1import { PineconeClient } from '@pinecone-database/pinecone';
2
3const pinecone = new PineconeClient();
4await pinecone.init({
5  environment: 'YOUR_ENVIRONMENT',
6  apiKey: 'YOUR_API_KEY'
7});
8
9// Create an index
10await pinecone.createIndex({
11  createRequest: {
12    name: 'my-index',
13    dimension: 1536,
14    metric: 'cosine'
15  }
16});
17
18const index = pinecone.Index('my-index');
19
20// Upsert vectors
21await index.upsert({
22  upsertRequest: {
23    vectors: [{
24      id: 'vec1',
25      values: [0.1, 0.2, 0.3, ...],
26      metadata: { text: 'This is a sample document.' }
27    }]
28  }
29});
30
31// Query the index
32const queryResponse = await index.query({
33  queryRequest: {
34    vector: [0.1, 0.2, 0.3, ...],
35    topK: 5,
36    includeMetadata: true
37  }
38});
39
40console.log(queryResponse);

1import axios from 'axios';
2
3const API_URL = 'https://memflare.com/api';
4const API_KEY = 'YOUR_API_KEY';
5
6const memflare = axios.create({
7  baseURL: API_URL,
8  headers: { Authorization: `Bearer ${API_KEY}` }
9});
10
11// Insert a document
12await memflare.post('/insert-document', {
13  collectionName: 'my-collection',
14  document: {
15    name: 'example.txt',
16    content: 'This is a sample document.'
17  }
18});
19
20// Query the collection
21const results = await memflare.post('/query-collection', {
22  query_text: 'Sample query',
23  collection_name: 'my-collection',
24  limit: 5
25});
26
27console.log(results.data);