vdblite 0.1.4

Vector Database Lite

Vector Database Lite (VDBLITE)

Vector Database Lite (like SQLITE but for vector search)

To discuss VDBLITE and ask general questions, use https://github.com/daveshap/VDBLITE/discussions

Quickstart

1. Install using pip install vdblite
2. Run a test with the following code:

import vdblite
from time import time
from uuid import uuid4
import sys
from pprint import pprint as pp


if __name__ == '__main__':
    vdb = vdblite.Vdb()
    dimension = 12    # dimensions of each vector                         
    n = 200    # number of vectors                   
    np.random.seed(1)             
    db_vectors = np.random.random((n, dimension)).astype('float32')
    print(db_vectors[0])
    for vector in db_vectors:
        info = {'vector': vector, 'time': time(), 'uuid': str(uuid4())}
        vdb.add(info)
    vdb.details()
    results = vdb.search(db_vectors[10])
    pp(results)

Class Vdb Methods

Vdb.add(payload)

# add a dictionary
info = dict()
vdb.add(info)
# or a list of dictionaries
info = list()
vdb.add(info)

Add a an arbitrary number of records to self.data (master list of data) of your Vdb object. No checks are performed beyond data type.

payload

Payload must be either a list or dict variable type. For instance:

info = {
	'time': 123.456789,
	'vector': [0.1, 0.1, 0.1, 0.1, 0.1],
	'uuid': '174657a5-ba76-47a8-a121-5fda05dde560',
	'content': 'lorem ipsum...',
}

or

info = [
	{'...'},
	{'...'},
	{'...'},
]

Vdb.delete(field, value, firstonly=False)

# delete all records with timestamp at UNIX time of 123.456789
vdb.delete('timestamp', 123.456789, False)

Delete record(s) with fields that match a given value

field

Specify which element within each record to match for deletion

value

Specify value to be matched for deletion

firstonly

Optional. False by default. Will delete all records with fields that match value. Set to True if you only want to delete a single record

Vdb.search(vector, field='vector', count=5)

results = vdb.search([1.0, 0.0], 'vector', 5)

Search for n number of records that are most similar to vector (cosine similarity). Specify field if searching any other field than vector.

vector

1-dimensional numpy array to match your query. Performs cosine similarity against all vectors in self.data

field='vector'

Optional. Specify which field contains the vector for comparison. Records can contain more than one vector. For instance you may have vectors of different dimensionality, or from different models for different purposes.

count=5

Optional. Specify number of matches to return.

Vdb.bound(field, lower_bound, upper_bound)

results = vdb.bound('time', 123.456789, 987.654321)

Return all records with field value between lower_bound and upper_bound e.g. all records with a timestamp between two specific values.

field

Specify which field to compare in all records.

lower_bound

Minimum threshold to return.

upper_bound

Maximum threshold to return.

Vdb.purge()

Delete self.data from memory and reinstantiate.

Vdb.save(filepath)

vdb.save('my_data.vdb')

Save VDB data to file

filepath

Relative or absolute filepath of save file

Vdb.load(filepath)

vdb = Vdb()
vdb.load('my_data.vdb')

Load saved VDB data into memory

filepath

Relative or absolute filepath of save file