@oramacloud/client v1.3.19

Orama Cloud Client

Install

npm i @oramacloud/client

Integrating with Orama Cloud

import { OramaClient } from "@oramacloud/client";

const client = new OramaClient({
  endpoint: "<Your Orama Cloud Endpoint>",
  api_key: "<Your Orama Cloud API Key>",
});

const results = await client.search({
  term: "red leather shoes",
});

Advanced search

const results = await client.search({
  term: "red leather shoes",
  where: {
    price: {
      lte: 9.99,
    },
    gender: "unisex",
  },
  limit: 5,
  offset: 1,
});

Generating embeddings via the Secure Proxy

import { OramaProxy } from "@oramacloud/client";

const proxy = new OramaClient({
  api_key: "<Your Orama Secure Proxy API Key>",
});

const embeddings = await proxy.generateEmbeddings(
  "red leather shoes",
  "openai/text-embedding-ada-002"
);

console.log(embeddings);
// [-0.019633075, -0.00820422, -0.013555876, -0.011825735, 0.006641511, -0.012948156, ...]

Available models:

• orama/gte-small. 384 dimensions, operated by Orama Cloud (preferred)
• orama/gte-medium. 768 dimensions, operated by Orama Cloud
• orama/gte-large. 1024 dimensions, operated by Orama Cloud
• openai/text-embedding-ada-002. 1536 dimensions, proxied to OpenAI
• openai/text-embedding-3-small. 1536 dimensions, proxied to OpenAI
• openai/text-embedding-3-large. 3072 dimensions, proxied to OpenAI

Generating chat completions via the Secure Proxy

You can generate chat completions via the Secure Proxy in two different ways:

Returning a single string

import { OramaProxy } from "@oramacloud/client";

const proxy = new OramaClient({
  api_key: "<Your Orama Secure Proxy API Key>",
});

const chatParams = {
  model: "openai/gpt-4",
  messages: [{ role: "user", content: "Who is Michael Scott?" }],
};

const response = await proxy.chat(chatParams);
console.log(response);

// "Michael Scott is a fictional character from the television show "The Office" (US version) ..."

Available models:

• openai/gpt-4o
• openai/gpt-4o-mini
• openai/gpt-4-turbo
• openai/gpt-4
• openai/gpt-3.5-turbo

Returning a stream (via async iterators)

import { OramaProxy } from "@oramacloud/client";

const proxy = new OramaClient({
  api_key: "<Your Orama Secure Proxy API Key>",
});

const chatParams = {
  model: "openai/gpt-4",
  messages: [{ role: "user", content: "Who is Michael Scott?" }],
};

for await (const message of proxy.chatStream(chatParams)) {
  console.log(message);
}

// Michael
// Scott is
// a fictional
//  character from the
//  television show
// "The
// Office" (US
// version)
// ...

Available models:

• openai/gpt-4o
• openai/gpt-4o-mini
• openai/gpt-4-turbo
• openai/gpt-4
• openai/gpt-3.5-turbo

With React

import { OramaCloud, useSearch } from "@oramacloud/client/react";

export function App() {
  return (
    <OramaCloud
      endpoint="<Your Orama Cloud Endpoint>"
      apiKey="<Your Orama Cloud API Key>"
    >
      <Search />
    </OramaCloud>
  );
}

function Search() {
  const { results, error } = useSearch({
    term: "red leather shoes",
    limit: 10,
    offset: 5,
  });

  return (
    <>
      {results.hits.map((hit) => {
        <div key={hit.id}>
          <p> {hit.document.myCustomProperty} </p>
        </div>;
      })}
    </>
  );
}

With Vue

Import the composable into your component and it's ready to use.

<template>
  <li v-for="hit in results?.hits" :key="hit.id">
    {{ hit.id }}
  </li>
</template>

<script setup>
import { useSearch } from "@oramacloud/client/vue";
import { orama } from './orama'

const { results } = useSearch({
  cloudConfig: {
    apiKey: "<Your Orama Cloud API Key>",
    endpoint: "<Your Orama Cloud Endpoint>",
  },
  term: "guitar",
  limit: 5
});
</script>

Identifying users

Usage with browsers

1. Call the .identify() method with the user's unique identifier.
2. Call .reset() when users log out.

Note: we suggest developers to always call .identify() when users sign-up, log-in or when the user re-opens the application in a logged-in state.

Example or already logged in state:

import { OramaClient } from "@oramacloud/client";

const client = new OramaClient({
  endpoint: "<Your Orama Cloud Endpoint>",
  api_key: "<Your Orama Cloud API Key>",
});

client.identify("<Your unique User ID>");

client.search({
  term: "red leather shoes",
});

Upon logging out:

client.reset();

Usage with server-side applications

1. Call the .identify() method with the user's unique identifier.
2. Call .reset() when users log out.

OramaClient will always generate a new userId upon initialization, so we suggest developers to call the .reset() function even when users are not necessarily identified. This will ensure that the client is not associated with the previous user, thus preventing improper data association between sessions.

Usage of Alias

Aliases are employed to link multiple identifiers to a single user, enabling the tracking of anonymous users across different sessions. This is particularly beneficial for monitoring users who are not logged in or who access the platform from various devices.

import { OramaClient } from "@oramacloud/client";

const client = new OramaClient({
  endpoint: "<Your Orama Cloud Endpoint>",
  api_key: "<Your Orama Cloud API Key>",
});

// Sets the alias for the current user
client.alias("<Unique Alias ID>");

client.search({
  term: "red leather shoes",
});