diff --git a/docs-website/reference/integrations-api/qdrant.md b/docs-website/reference/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference/integrations-api/qdrant.md +++ b/docs-website/reference/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:** diff --git a/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md index 5bc7fc3a0e..9efadf3095 100644 --- a/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md +++ b/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md @@ -357,8 +357,9 @@ Asynchronously run the Sparse Embedding Retriever on the given input data. ### QdrantHybridRetriever -A component for retrieving documents from an QdrantDocumentStore using both dense and sparse vectors -and fusing the results using Reciprocal Rank Fusion. +A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors. + +Fuses the results using Reciprocal Rank Fusion. Usage example: @@ -550,8 +551,9 @@ Batch elements of an iterable into fixed-length chunks or blocks. ### QdrantDocumentStore -A QdrantDocumentStore implementation that you can use with any Qdrant instance: in-memory, disk-persisted, -Docker-based, and Qdrant Cloud Cluster deployments. +A QdrantDocumentStore implementation that you can use with any Qdrant instance. + +Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments. Usage example by creating an in-memory instance: @@ -736,6 +738,7 @@ write_documents( ``` Writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -761,6 +764,7 @@ write_documents_async( ``` Asynchronously writes documents to Qdrant using the specified policy. + The QdrantDocumentStore can handle duplicate documents based on the given policy. The available policies are: @@ -1042,8 +1046,9 @@ count_unique_metadata_by_filter_async( ) -> dict[str, int] ``` -Asynchronously returns the number of unique values for each specified metadata field among documents that -match the filters. +Asynchronously returns the number of unique values for each specified metadata field among documents. + +Only documents that match the filters are considered. **Parameters:**