refactor: Remove semantic search and vector embedding functionality

Removes @xenova/transformers dependency, vector storage tables, embedding generation, and semantic search APIs. Simplifies context building to use only FTS search. Eliminates visualizer server, postinstall model download, and related CLI commands. Reduces package size and complexity while maintaining core static analysis capabilities.

src/index.ts

@@ -46,7 +46,6 @@ import {
   ResolutionResult,
 } from './resolution';
 import { GraphTraverser, GraphQueryManager } from './graph';
-import { VectorManager, createVectorManager, EmbeddingProgress } from './vectors';
 import { ContextBuilder, createContextBuilder } from './context';
 import { Mutex, FileLock } from './utils';
 
@@ -63,7 +62,6 @@ export {
 export { IndexProgress, IndexResult, SyncResult } from './extraction';
 export { detectLanguage, isLanguageSupported, isGrammarLoaded, getSupportedLanguages, initGrammars, loadGrammarsForLanguages, loadAllGrammars } from './extraction';
 export { ResolutionResult } from './resolution';
-export { EmbeddingProgress } from './vectors';
 export {
   CodeGraphError,
   FileError,
@@ -134,7 +132,6 @@ export class CodeGraph {
   private resolver: ReferenceResolver;
   private graphManager: GraphQueryManager;
   private traverser: GraphTraverser;
-  private vectorManager: VectorManager | null = null;
   private contextBuilder: ContextBuilder;
 
   // Mutex for preventing concurrent indexing operations (in-process)
@@ -160,14 +157,10 @@ export class CodeGraph {
     this.resolver = createResolver(projectRoot, queries);
     this.graphManager = new GraphQueryManager(queries);
     this.traverser = new GraphTraverser(queries);
-    // Vector manager — always created, embeddings generated lazily on first use
-    this.vectorManager = createVectorManager(db.getDb(), queries, {});
-    // Context builder (uses vector manager for semantic search)
     this.contextBuilder = createContextBuilder(
       projectRoot,
       queries,
-      this.traverser,
-      this.vectorManager
+      this.traverser
     );
   }
 
@@ -328,11 +321,6 @@ export class CodeGraph {
   close(): void {
     // Release file lock if held
     this.fileLock.release();
-    // Dispose vector manager first to release ONNX workers
-    if (this.vectorManager) {
-      this.vectorManager.dispose();
-      this.vectorManager = null;
-    }
     this.db.close();
   }
 
@@ -838,102 +826,6 @@ export class CodeGraph {
     return this.graphManager.getNodeMetrics(nodeId);
   }
 
-  // ===========================================================================
-  // Semantic Search (Vector Embeddings)
-  // ===========================================================================
-
-  /**
-   * Initialize the embedding system
-   *
-   * This downloads the embedding model on first use and initializes
-   * the vector search system. Must be called before using semantic search.
-   */
-  async initializeEmbeddings(): Promise<void> {
-    if (!this.vectorManager) {
-      this.vectorManager = createVectorManager(this.db.getDb(), this.queries, {
-        embedder: {
-          showProgress: true,
-        },
-      });
-    }
-    await this.vectorManager.initialize();
-  }
-
-  /**
-   * Check if embeddings are initialized
-   */
-  isEmbeddingsInitialized(): boolean {
-    return this.vectorManager?.isInitialized() ?? false;
-  }
-
-  /**
-   * Generate embeddings for all eligible nodes
-   *
-   * @param onProgress - Optional progress callback
-   * @returns Number of nodes embedded
-   */
-  async generateEmbeddings(
-    onProgress?: (progress: EmbeddingProgress) => void
-  ): Promise<number> {
-    if (!this.vectorManager) {
-      await this.initializeEmbeddings();
-    }
-    return this.vectorManager!.embedAllNodes(onProgress);
-  }
-
-  /**
-   * Semantic search using embeddings
-   *
-   * Searches for code nodes semantically similar to the query.
-   * Requires embeddings to be initialized first.
-   *
-   * @param query - Natural language search query
-   * @param limit - Maximum number of results (default: 10)
-   * @returns Array of search results with similarity scores
-   */
-  async semanticSearch(query: string, limit: number = 10): Promise<SearchResult[]> {
-    if (!this.vectorManager || !this.vectorManager.isInitialized()) {
-      throw new Error(
-        'Embeddings not initialized. Call initializeEmbeddings() first.'
-      );
-    }
-    return this.vectorManager.search(query, { limit });
-  }
-
-  /**
-   * Find similar code blocks
-   *
-   * Finds nodes semantically similar to a given node.
-   * Requires embeddings to be initialized first.
-   *
-   * @param nodeId - ID of the node to find similar nodes for
-   * @param limit - Maximum number of results (default: 10)
-   * @returns Array of similar nodes with similarity scores
-   */
-  async findSimilar(nodeId: string, limit: number = 10): Promise<SearchResult[]> {
-    if (!this.vectorManager || !this.vectorManager.isInitialized()) {
-      throw new Error(
-        'Embeddings not initialized. Call initializeEmbeddings() first.'
-      );
-    }
-    return this.vectorManager.findSimilar(nodeId, { limit });
-  }
-
-  /**
-   * Get vector embedding statistics
-   */
-  getEmbeddingStats(): {
-    totalVectors: number;
-    vssEnabled: boolean;
-    modelId: string;
-    dimension: number;
-  } | null {
-    if (!this.vectorManager) {
-      return null;
-    }
-    return this.vectorManager.getStats();
-  }
-
   // ===========================================================================
   // Context Building
   // ===========================================================================
@@ -964,13 +856,6 @@ export class CodeGraph {
     query: string,
     options?: FindRelevantContextOptions
   ): Promise<Subgraph> {
-    // Update context builder with current vector manager
-    this.contextBuilder = createContextBuilder(
-      this.projectRoot,
-      this.queries,
-      this.traverser,
-      this.vectorManager
-    );
     return this.contextBuilder.findRelevantContext(query, options);
   }
 
@@ -978,7 +863,7 @@ export class CodeGraph {
    * Build context for a task
    *
    * Creates comprehensive context by:
-   * 1. Running semantic search to find entry points
+   * 1. Running FTS search to find entry points
    * 2. Expanding the graph around entry points
    * 3. Extracting code blocks for key nodes
    * 4. Formatting output for Claude
@@ -991,13 +876,6 @@ export class CodeGraph {
     input: TaskInput,
     options?: BuildContextOptions
   ): Promise<TaskContext | string> {
-    // Update context builder with current vector manager
-    this.contextBuilder = createContextBuilder(
-      this.projectRoot,
-      this.queries,
-      this.traverser,
-      this.vectorManager
-    );
     return this.contextBuilder.buildContext(input, options);
   }