qdrant

The Qdrant plugin integrates the Qdrant vector database with the Genkit AI development framework. It enables developers to easily build retrieval-augmented generation (RAG) applications by providing standardized indexer and retriever components.

Key Features

• Qdrant Integration — Connects Genkit applications to Qdrant vector stores for efficient similarity search.
• Dual Language Support — Offers implementations in both JavaScript and Go, catering to different tech stacks.
• Configurable Embedders — Supports specifying embedding models (like Google AI's text-embedding-004) for vector generation.
• Flexible Payload Mapping — Allows customization of payload field names for document content, metadata, and data types.
• Collection Management — Provides options for Qdrant collection creation and client parameter configuration.

Philosophy

The plugin is designed to simplify the integration of powerful vector search capabilities into Genkit workflows, following Genkit's plugin architecture for modular and extensible AI application development.