ZeroDB vector store for LlamaIndex - AI-native vector database with free embeddings, semantic search, and RAG support. Pinecone alternative.
Project description
llama-index-vector-stores-zerodb
ZeroDB vector store integration for LlamaIndex - the AI-native vector database with free embeddings and sub-millisecond semantic search.
Why ZeroDB?
- Free embeddings - BAAI/bge-small-en-v1.5 (384-dim) powered by TEI, no OpenAI costs
- Sub-millisecond search - pgvector with HNSW indexes
- Zero infrastructure - fully managed, no servers to run
- Instant provisioning -
POST /api/v1/instant-dbgets you a database in one request - Built for agents - MCP server, memory API, event streams
Installation
pip install llama-index-vector-stores-zerodb
Quick Start
from llama_index_zerodb import ZeroDBVectorStore
from llama_index.core import VectorStoreIndex, Document
# Initialize (get your API key at ainative.studio)
vector_store = ZeroDBVectorStore(
api_key="your-api-key",
project_id="your-project-id",
)
# Build index from documents
documents = [
Document(text="ZeroDB is an AI-native vector database"),
Document(text="Semantic search finds meaning, not keywords"),
]
index = VectorStoreIndex.from_documents(documents, vector_store=vector_store)
# Query
query_engine = index.as_query_engine()
response = query_engine.query("What is ZeroDB?")
print(response)
Use as a Standalone Vector Store
from llama_index_zerodb import ZeroDBVectorStore
from llama_index.core import VectorStoreIndex
# Connect to existing vectors
vector_store = ZeroDBVectorStore(
api_key="your-api-key",
project_id="your-project-id",
)
# Build index from existing store
index = VectorStoreIndex.from_vector_store(vector_store)
# Query
retriever = index.as_retriever(similarity_top_k=5)
results = retriever.retrieve("semantic search performance")
for node in results:
print(f"{node.score:.3f}: {node.text[:100]}")
Get a Free API Key
- Sign up at ainative.studio
- Create a ZeroDB project
- Copy your API key
Or get an instant database with no signup:
curl -X POST https://api.ainative.studio/api/v1/public/instant-db
Links
License
MIT - Built by AINative Studio
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file llama_index_vector_stores_zerodb-0.1.0.tar.gz.
File metadata
- Download URL: llama_index_vector_stores_zerodb-0.1.0.tar.gz
- Upload date:
- Size: 4.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f7edd87039bb8a904ad3666dc54a74ebd4f5a9a7a63baa2318aae25f44305cf7
|
|
| MD5 |
c70cec63cb4325b88c552d61a728044b
|
|
| BLAKE2b-256 |
dd6d927fc67abc5904c697f0bdfd4bf28d2923530f17d306038be2ca9a5229d6
|
File details
Details for the file llama_index_vector_stores_zerodb-0.1.0-py3-none-any.whl.
File metadata
- Download URL: llama_index_vector_stores_zerodb-0.1.0-py3-none-any.whl
- Upload date:
- Size: 5.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f294721472516f149385b15ca12988073be23b7fef779f6637cd259c790bd044
|
|
| MD5 |
6bc68ab7973e7d0a0ee067334bca4824
|
|
| BLAKE2b-256 |
b3e1f23c554b0770f07fd19dce59bb83bcd7d3142de7785006e21fa5ed8aed02
|