Files
spring-ai/vector-stores/spring-ai-qdrant-store
Ilayaperumal Gopinathan ebd29e0959 GH-1826 Fix EmbeddingModel's usage on Document#embedding
- Since the Document object's reference to the `embedding` is deprecated and will be removed, the VectorStore implementations require a way to store the embedding of the corresponding Document objects

     - One way to fix this is, to have the EmbeddingModel#embed to return the embeddings in the same order as that of the Documents passed to it.

       - Since both the Document and embedding collections use the List object, their iteration operation will make sure to keep them in line with the same order.

       - A fix is required to preserve the order when batching strategy is applied.
	  - Updated the Javadoc for BatchingStrategy
          - Fixed the Document List order in TokenCountBatchingStrategy

    - Refactored the vector store implementations to update this change

Resolves #GH-1826
2024-12-05 21:37:27 +01:00
..
2024-10-21 10:24:28 +02:00

Qdrant Vector Store

Reference Documentation

Run locally

Accessing the Web UI

First, run the Docker container:

docker run -p 6333:6333 -p 6334:6334 \
    -v $(pwd)/qdrant_storage:/qdrant/storage:z \
    qdrant/qdrant

Security: Adding API Key to Qdrant Container

To enhance security, you can add an API key to your Qdrant container using the environment variable.

-e QDRANT__SERVICE__API_KEY=<your_generated_api_key_here>

This ensures that only authorized users with the correct API key can access the Qdrant service.

The GUI is available at http://localhost:6333/dashboard

Qdrant references