Quick Start

Follow the steps below to install the VectorX SDK and set up your environment.

Requirements

Python ≥ 3.8
pip (Python package manager)
Works on Linux, macOS, and Windows

Installation

To install the SDK:


pip install vecx

Set Up VectorX DB and Create Index

Following snippet can be followed to initialize vectorx and index creation.


from vecx.vectorx import VectorX
 
# Initialize client with your API token
vx = VectorX(token="your-token-here")
 
# Create a new index
vx.create_index(
    name="my_index",
    dimension=768,  # Your vector dimension
    space_type="cosine"  # Distance metric (cosine, l2, ip)
)
 
# Get index reference
index = vx.get_index(name="my_index")
 
# Insert vectors
index.upsert([
    {
        "id": "doc1",
        "vector": [0.1, 0.2, 0.3, ...],  # Your vector data with specified dimension
        "meta": {"text": "Example document"},
        "filter":{"category": "reference"} # Optional filter
    }
])
 
# Query similar vectors
results = index.query(
    vector=[0.2, 0.3, 0.4, ...],  # Query vector with specified dimenension
    top_k=10,
    filter=[{"category": {"$eq":"reference"}}]  # Optional filter
)
 
# Process results
for item in results:
    print(f"ID: {item['id']}, Similarity: {item['similarity']}")
    print(f"Metadata: {item['meta']}")