euantran / tychos-node

Node.js library for the Tychos API. Connect live data to AI without managing pipelines.

Tychos Node.js Library

The Tychos Node.js library provides convenient access to the Tychos API from applications written in JavaScript and TypeScript. The Tychos API allows you to query live, hosted vector datasets in your LLM application without needing to manage your own vector database / embedding pipelines.

To see the Tychos API in action, you can test out our PubMed Demo App.

Note: this library is meant for server-side usage only

Installation

You don't need this source code unless you want to modify the package. If you just want to use the package, just run:

npm install tychos

Requirements

• Node.js 12 or higher

Usage

The library needs to be configured with your account's secret key which is available via the Tychos Website. Set tychos.apiKey to its value:

const { VectorDataStore } = require('tychos');
const apiKey = "sk_test_12345";

Query live vector datasets

// initialize data store with API key
const dataStore = new VectorDataStore(apiKey)

// list available datasets
const datasets = tychos.list()

// get name of the first dataset's id
console.log(datasets.data[0].name)

// query a single dataset from the data store object
const queryResults = await dataStore.query({
    name: "pub-med-abstracts",
    queryString: "What is the latest research on molecular peptides",
    limit: 5
})

// query multiple datasets and return the global top results
const queryResults = await dataStore.query({
    name: ["arxiv-abstracts", "pub-med-abstracts"],
    queryString: "What is the latest research on molecular peptides",
    limit: 5
})

// print the metadata associated with the first result
console.log(queryResults[0].payload);

Filter queries on metadata fields

You can filter queries of individual datasets by passing a queryFilter object that specifies the field, operator and condition to apply. The following operators are currently available:

Operator	Checks if the field value is...
$eq	equal to the specified value
$ne	not equal to the specified value
$in	within the specified array
$nin	not within the specified array

Example queries using filters:

// filter PubMed query on articles within a particular journal
const queryResults = await dataStore.query({
    name: "pub-med-abstracts",
    queryString: "What is the latest research on molecular peptides",
    queryFilter: {"Journal": {"$eq":"New England Journal of Medicine"}}
    limit: 5
})

// filter ArXiv query on papers written by LeCun, Hinton and Bengio
const queryResults = await dataStore.query({
    name: "arxiv-abstracts",
    queryString: "What is the latest research on molecular peptides",
    queryFilter: {"authors": {"$in":["LeCun", "Hinton", "Bengio"]}}
    limit: 5
})

See the datasets table below for the metadata fields available on each. We are working on adding additional query operators and fields (e.g., date ranges). As we expand datasets, we also plan to make available a set of general filters (e.g., date, author, type) for queries across multiple datasets.

Datasets available

We currently support the full PubMed and ArXiv datasets and have plans to add additional sources in the coming weeks. If there's a particular dataset you'd like to incorporate into your LLM application, feel free to reach out or raise a GitHub issue.

Vector datasets

Dataset	Name	Size	Syncs	Metadata Fields
PubMed (source)	pub-med-abstracts	35.5M documents	Daily at 07:00 UTC	All fields: PMID, PMCID, Title, Abstract, Authors, Abstract_URL, PMC_URL, Journal, Publication Date Query filterable: Authors, Journal
ArXiv (source)	arxiv-abstracts	2.3M documents	Weekly at 07:00 UTC (Sunday)	All fields: id, doi, paper_title, abstract, authors, categories, abstract_url, full_text_url, journal, pub_date, update_date Query filterable: authors, categories, journal

Feedback and support

If you'd like to provide feedback, run into issues, or need support using embeddings, feel free to reach out or raise an issue via GitHub.