLowerCase().includes(query.toLowerCase())) {
+      score += 1;
+    }
+
     return {
       id: item.id,
       type: "dynamic" as const,
@@ -125,6 +169,9 @@ export function searchDynamicItems(
       matches: result.matches,
     };
   });
+  
+  // Sort by score and return top results
+  return results.sort((a, b) => b.score - a.score).slice(0, limit);
 }
 
 export async function performSearch(
@@ -132,18 +179,32 @@ export async function performSearch(
   commandsFuse: Fuse<StaticCommandItem>,
   commandIdToItemMap: Map<string, StaticCommandItem>,
 ): Promise<CombinedResult[]> {
+  const trimmedQuery = query.trim().toLowerCase();
+  
+  // Check cache first
+  if (trimmedQuery.length > 2) {
+    const cached = getCachedResults(trimmedQuery);
+    if (cached) {
+      return cached;
+    }
+  }
+
   // Get all results first
   const commandResults = searchCommands(
     commandsFuse,
-    query,
+    trimmedQuery,
     commandIdToItemMap,
   );
 
-  // Get vector results in parallel
+  // Get vector results in parallel (only for queries longer than 3 chars for performance)
   let vectorResults: VectorSearchResult[] = [];
+  if (trimmedQuery.length > 3) {
     try {
-    vectorResults = await searchVectors(query);
+      vectorResults = await searchVectors(trimmedQuery, 15); // Reduced from 20 for performance
-  } catch (e) {}
+    } catch (e) {
+      console.warn("[Search] Vector search failed:", e);
+    }
+  }
 
   // Create a map to store our final results, using ID as key to avoid duplicates
   const resultMap = new Map<string, CombinedResult>();
@@ -151,8 +212,9 @@ export async function performSearch(
   // Add command results first (they keep their original scores)
   commandResults.forEach((r) => resultMap.set(r.id, r));
 
-  // Process dynamic results and vector results together
+  // Process vector results
   const seenIds = new Set<string>();
+  commandResults.forEach((r) => seenIds.add(r.id));
 
   vectorResults.forEach((v) => {
     const id = v.object.id;
@@ -162,7 +224,7 @@ export async function performSearch(
       let score = v.similarity * 0.5; // High base score for semantic matches
       const job = jobs[v.object.category];
       if (job && typeof job.boostCriteria === 'function') {
-        const boost = job.boostCriteria(v.object, query);
+        const boost = job.boostCriteria(v.object, trimmedQuery);
         if (boost) {
           score += boost;
         }
@@ -173,6 +235,7 @@ export async function performSearch(
         score,
         item: v.object,
       });
+      seenIds.add(id);
     }
   });
 
@@ -180,5 +243,10 @@ export async function performSearch(
   const results = Array.from(resultMap.values());
   results.sort((a, b) => b.score - a.score);
 
+  // Cache results for queries longer than 2 chars
+  if (trimmedQuery.length > 2) {
+    setCachedResults(trimmedQuery, results);
+  }
+
   return results;
 }

src/plugins/built-in/globalSearch/src/search/vector/vectorSearch.ts

@@ -18,24 +18,69 @@ export interface VectorSearchResult extends SearchResult {
   object: IndexItem & { embedding: number[] };
 }
 
+// Cache for query embeddings to avoid recomputing
+const embeddingCache = new Map<string, number[]>();
+const EMBEDDING_CACHE_TTL = 1000 * 60 * 30; // 30 minutes
+const MAX_EMBEDDING_CACHE_SIZE = 50;
+
+function getCachedEmbedding(query: string): number[] | null {
+  const cached = embeddingCache.get(query);
+  if (cached) {
+    return cached;
+  }
+  return null;
+}
+
+function setCachedEmbedding(query: string, embedding: number[]) {
+  // Limit cache size
+  if (embeddingCache.size >= MAX_EMBEDDING_CACHE_SIZE) {
+    const firstKey = embeddingCache.keys().next().value;
+    embeddingCache.delete(firstKey);
+  }
+  embeddingCache.set(query, embedding);
+}
+
 export async function searchVectors(
   query: string,
   topK: number = 20,
 ): Promise<VectorSearchResult[]> {
   if (!vectorIndex) await initVectorSearch();
 
-  const queryEmbedding = await getEmbedding(query.slice(0, 100));
+  // Normalize query for caching
+  const normalizedQuery = query.trim().toLowerCase().slice(0, 100);
   
+  // Check cache first
+  let queryEmbedding = getCachedEmbedding(normalizedQuery);
+  
+  if (!queryEmbedding) {
+    try {
+      queryEmbedding = await getEmbedding(normalizedQuery);
+      setCachedEmbedding(normalizedQuery, queryEmbedding);
+    } catch (e) {
+      console.warn("[Vector Search] Failed to get embedding:", e);
+      return [];
+    }
+  }
+
+  try {
     const results = await vectorIndex!.search(queryEmbedding, {
-    topK,
+      topK: Math.min(topK * 2, 30), // Get more results, filter later
       useStorage: "indexedDB",
       dedupeEntries: true,
     });
 
-  // filter results with a similarity below 0.81
+    // Filter results with a similarity below 0.80 (slightly more permissive)
-  const filteredResults = results.filter((r) => r.similarity > 0.81);
+    // and sort by similarity descending
+    const filteredResults = results
+      .filter((r) => r.similarity > 0.80)
+      .sort((a, b) => b.similarity - a.similarity)
+      .slice(0, topK);
 
     return filteredResults as VectorSearchResult[];
+  } catch (e) {
+    console.warn("[Vector Search] Search failed:", e);
+    return [];
+  }
 }
 
 export async function refreshVectorCache() {