import { create, search, insert } from 'npm:@orama/orama'

import { create, insert, remove, search, searchVector } from '@orama/orama'

const db = await create({
  schema: {
    name: 'string',
    description: 'string',
    price: 'number',
    embedding: 'vector[1536]', // Vector size must be expressed during schema initialization
    meta: {
      rating: 'number',
    },
  },
})

await insert(db, {
  name: 'Wireless Headphones',
  description: 'Experience immersive sound quality with these noise-cancelling wireless headphones.',
  price: 99.99,
  embedding: [...],
  meta: {
    rating: 4.5,
  },
})

await insert(db, {
  name: 'Smart LED Bulb',
  description: 'Control the lighting in your home with this energy-efficient smart LED bulb, compatible with most smart home systems.',
  price: 24.99,
  embedding: [...],
  meta: {
    rating: 4.3,
  },
})

await insert(db, {
  name: 'Portable Charger',
  description: 'Never run out of power on-the-go with this compact and fast-charging portable charger for your devices.',
  price: 29.99,
  embedding: [...],
  meta: {
    rating: 3.6,
  },
})

const searchResult = await search(db, {
  term: 'headphones',
})

{
  elapsed: {
    raw: 99512,
    formatted: '99μs',
  },
  hits: [
    {
      id: '41013877-56',
      score: 0.925085832971998432,
      document: {
        name: 'Wireless Headphones',
        description: 'Experience immersive sound quality with these noise-cancelling wireless headphones.',
        price: 99.99,
        meta: {
          rating: 4.5
        }
      }
    }
  ],
  count: 1
}

const searchResult = await search(db, {
  term: 'immersive sound quality',
  properties: ['description'],
})

{
  elapsed: {
    raw: 21492,
    formatted: '21μs',
  },
  hits: [
    {
      id: '41013877-56',
      score: 0.925085832971998432,
      document: {
        name: 'Wireless Headphones',
        description: 'Experience immersive sound quality with these noise-cancelling wireless headphones.',
        price: 99.99,
        meta: {
          rating: 4.5
        }
      }
    }
  ],
  count: 1
}

const searchResult = await search(db, {
  term: 'immersive sound quality',
  where: {
    price: {
      lte: 199.99
    },
    rating: {
      gt: 4
    }
  },
})

const searchResult = await searchVector(db, {
  mode: 'vector', // or 'hybrid'
  vector: {
    value: [...], // OpenAI embedding or similar vector to be used as an input
    property: 'embedding' // Property to search through. Mandatory for vector search
  }
})

import { create } from '@orama/orama'
import { pluginSecureProxy } from '@orama/plugin-secure-proxy'

const secureProxy = secureProxyPlugin({
  apiKey: '<YOUR-PUBLIC-API-KEY>',
  defaultProperty: 'embedding', // the default property to perform vector and hybrid search on
  model: 'openai/text-embedding-ada-002' // the model to use to generate embeddings
})

const db = await create({
  schema: {
    name: 'string',
    description: 'string',
    price: 'number',
    embedding: 'vector[1536]',
    meta: {
      rating: 'number',
    },
  },
  plugins: [secureProxy]
})

const resultsHybrid = await search(db, {
  mode: 'vector', // or 'hybrid'
  term: 'Videogame for little kids with a passion about ice cream',
  where: {
    price: {
      lte: 19.99
    },
    'meta.rating': {
      gte: 4.5
    }
  }
})

import { create, insert } from '@orama/orama'

const db = await create({
  schema: {
    name: 'string',
    location: 'geopoint'
  }
})

await insert(db, { name: 'Duomo di Milano', location: { lat: 45.46409, lon: 9.19192 } })
await insert(db, { name: 'Piazza Duomo',    location: { lat: 45.46416, lon: 9.18945 } })
await insert(db, { name: 'Piazzetta Reale', location: { lat: 45.46339, lon: 9.19092 } })

const searchResult = await search(db, {
  term: 'Duomo',
  where: {
    location: {           // The property we want to filter by
      radius: {           // The filter we want to apply (in that case: "radius")
        coordinates: {    // The central coordinate
          lat: 45.4648, 
          lon: 9.18998
        },
        unit: 'm',        // The unit of measurement. The default is "m" (meters)
        value: 1000,      // The radius length. In that case, 1km
        inside: true      // Whether we want to return the documents inside or outside the radius. The default is "true"
      }
    }
  }
})