Fix: Update all search calls to 2-parameter API

src/brainyData.ts

@@ -3205,9 +3205,11 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
     const searchK = options.cursor ? k + 20 : k // Get extra results for filtering
 
     // Perform regular search
-    const allResults = await this.search(queryVectorOrData, searchK, {
-      ...options,
-      skipCache: options.skipCache
+    const { cursor, ...searchOptions } = options
+    const allResults = await this.search(queryVectorOrData, {
+      limit: searchK,
+      nounTypes: searchOptions.nounTypes,
+      metadata: searchOptions.filter
     })
 
     let results = allResults
@@ -3469,11 +3471,10 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
 
     // If no relationType is specified, use the original vector similarity search
     const k = (options.limit || 10) + 1 // Add 1 to account for the original entity
-    const searchResults = await this.search(entity.vector, k, {
-      forceEmbed: false,
-      nounTypes: options.nounTypes,
-      includeVerbs: options.includeVerbs,
-      searchMode: options.searchMode
+    const searchResults = await this.search(entity.vector, {
+      limit: k,
+      excludeDeleted: false,
+      nounTypes: options.nounTypes
     })
 
     // Filter out the original entity and limit to the requested number
@@ -5802,12 +5803,10 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
       const queryVector = await this.embed(query)
 
       // Search using the embedded vector with metadata filtering
-      const results = await this.search(queryVector, k, {
+      const results = await this.search(queryVector, {
+        limit: k,
         nounTypes: options.nounTypes,
-        includeVerbs: options.includeVerbs,
-        searchMode: options.searchMode,
-        metadata: options.metadata,
-        forceEmbed: false // Already embedded
+        metadata: options.metadata
       })
 
       // Track search performance
@@ -6683,11 +6682,8 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
     for (const [service, fieldNames] of Object.entries(serviceFieldMappings)) {
       for (const fieldName of fieldNames) {
         // Search using the specific field name for this service
-        const results = await this.search(searchTerm, k, {
-          searchField: fieldName,
-          service,
-          includeVerbs: options.includeVerbs,
-          searchMode: options.searchMode
+        const results = await this.search(searchTerm, {
+          limit: k
         })
 
         // Add results to the combined list

src/chat/BrainyChat.ts

@@ -67,8 +67,8 @@ export class BrainyChat {
       // Search for the most recent chat message using Brainy's search
       const recentMessages = await this.brainy.search(
         'recent chat conversation',
-        1,
         {
+          limit: 1,
           nounTypes: [NounType.Message],
           metadata: {
             messageType: 'chat'
@@ -198,7 +198,9 @@ export class BrainyChat {
     await this.addMessage(question, 'user')
 
     // Search for relevant content using Brainy's search
-    const searchResults = await this.brainy.search(question, options?.maxSources || 5)
+    const searchResults = await this.brainy.search(question, {
+      limit: options?.maxSources || 5
+    })
 
     // Generate a template-based response
     let response = ''
@@ -242,8 +244,8 @@ export class BrainyChat {
       // Search for messages in this session using Brainy's search
       const messageNouns = await this.brainy.search(
         '', // Empty query to get all messages
-        limit,
         {
+          limit: limit,
           nounTypes: [NounType.Message],
           metadata: {
             sessionId: this.currentSessionId,
@@ -286,8 +288,8 @@ export class BrainyChat {
     try {
       const results = await this.brainy.search(
         options?.semanticSearch !== false ? query : '',
-        options?.limit || 20,
         {
+          limit: options?.limit || 20,
           nounTypes: [NounType.Message],
           metadata
         }
@@ -308,8 +310,8 @@ export class BrainyChat {
     try {
       const sessionNouns = await this.brainy.search(
         '',
-        limit,
         {
+          limit: limit,
           nounTypes: [NounType.Concept],
           metadata: {
             sessionType: 'chat'
@@ -409,8 +411,8 @@ export class BrainyChat {
     // Find previous message to create conversation flow using VerbType.Precedes
     const previousMessages = await this.brainy.search(
       '',
-      1,
       {
+        limit: 1,
         nounTypes: [NounType.Message],
         metadata: {
           sessionId: this.currentSessionId,
@@ -435,8 +437,8 @@ export class BrainyChat {
     try {
       const sessionNouns = await this.brainy.search(
         '',
-        1,
         {
+          limit: 1,
           nounTypes: [NounType.Concept],
           metadata: {
             sessionType: 'chat'
@@ -460,8 +462,8 @@ export class BrainyChat {
     try {
       const messageNouns = await this.brainy.search(
         '',
-        limit,
         {
+          limit: limit,
           nounTypes: [NounType.Message],
           metadata: {
             sessionId: sessionId,

src/examples/basicUsage.ts

@@ -52,7 +52,7 @@ async function runExample() {
 
   // Search for similar vectors
   console.log('\nSearching for vectors similar to "cat"...')
-  const catResults = await db.search(wordEmbeddings['cat'], 3)
+  const catResults = await db.search(wordEmbeddings['cat'], { limit: 3 })
   console.log('Results:')
   for (const result of catResults) {
     const word =
@@ -66,7 +66,7 @@ async function runExample() {
 
   // Search for similar vectors
   console.log('\nSearching for vectors similar to "fish"...')
-  const fishResults = await db.search(wordEmbeddings['fish'], 3)
+  const fishResults = await db.search(wordEmbeddings['fish'], { limit: 3 })
   console.log('Results:')
   for (const result of fishResults) {
     const word =
@@ -96,7 +96,7 @@ async function runExample() {
 
   // Search again to verify shark is gone
   console.log('\nSearching for vectors similar to "fish" after deletion...')
-  const fishResultsAfterDeletion = await db.search(wordEmbeddings['fish'], 3)
+  const fishResultsAfterDeletion = await db.search(wordEmbeddings['fish'], { limit: 3 })
   console.log('Results:')
   for (const result of fishResultsAfterDeletion) {
     const word =

src/neural/embeddedPatterns.ts

@@ -2,7 +2,7 @@
  * 🧠 BRAINY EMBEDDED PATTERNS
  * 
  * AUTO-GENERATED - DO NOT EDIT
- * Generated: 2025-08-26T19:07:11.967Z
+ * Generated: 2025-08-26T19:40:18.500Z
  * Patterns: 220
  * Coverage: 94-98% of all queries
  * 

src/neural/naturalLanguageProcessor.ts

@@ -355,7 +355,7 @@ export class NaturalLanguageProcessor {
     for (const term of terms) {
       try {
         // Search for similar entities in the knowledge base
-        const results = await this.brain.search(term, 5)
+        const results = await this.brain.search(term, { limit: 5 })
         
         for (const result of results) {
           if (result.score > 0.8) { // High similarity threshold