qdrant and Basic-Qdrant-Upload-and-Search-Example

The official Qdrant vector database (A) is complemented by a third-party example repository (B) that demonstrates practical implementation patterns for uploading data and performing semantic searches within Qdrant for AI retrieval applications.

qdrant
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Maintenance 0/25
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Maturity 9/25
Community 12/25
Stars: 29,544
Forks: 2,095
Downloads: 15,117,788
Commits (30d): 214
Language: Rust
License: Apache-2.0
Stars: 2
Forks: 1
Downloads:
Commits (30d): 0
Language: Python
License: MIT
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Stale 6m No Package No Dependents

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/

Built in Rust for reliability under high load, Qdrant supports extended JSON payload filtering alongside vector similarity search, enabling semantic matching with rich metadata constraints. It offers both REST and gRPC interfaces, with official clients for Python, Go, Rust, JavaScript, Java, and .NET, plus integrations for semantic search, image retrieval, recommendations, and anomaly detection use cases.

About Basic-Qdrant-Upload-and-Search-Example

libraryofcelsus/Basic-Qdrant-Upload-and-Search-Example

Example code on how to upload and search a Qdrant Vector Database for Ai Chatbot Retrieval Frameworks

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