helix-py

Helix-DB | Homepage | Documentation

Helix-py is a python library for interacting with helix-db a graph-vector database written in rust. This library will make it easy to quickly setup a rag agent with your documents and favorite model.

Features

Queries

helix-py using a pytorch like front-end to creating queries. Like you would define a neural network forward pass, you can do the same thing for a helix-db query. We provide some default queries in helix/client.py to get started with inserting and search vectors, but you can also define you're own queries if you plan on doing more complex things. For example, for this hql query

QUERY addUser(name: String, age: Integer) =>
  AddV<User>({Name: name, Age: age})
  RETURN "Success"

you would write

class addUser(Query):
    def __init__(self, user: Tuple[str, int]):
        super().__init__()
        self.user = user
    def query(self):
        return [{ "Name": self.user[0], "Age": self.user[1] }]
    def response(self, response):
        pass

for your python script.

Loader

The loader (helix/loader.py) currently supports .parquet, .fvecs, and .csv data. Simply pass in the path to your file or files and the columns you want to process and the loader does the rest for you and is easy to integrate with your queries

Installation

git clone https://github.com/HelixDB/helix-py
cd helix-py
python3 -m pip install -e . # use a venv if needed

See getting started for more information on installing helix-db

curl -sSL "https://install.helix-db.com" | bash
helix install
helix init
helix deploy --local

Now you're good to go! See examples/ for how to use helix-py. See helixdb-queries/queries.hx for the queries installed with helix deploy --local. You can add your own here and write corresponding Query classes in your python script.

Documentation

Proper docs are coming soon. See examples/tutorial.py for now.

import helix
from helix.client import hnswload, hnswsearch

db = helix.Client(local=True)
data = helix.Loader("path/to/data", cols=["openai"])
ids = db.query(hnswload(data)) # build hnsw index

my_query = [0.32, ..., -1.321]
nearest = db.query(hnswsearch(my_query)) # query hnsw index

Roadmap

• Goal 1: default data loading and http client up and running
• Goal 2: full working default queries
• Goal 3: working rag pipeline with default queries and workflow
• Goal 4: processing, chunking, tokenizing, vectorising data
• Goal 5: some sort of knowledge storing and loading system to build a brain for an llm (for now)

License

helix-py is licensed under the GNU General Public License v3.0 (GPL-3.0).