Added cloudflare vector-store (#2607)
This commit is contained in:
Mrinank Bhowmick
45
docs/components/vectordbs/dbs/vectorize.mdx
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45
docs/components/vectordbs/dbs/vectorize.mdx
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@@ -0,0 +1,45 @@
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[Cloudflare Vectorize](https://developers.cloudflare.com/vectorize/) is a vector database offering from Cloudflare, allowing you to build AI-powered applications with vector embeddings.
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### Usage
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<CodeGroup>
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```typescript TypeScript
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import { Memory } from 'mem0ai/oss';
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const config = {
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vectorStore: {
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provider: 'vectorize',
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config: {
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indexName: 'my-memory-index',
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accountId: 'your-cloudflare-account-id',
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apiKey: 'your-cloudflare-api-key',
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dimension: 1536, // Optional: defaults to 1536
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},
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},
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};
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const memory = new Memory(config);
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const messages = [
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{"role": "user", "content": "I'm looking for a good book to read."},
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{"role": "assistant", "content": "Sure, what genre are you interested in?"},
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{"role": "user", "content": "I enjoy fantasy novels with strong world-building."},
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{"role": "assistant", "content": "Great! I'll keep that in mind for future recommendations."}
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]
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await memory.add(messages, { userId: "bob", metadata: { interest: "books" } });
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```
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</CodeGroup>
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### Config
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Let's see the available parameters for the `vectorize` config:
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<Tabs>
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<Tab title="TypeScript">
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| Parameter | Description | Default Value |
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| --- | --- | --- |
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| `indexName` | The name of the Vectorize index | `None` (Required) |
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| `accountId` | Your Cloudflare account ID | `None` (Required) |
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| `apiKey` | Your Cloudflare API token | `None` (Required) |
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| `dimension` | Dimensions of the embedding model | `1536` |
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</Tab>
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</Tabs>
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@@ -13,7 +13,7 @@ Mem0 includes built-in support for various popular databases. Memory can utilize
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See the list of supported vector databases below.
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<Note>
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The following vector databases are supported in the Python implementation. The TypeScript implementation currently only supports Qdrant, Redis and in-memory vector database.
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The following vector databases are supported in the Python implementation. The TypeScript implementation currently only supports Qdrant, Redis,Vectorize and in-memory vector database.
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</Note>
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<CardGroup cols={3}>
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@@ -21,6 +21,7 @@
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"@types/redis": "^4.0.10",
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"@types/sqlite3": "^3.1.11",
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"@types/uuid": "^9.0.8",
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"cloudflare": "^4.2.0",
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"dotenv": "^16.4.4",
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"groq-sdk": "^0.3.0",
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"openai": "^4.28.0",
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@@ -31,6 +32,7 @@
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"zod": "^3.22.4"
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},
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"devDependencies": {
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"@cloudflare/workers-types": "^4.20250504.0",
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"@types/jest": "^29.5.12",
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"jest": "^29.7.0",
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"rimraf": "^5.0.5",
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@@ -22,4 +22,5 @@ export * from "./vector_stores/qdrant";
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export * from "./vector_stores/redis";
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export * from "./vector_stores/supabase";
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export * from "./vector_stores/langchain";
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export * from "./vector_stores/vectorize";
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export * from "./utils/factory";
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@@ -16,6 +16,7 @@ import { Embedder } from "../embeddings/base";
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import { LLM } from "../llms/base";
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import { VectorStore } from "../vector_stores/base";
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import { Qdrant } from "../vector_stores/qdrant";
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import { VectorizeDB } from "../vector_stores/vectorize";
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import { RedisDB } from "../vector_stores/redis";
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import { OllamaLLM } from "../llms/ollama";
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import { SupabaseDB } from "../vector_stores/supabase";
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@@ -90,6 +91,8 @@ export class VectorStoreFactory {
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return new SupabaseDB(config as any);
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case "langchain":
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return new LangchainVectorStore(config as any);
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case "vectorize":
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return new VectorizeDB(config as any);
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default:
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throw new Error(`Unsupported vector store provider: ${provider}`);
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}
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436
mem0-ts/src/oss/src/vector_stores/vectorize.ts
Normal file
436
mem0-ts/src/oss/src/vector_stores/vectorize.ts
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@@ -0,0 +1,436 @@
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import Cloudflare from "cloudflare";
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import type { Vectorize, VectorizeVector } from "@cloudflare/workers-types";
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import { VectorStore } from "./base";
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import { SearchFilters, VectorStoreConfig, VectorStoreResult } from "../types";
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interface VectorizeConfig extends VectorStoreConfig {
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apiKey?: string;
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indexName: string;
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accountId: string;
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}
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interface CloudflareVector {
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id: string;
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values: number[];
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metadata?: Record<string, any>;
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}
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export class VectorizeDB implements VectorStore {
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private client: Cloudflare | null = null;
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private dimensions: number;
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private indexName: string;
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private accountId: string;
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constructor(config: VectorizeConfig) {
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this.client = new Cloudflare({ apiToken: config.apiKey });
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this.dimensions = config.dimension || 1536;
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this.indexName = config.indexName;
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this.accountId = config.accountId;
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this.initialize().catch(console.error);
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}
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async insert(
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vectors: number[][],
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ids: string[],
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payloads: Record<string, any>[]
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): Promise<void> {
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try {
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const vectorObjects: CloudflareVector[] = vectors.map(
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(vector, index) => ({
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id: ids[index],
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values: vector,
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metadata: payloads[index] || {},
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})
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);
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const ndjsonPayload = vectorObjects
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.map((v) => JSON.stringify(v))
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.join("\n");
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const response = await fetch(
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`https://api.cloudflare.com/client/v4/accounts/${this.accountId}/vectorize/v2/indexes/${this.indexName}/insert`,
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{
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method: "POST",
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headers: {
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"Content-Type": "application/x-ndjson",
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Authorization: `Bearer ${this.client?.apiToken}`,
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},
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body: ndjsonPayload,
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}
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);
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(
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`Failed to insert vectors: ${response.status} ${errorText}`
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);
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}
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} catch (error) {
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console.error("Error inserting vectors:", error);
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throw new Error(
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`Failed to insert vectors: ${error instanceof Error ? error.message : String(error)}`
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);
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}
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}
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async search(
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query: number[],
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limit: number = 5,
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filters?: SearchFilters
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): Promise<VectorStoreResult[]> {
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try {
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const result = await this.client?.vectorize.indexes.query(
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this.indexName,
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{
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account_id: this.accountId,
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vector: query,
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filter: filters,
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returnMetadata: "all",
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topK: limit,
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}
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);
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return (
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(result?.matches?.map((match) => ({
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id: match.id,
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payload: match.metadata,
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score: match.score,
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})) as VectorStoreResult[]) || []
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); // Return empty array if result or matches is null/undefined
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} catch (error) {
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console.error("Error searching vectors:", error);
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throw new Error(
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`Failed to search vectors: ${error instanceof Error ? error.message : String(error)}`
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);
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}
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}
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async get(vectorId: string): Promise<VectorStoreResult | null> {
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try {
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const result = (await this.client?.vectorize.indexes.getByIds(
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this.indexName,
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{
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account_id: this.accountId,
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ids: [vectorId],
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}
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)) as any;
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if (!result?.length) return null;
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return {
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id: vectorId,
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payload: result[0].metadata,
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};
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} catch (error) {
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console.error("Error getting vector:", error);
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throw new Error(
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`Failed to get vector: ${error instanceof Error ? error.message : String(error)}`
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);
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}
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}
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async update(
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vectorId: string,
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vector: number[],
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payload: Record<string, any>
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): Promise<void> {
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try {
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const data: VectorizeVector = {
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id: vectorId,
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values: vector,
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metadata: payload,
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};
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const response = await fetch(
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`https://api.cloudflare.com/client/v4/accounts/${this.accountId}/vectorize/v2/indexes/${this.indexName}/upsert`,
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{
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method: "POST",
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headers: {
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"Content-Type": "application/x-ndjson",
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Authorization: `Bearer ${this.client?.apiToken}`,
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},
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body: JSON.stringify(data) + "\n", // ndjson format
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}
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);
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(
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`Failed to update vector: ${response.status} ${errorText}`
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);
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}
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} catch (error) {
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console.error("Error updating vector:", error);
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throw new Error(
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`Failed to update vector: ${error instanceof Error ? error.message : String(error)}`
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);
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}
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}
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async delete(vectorId: string): Promise<void> {
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try {
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await this.client?.vectorize.indexes.deleteByIds(this.indexName, {
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account_id: this.accountId,
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ids: [vectorId],
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});
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} catch (error) {
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console.error("Error deleting vector:", error);
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throw new Error(
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`Failed to delete vector: ${error instanceof Error ? error.message : String(error)}`
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);
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}
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}
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async deleteCol(): Promise<void> {
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try {
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await this.client?.vectorize.indexes.delete(this.indexName, {
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account_id: this.accountId,
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});
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} catch (error) {
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console.error("Error deleting collection:", error);
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throw new Error(
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`Failed to delete collection: ${error instanceof Error ? error.message : String(error)}`
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);
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}
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}
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async list(
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filters?: SearchFilters,
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limit: number = 20
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): Promise<[VectorStoreResult[], number]> {
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try {
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const result = await this.client?.vectorize.indexes.query(
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this.indexName,
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{
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account_id: this.accountId,
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vector: Array(this.dimensions).fill(0), // Dummy vector for listing
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filter: filters,
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topK: limit,
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returnMetadata: "all",
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}
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);
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const matches =
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(result?.matches?.map((match) => ({
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id: match.id,
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payload: match.metadata,
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score: match.score,
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})) as VectorStoreResult[]) || [];
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return [matches, matches.length];
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} catch (error) {
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console.error("Error listing vectors:", error);
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throw new Error(
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`Failed to list vectors: ${error instanceof Error ? error.message : String(error)}`
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);
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}
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}
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private generateUUID(): string {
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return "xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx".replace(
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/[xy]/g,
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function (c) {
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const r = (Math.random() * 16) | 0;
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const v = c === "x" ? r : (r & 0x3) | 0x8;
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return v.toString(16);
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}
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);
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}
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async getUserId(): Promise<string> {
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try {
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let found = false;
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for await (const index of this.client!.vectorize.indexes.list({
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account_id: this.accountId,
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})) {
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if (index.name === "memory_migrations") {
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found = true;
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}
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}
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if (!found) {
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await this.client?.vectorize.indexes.create({
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account_id: this.accountId,
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name: "memory_migrations",
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config: {
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dimensions: 1,
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metric: "cosine",
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},
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});
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}
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|
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// Now try to get the userId
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const result: any = await this.client?.vectorize.indexes.query(
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"memory_migrations",
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{
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account_id: this.accountId,
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vector: [0],
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topK: 1,
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returnMetadata: "all",
|
||||
}
|
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);
|
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if (result.matches.length > 0) {
|
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return result.matches[0].metadata.userId as string;
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||||
}
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|
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// Generate a random userId if none exists
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const randomUserId =
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Math.random().toString(36).substring(2, 15) +
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Math.random().toString(36).substring(2, 15);
|
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const data: VectorizeVector = {
|
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id: this.generateUUID(),
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values: [0],
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metadata: { userId: randomUserId },
|
||||
};
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|
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await fetch(
|
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`https://api.cloudflare.com/client/v4/accounts/${this.accountId}/vectorize/v2/indexes/memory_migrations/upsert`,
|
||||
{
|
||||
method: "POST",
|
||||
headers: {
|
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"Content-Type": "application/x-ndjson",
|
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Authorization: `Bearer ${this.client?.apiToken}`,
|
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},
|
||||
body: JSON.stringify(data) + "\n", // ndjson format
|
||||
}
|
||||
);
|
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return randomUserId;
|
||||
} catch (error) {
|
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console.error("Error getting user ID:", error);
|
||||
throw new Error(
|
||||
`Failed to get user ID: ${error instanceof Error ? error.message : String(error)}`
|
||||
);
|
||||
}
|
||||
}
|
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|
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async setUserId(userId: string): Promise<void> {
|
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try {
|
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// Get existing point ID
|
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const result: any = await this.client?.vectorize.indexes.query(
|
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"memory_migrations",
|
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{
|
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account_id: this.accountId,
|
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vector: [0],
|
||||
topK: 1,
|
||||
returnMetadata: "all",
|
||||
}
|
||||
);
|
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const pointId =
|
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result.matches.length > 0 ? result.matches[0].id : this.generateUUID();
|
||||
|
||||
const data: VectorizeVector = {
|
||||
id: pointId,
|
||||
values: [0],
|
||||
metadata: { userId },
|
||||
};
|
||||
await fetch(
|
||||
`https://api.cloudflare.com/client/v4/accounts/${this.accountId}/vectorize/v2/indexes/memory_migrations/upsert`,
|
||||
{
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/x-ndjson",
|
||||
Authorization: `Bearer ${this.client?.apiToken}`,
|
||||
},
|
||||
body: JSON.stringify(data) + "\n", // ndjson format
|
||||
}
|
||||
);
|
||||
} catch (error) {
|
||||
console.error("Error setting user ID:", error);
|
||||
throw new Error(
|
||||
`Failed to set user ID: ${error instanceof Error ? error.message : String(error)}`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
async initialize(): Promise<void> {
|
||||
try {
|
||||
// Check if the index already exists
|
||||
let indexFound = false;
|
||||
for await (const idx of this.client!.vectorize.indexes.list({
|
||||
account_id: this.accountId,
|
||||
})) {
|
||||
if (idx.name === this.indexName) {
|
||||
indexFound = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
// If the index doesn't exist, create it
|
||||
if (!indexFound) {
|
||||
try {
|
||||
await this.client?.vectorize.indexes.create({
|
||||
account_id: this.accountId,
|
||||
name: this.indexName,
|
||||
config: {
|
||||
dimensions: this.dimensions,
|
||||
metric: "cosine",
|
||||
},
|
||||
});
|
||||
|
||||
const properties = ["userId", "agentId", "runId"];
|
||||
|
||||
for (const propertyName of properties) {
|
||||
await this.client?.vectorize.indexes.metadataIndex.create(
|
||||
this.indexName,
|
||||
{
|
||||
account_id: this.accountId,
|
||||
indexType: "string",
|
||||
propertyName,
|
||||
}
|
||||
);
|
||||
}
|
||||
} catch (err: any) {
|
||||
throw new Error(err);
|
||||
}
|
||||
}
|
||||
|
||||
// check for metadata index
|
||||
const metadataIndexes =
|
||||
await this.client?.vectorize.indexes.metadataIndex.list(
|
||||
this.indexName,
|
||||
{
|
||||
account_id: this.accountId,
|
||||
}
|
||||
);
|
||||
const existingMetadataIndexes = new Set<string>();
|
||||
for (const metadataIndex of metadataIndexes?.metadataIndexes || []) {
|
||||
existingMetadataIndexes.add(metadataIndex.propertyName!);
|
||||
}
|
||||
const properties = ["userId", "agentId", "runId"];
|
||||
for (const propertyName of properties) {
|
||||
if (!existingMetadataIndexes.has(propertyName)) {
|
||||
await this.client?.vectorize.indexes.metadataIndex.create(
|
||||
this.indexName,
|
||||
{
|
||||
account_id: this.accountId,
|
||||
indexType: "string",
|
||||
propertyName,
|
||||
}
|
||||
);
|
||||
}
|
||||
}
|
||||
// Create memory_migrations collection if it doesn't exist
|
||||
let found = false;
|
||||
for await (const index of this.client!.vectorize.indexes.list({
|
||||
account_id: this.accountId,
|
||||
})) {
|
||||
if (index.name === "memory_migrations") {
|
||||
found = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (!found) {
|
||||
await this.client?.vectorize.indexes.create({
|
||||
account_id: this.accountId,
|
||||
name: "memory_migrations",
|
||||
config: {
|
||||
dimensions: 1,
|
||||
metric: "cosine",
|
||||
},
|
||||
});
|
||||
}
|
||||
} catch (err: any) {
|
||||
throw new Error(err);
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user