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Python library for the Tychos API. The data transformation layer for AI.

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Tychos Python Library

The Tychos Python library provides convenient access to the Tychos API from applications written in the Python language. 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.

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:

pip install tychos

Install from source with:

python setup.py install

Requirements

  • Python 2.7+ or Python 3.6+
  • Requests

Usage

The library needs to be configured with your account's secret key which is available via the Tychos Website. Either set the TYCHOS_API_KEY environment variable before using the library:

import tychos
export TYCHOS_API_KEY='sk_a9adj...'

Or initialize the VectorDataStore using an API key:

import tychos
data_store = tychos.VectorDataStore(api_key="sk_a9adj...")

Query live vector datasets

# initialize data store
data_store = tychos.VectorDataStore()

# list available datasets
datasets = data_store.list()

# get name of the first dataset's id
print(datasets['data'][0]['name'])

# query a single dataset from the data store object
query_results = data_store.query(
    name = "pub-med-abstracts", # dataset index can be a string or an array
    query_string = "What is the latest research on molecular peptides", # search string
    limit = 5, # number of results
)

# query multiple datasets and return the global top results
query_results = data_store.query(
    name = ["arxiv-abstracts", "pub-med-abstracts"], # dataset index can be a string or an array
    query_string = "What is the latest research on molecular peptides", # search string
    limit = 5, # number of results (across all datasets queried)
)

# print the metadata associated with the first result
print(query_results[0]['payload'])

Filter queries on metadata fields

You can filter queries of individual datasets by passing a query_filter dict 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
query_results = data_store.query(
    name = "pub-med-abstracts",
    query_string = "What is the latest research on molecular peptides",
    query_filter = {"Journal": {"$eq":"New England Journal of Medicine"}}
    limit = 5,
)

# filter ArXiv query on papers written by LeCun, Hinton and Bengio
query_results = data_store.query(
    name = "arxiv-abstracts",
    query_string = "What is the latest research on molecular peptides",
    query_filter = {"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.

Command-line interface

This library additionally provides a tychos command-line utility to make it easy to interact with the API from your terminal. Run tychos-cli -h for usage.

tychos-cli query --api-key <YOUR-API-KEY> --name pub-med-abstracts --query-string <"Your query string"> --limit 5

Datasets available

We currently support a range of pre-print, research, and patent 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
US Patents (source) us-patents 6.9M patents Quarterly at 07:00 UTC (1st of Quarter) All fields: patent_id, title, summary, claims, patent_url, inventors, classification, type, assignees, location, date_filed, date_granted, term
Query filterable: coming soon!
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
BioRxiv (source) biorxiv 285.5K documents Monthly at 07:00 UTC (Sunday) All fields: doi, title, abstract, authors, category, jatsxml, author_corresponding, author_corresponding_institution, date, date_timestamp, license, published, type
Query filterable: authors, category, date_timestamp
MedRxiv (source) medrxiv 58.2K documents Monthly at 07:00 UTC (Sunday) All fields: doi, title, abstract, authors, category, jatsxml, author_corresponding, author_corresponding_institution, date, date_timestamp, license, published, type
Query filterable: authors, category, date_timestamp

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 a GitHub issue.

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