turbopuffer 0.1.4

Python Client for accessing the turbopuffer API

turbopuffer Python Client

The official Python client for accessing the turbopuffer API.

Usage

1. Install the turbopuffer package and set your API key.

$ pip install turbopuffer

Or if you're able to run C binaries for JSON encoding, use:

$ pip install turbopuffer[fast]

2. Start using the API

import turbopuffer as tpuf
tpuf.api_key = 'your-token' # Alternatively: export=TURBOPUFFER_API_KEY=your-token

# Open a namespace
ns = tpuf.Namespace('hello_world')

# Upsert your dataset
ns.upsert(
    ids=[1, 2],
    vectors=[[0.1, 0.2], [0.3, 0.4]],
    attributes={'name': ['foo', 'foos']}
)

# Alternatively, upsert using a row iterator
ns.upsert(
    {
        'id': id,
        'vector': [id/10, id/10],
        'attributes': {'name': 'food'}
    } for id in range(3, 10)
)

# Query your dataset
vectors = ns.query(
    vector=[0.15, 0.22],
    distance_metric='cosine_distance',
    top_k=10,
    filters={ 'name': [['Glob', 'foo*'], ['NotEq', 'food']] },
    include_attributes=['name'],
    include_vectors=True
)
print(vectors)
# [
#   VectorRow(id=2, vector=[0.30000001192092896, 0.4000000059604645], attributes={'name': 'foos'}, dist=0.001016080379486084),
#   VectorRow(id=1, vector=[0.10000000149011612, 0.20000000298023224], attributes={'name': 'foo'}, dist=0.009067952632904053)
# ]

Endpoint Documentation

For more details on request parameters and query options, check the docs at https://turbopuffer.com/docs