embex 0.1.1

Embex: A Universal Vector Database ORM

Embex (Python)

The Universal Vector Database ORM. One API for Qdrant, Pinecone, Chroma, LanceDB, and more.

Embex is a high-performance, universal client for vector databases, built on a shared Rust core related to BridgeRust.

🚀 Features

• Unified API: Switch providers instantly. "Write once, run anywhere."
• Performance: Powered by Rust with SIMD acceleration.
• Type Safety: Fully typed Python bindings.

📦 Installation

uv pip install embex

pip install embex

⚡ Quick Start

1. Connect to a Provider

from embex import EmbexClient

# Connect to Qdrant
client = EmbexClient("qdrant", "http://localhost:6333")

# Or use async initialization (required for some providers like LanceDB/Milvus)
# Note: Python client handles async init internally via await if needed,
# or use the async factory if exposed.
# For standard usage, EmbexClient constructor handles most sync/async bridging.

2. Create a Collection

collection = client.collection("my_collection")

# Create with specific dimension and metric
collection.create(768, "cosine")

3. Insert Vectors

collection.insert([
  {
    "id": "1",
    "vector": [0.1, 0.2, ...], # 768 dimensions
    "metadata": {"title": "Hello World", "category": "greeting"}
  }
])

4. Search

results = collection.search(
  vector=[0.1, 0.2, ...], # Query vector
  limit=5
)

for result in results.results:
    print(result.id, result.score, result.metadata)

5. Filtered Search (Builder Pattern)

# Coming soon: Python Builder Pattern
# Currently supported via search() arguments:

results = collection.search(
    vector=[0.1, 0.2, ...],
    limit=10,
    filter={"course": "CS101"}
)

🔌 Supported Providers

Provider	Key	Status
Qdrant	qdrant	Supported
Chroma	chroma	Supported
Pinecone	pinecone	Supported
Weaviate	weaviate	Supported
LanceDB	lancedb	Supported
Milvus	milvus	Supported
PgVector	pgvector	Supported

🔗 Resources

• Main Repository: github.com/bridgerust/bridgerust
• Issues: github.com/bridgerust/bridgerust/issues
• Documentation: Full Docs