Python Client library for the Qdrant vector search engine.

Python Qdrant Client

Client library and SDK for the Qdrant vector search engine.

Library contains type definitions for all Qdrant API and allows to make both Sync and Async requests.

Client allows calls for all Qdrant API methods directly. It also provides some additional helper methods for frequently required operations, e.g. initial collection uploading.

See QuickStart for more details!

Installation

pip install qdrant-client

Features

• Type hints for all API methods
• Local mode - use same API without running server
• REST and gRPC support
• Minimal dependencies
• Extensive Test Coverage

Local mode

Python client allows you to run same code in local mode without running Qdrant server.

Simply initialize client like this:

from qdrant_client import QdrantClient

client = QdrantClient(":memory:")
# or
client = QdrantClient(path="path/to/db")  # Persists changes to disk

Local mode is useful for development, prototyping and testing.

• You can use it to run tests in your CI/CD pipeline.
• Run it in Colab or Jupyter Notebook, no extra dependencies required. See an example
• When you need to scale, simply switch to server mode.

Connect to Qdrant server

To connect to Qdrant server, simply specify host and port:

from qdrant_client import QdrantClient

client = QdrantClient(host="localhost", port=6333)
# or
client = QdrantClient(url="http://localhost:6333")

You can run Qdrant server locally with docker:

docker run -p 6333:6333 qdrant/qdrant:latest

See more launch options in Qdrant repository.

Connect to Qdrant cloud

You can register and use Qdrant Cloud to get a free tier account with 1GB RAM.

Once you have your cluster and API key, you can connect to it like this:

from qdrant_client import QdrantClient

qdrant_client = QdrantClient(
    url="https://xxxxxx-xxxxx-xxxxx-xxxx-xxxxxxxxx.us-east.aws.cloud.qdrant.io:6333",
    api_key="<your-api-key>",
)

Inference API

Qdrant Client has Inference API that allows to seamlessly create embeddings and use them in Qdrant. Inference API can be used locally with FastEmbed or remotely with models available in Qdrant Cloud.

Local Inference with FastEmbed

pip install qdrant-client[fastembed