fix: copilot not working (#3425)

plugins/copilot/src/core/langchain/vector-store.ts

@@ -1,118 +0,0 @@
-// fixme: vector store has not finished
-import type { DBSchema } from 'idb';
-import { Document } from 'langchain/document';
-import { Embeddings } from 'langchain/embeddings';
-import { VectorStore } from 'langchain/vectorstores';
-import { similarity as ml_distance_similarity } from 'ml-distance';
-
-// eslint-disable-next-line @typescript-eslint/no-unused-vars
-interface VectorDBV1 extends DBSchema {
-  vector: {
-    key: string;
-    value: Vector;
-  };
-}
-
-interface Vector {
-  id: string;
-
-  content: string;
-  embedding: number[];
-  metadata: Record<string, unknown>;
-}
-
-export interface MemoryVectorStoreArgs {
-  similarity?: typeof ml_distance_similarity.cosine;
-}
-
-export class IndexedDBVectorStore extends VectorStore {
-  memoryVectors: any[] = [];
-
-  similarity: typeof ml_distance_similarity.cosine;
-
-  constructor(
-    embeddings: Embeddings,
-    { similarity, ...rest }: MemoryVectorStoreArgs = {}
-  ) {
-    super(embeddings, rest);
-
-    this.similarity = similarity ?? ml_distance_similarity.cosine;
-  }
-
-  async addDocuments(documents: Document[]): Promise<void> {
-    const texts = documents.map(({ pageContent }) => pageContent);
-    return this.addVectors(
-      await this.embeddings.embedDocuments(texts),
-      documents
-    );
-  }
-
-  async addVectors(vectors: number[][], documents: Document[]): Promise<void> {
-    const memoryVectors = vectors.map((embedding, idx) => ({
-      content: documents[idx].pageContent,
-      embedding,
-      metadata: documents[idx].metadata,
-    }));
-
-    this.memoryVectors = this.memoryVectors.concat(memoryVectors);
-  }
-
-  async similaritySearchVectorWithScore(
-    query: number[],
-    k: number
-  ): Promise<[Document, number][]> {
-    const searches = this.memoryVectors
-      .map((vector, index) => ({
-        similarity: this.similarity(query, vector.embedding),
-        index,
-      }))
-      .sort((a, b) => (a.similarity > b.similarity ? -1 : 0))
-      .slice(0, k);
-
-    const result: [Document, number][] = searches.map(search => [
-      new Document({
-        metadata: this.memoryVectors[search.index].metadata,
-        pageContent: this.memoryVectors[search.index].content,
-      }),
-      search.similarity,
-    ]);
-
-    return result;
-  }
-
-  static override async fromTexts(
-    texts: string[],
-    metadatas: object[] | object,
-    embeddings: Embeddings,
-    dbConfig?: MemoryVectorStoreArgs
-  ): Promise<IndexedDBVectorStore> {
-    const docs: Document[] = [];
-    for (let i = 0; i < texts.length; i += 1) {
-      const metadata = Array.isArray(metadatas) ? metadatas[i] : metadatas;
-      const newDoc = new Document({
-        pageContent: texts[i],
-        metadata,
-      });
-      docs.push(newDoc);
-    }
-    return IndexedDBVectorStore.fromDocuments(docs, embeddings, dbConfig);
-  }
-
-  static override async fromDocuments(
-    docs: Document[],
-    embeddings: Embeddings,
-    dbConfig?: MemoryVectorStoreArgs
-  ): Promise<IndexedDBVectorStore> {
-    const instance = new this(embeddings, dbConfig);
-    await instance.addDocuments(docs);
-    return instance;
-  }
-
-  static async fromExistingIndex(
-    embeddings: Embeddings,
-    dbConfig?: MemoryVectorStoreArgs
-  ): Promise<IndexedDBVectorStore> {
-    const instance = new this(embeddings, dbConfig);
-    return instance;
-  }
-}