llama-index-vector-stores-zeusdb 0.1.0

LlamaIndex integration for ZeusDB vector database. Enterprise-grade RAG with high-performance vector search.

LlamaIndex ZeusDB Integration

ZeusDB vector database integration for LlamaIndex. Connect LlamaIndex's RAG framework with high-performance, enterprise-grade vector database.

Features

• Production Ready: Built for enterprise-scale RAG applications
• Advanced Filtering: Comprehensive metadata filtering with complex operators
• MMR Support: Maximal Marginal Relevance for diverse result sets
• Async Helpers: Async wrappers for add, query, delete, and clear

Installation

pip install llama-index-vector-stores-zeusdb

Quick Start

from llama_index.core import VectorStoreIndex, Document, StorageContext
from llama_index.vector_stores.zeusdb import ZeusDBVectorStore
from llama_index.embeddings.openai import OpenAIEmbedding
from llama_index.core import Settings

# Set up embedding model
Settings.embed_model = OpenAIEmbedding(model="text-embedding-3-small")

# Create ZeusDB vector store
vector_store = ZeusDBVectorStore(
    dim=1536,  # OpenAI embedding dimension
    distance="cosine",
    index_type="hnsw"
)

# Create storage context
storage_context = StorageContext.from_defaults(vector_store=vector_store)

# Create documents
documents = [
    Document(text="ZeusDB is a high-performance vector database."),
    Document(text="LlamaIndex provides RAG capabilities."),
    Document(text="Vector search enables semantic similarity.")
]

# Create index and store documents
index = VectorStoreIndex.from_documents(
    documents, 
    storage_context=storage_context
)

# Query the index
query_engine = index.as_query_engine()
response = query_engine.query("What is ZeusDB?")
print(response)

Configuration

Parameter	Description	Default
dim	Vector dimension	Required
distance	Distance metric (cosine, l2, l1)	cosine
index_type	Index type (hnsw)	hnsw
m	HNSW connectivity parameter	16
ef_construction	HNSW build-time search depth	200

Documentation

For comprehensive guides, advanced examples, and configuration options, visit:

ZeusDB LlamaIndex Documentation

Requirements

• Python 3.10+
• llama-index-core >= 0.13.6
• zeusdb >= 0.0.8

Contributing

Contributions are welcome! Please see our Contributing Guidelines for details.

Support

• Issues: GitHub Issues
• Documentation: docs.zeusdb.com
• Email: [e-mail]

License

This project is licensed under the MIT License - see the LICENSE file for details.