Custom embeddings

import { MossClient } from '@moss-dev/moss'

const client = new MossClient(process.env.MOSS_PROJECT_ID!, process.env.MOSS_PROJECT_KEY!)

// Your embedding function - any model, as long as dimensions are consistent.
async function embed(text: string): Promise<number[]> {
  // ...call your model or embedding API and return the vector
}

// Index with precomputed vectors. modelId: 'custom' -> Moss does not embed.
await client.createIndex('tickets', [
  { id: '1', text: 'Customer asked about billing', embedding: await embed('Customer asked about billing') },
  { id: '2', text: 'Refund requested for duplicate charge', embedding: await embed('Refund requested for duplicate charge') },
], { modelId: 'custom' })

await client.loadIndex('tickets') // required before querying

// Query with your own query vector (required for custom embeddings).
const queryVector = await embed('billing problem')
const results = await client.query('tickets', 'billing problem', { topK: 3, embedding: queryVector })
results.docs.forEach(d => console.log(d.id, d.score, d.text))

const session = await client.session('conv-123', 'custom')

await session.addDocs([
  { id: '1', text: 'Customer asked about billing', embedding: await embed('Customer asked about billing') },
])

const hits = await session.query('billing problem', { topK: 3, embedding: await embed('billing problem') })