Qdrant

Run more texts through the embeddings and add to the VectorStore.

Run more texts through the embeddings and add to the VectorStore.

Return docs most similar to query.

Return docs most similar to query.

Return docs most similar to query.

Return docs most similar to query.

Return docs most similar to embedding vector.

Return docs most similar to embedding vector.

Return docs most similar to embedding vector.

Return docs most similar to embedding vector.

Return docs selected using the maximal marginal relevance.

Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.

Return docs selected using the maximal marginal relevance.

Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.

Return docs selected using the maximal marginal relevance.

Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.

Return docs selected using the maximal marginal relevance.

Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.

Return docs selected using the maximal marginal relevance.

Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.

Return docs selected using the maximal marginal relevance.

Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.

Delete by vector ID or other criteria.

Delete by vector ID or other criteria.

Construct Qdrant wrapper from a list of texts.

Get instance of an existing Qdrant collection.

This method will return the instance of the store without inserting any new embeddings.

Construct Qdrant wrapper from a list of texts.