Embedbase

Seamless data connections to LLMs

Open-source API & SDK to sync your data and easily hook them up to LLMs

Used by AVA and serving 100k request a day

Try Embedbase Cloud now · Request Feature · Report Bug

Check out the docs for more info.

Getting started
Javascript SDK
Docs and support
Contributing

The 3 ways to use Embedbase

Embedbase Cloud: Build embeddings-powered apps in minutes | npm i embedbase-js | ⏱️ 3min
Embedbase.py: Choose your own db, embeddings models, and get started with a simple | pip install embedbase | ⏱️ 5 min
Embedbase self-hosted: Get Embedbase Cloud on your infra | docker-compose up | ⏱️ 15 min

What are people building

Getting started

Let's install Python dependencies:

pip install embedbase sentence-transformers

Run a local-first instance of Embedbase:

embedbase run

🔥 Embedbase now runs! Look here to see how to use the sdk

ℹ️ Look at the code you just ran here, feel free to modify it to your needs.

Managed Instance

The fastest way to get started with Embedbase is signing up for free to Embedbase Cloud.

How to use

SDK

npm i embedbase-js

import { createClient } from 'embedbase-js'

const question = 'What can I do with Embedbase API?'

const embedbase = createClient(
  'https://api.embedbase.xyz',
  'api-key')

const context = await embedbase
.dataset('embedbase-docs')
.createContext('What can I do with Embedbase API?', { limit: 3 });

console.log(context) 
[
  "Embedbase API allows to store unstructured data...",
  "Embedbase API has 3 main functions a) provides a plug and play solution to store embeddings b) makes it easy to connect to get the right data into llms c)..",
  "Embedabase API is self-hostable...",
]

// refer to https://github.com/openai/openai-node for the exact api
openai.createCompletion(
  `Write a response to question: ${question} 
  based on the follwing context ${context.toString()}`
)
// answer:
// You can use the Embedbase API to store unstructured data and then use the data to connect it to LLMs

Inserting data

const URL = 'http://localhost:8000'
const VAULT_ID = 'people'
// if using the hosted version
const API_KEY = '<https://app.embedbase.xyz/signup>'
fetch(`${URL}/v1/${VAULT_ID}`, {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      // if using the hosted version, uncomment
      // 'Authorization': `Bearer ${API_KEY}`
    },
    body: JSON.stringify({
      documents: [{
        data: 'Elon is sipping a tea on Mars',
      }],
    }),
  });

Searching

fetch(`${URL}/v1/${VAULT_ID}/search`, {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      // 'Authorization': `Bearer ${API_KEY}`
    },
    body: JSON.stringify({
      query: 'Something about a red planet',
    }),
  });

Result:

{
  "query": "Something about a red planet",
  "similarities": [
    {
      "score": 0.828773,
      "id": "ABCU75FEBE",
      "data": "Elon is sipping a tea on Mars",
    }
  ]
}

Docs and support

Check out our tutorials for step-by-step guides, how-to's, and best practices, our documentation is powered by GPT-4, so you can ask question directly.

Ask a question in our Discord community to get support.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

MhrnMhrn/embedbase