qdrant and qdrant-client

The database engine and its official Python client library are complements designed to be used together, where the client provides programmatic access to Qdrant's vector search functionality.

qdrant
81
Verified
qdrant-client
80
Verified
Maintenance 22/25
Adoption 15/25
Maturity 25/25
Community 19/25
Maintenance 17/25
Adoption 15/25
Maturity 25/25
Community 23/25
Stars: 29,544
Forks: 2,095
Downloads:
Commits (30d): 214
Language: Rust
License: Apache-2.0
Stars: 1,240
Forks: 202
Downloads:
Commits (30d): 6
Language: Python
License: Apache-2.0
No risk flags
No risk flags

About qdrant

qdrant/qdrant

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

This helps AI developers and data scientists build and manage powerful search, recommendation, and classification applications. It takes high-dimensional numerical data (vectors/embeddings) and associated information (payloads) as input. It then allows users to quickly search for similar items, apply complex filters, and power various AI applications, making it ideal for those working with neural networks and semantic data.

AI-application-development semantic-search recommendation-engines machine-learning-operations data-science

About qdrant-client

qdrant/qdrant-client

Python client for Qdrant vector search engine

This is a Python tool that helps developers interact with a vector search engine to find similar data points. You can input text, images, or other data, and it helps store them as 'vectors' and then quickly find other vectors that are semantically similar. This is primarily used by developers building applications that require searching and retrieving information based on meaning, rather than exact keywords.

semantic-search information-retrieval vector-databases AI-application-development data-indexing

Scores updated daily from GitHub, PyPI, and npm data. How scores work