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Parameters

ParameterTypeDefaultDescription
configConfigRequiredA validated and immutable Config object containing all necessary parameters for the provider’s operation

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Functions

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connect

Establishes a connection to the Qdrant vector database. This method uses the connection parameters from self._config.core to initialize the QdrantClient based on the specified operational mode. Raises:
  • VectorDBConnectionError: If the connection fails for any reason.

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disconnect

Gracefully terminates the connection to the Qdrant database.

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disconnect_async

Async version of disconnect for proper async cleanup.

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is_ready

Performs a health check to ensure the Qdrant instance is responsive. Returns:
  • bool: True if the database is connected and responsive, False otherwise.

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create_collection

Creates the collection in Qdrant according to the full framework config. This method handles the recreate_if_exists logic and translates the framework configuration into Qdrant-specific parameters. Raises:
  • VectorDBConnectionError: If not connected to Qdrant to create a collection.
  • VectorDBError: If the collection creation fails.

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delete_collection

Permanently deletes the collection specified in the config. Raises:
  • VectorDBConnectionError: If not connected to Qdrant to delete a collection.
  • CollectionDoesNotExistError: If the collection to be deleted does not exist.
  • VectorDBError: For other unexpected errors.

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collection_exists

Checks if the collection specified in the config already exists. Returns:
  • bool: True if the collection exists, False otherwise.
Raises:
  • VectorDBConnectionError: If not connected to Qdrant to check for a collection.
  • VectorDBError: If checking collection existence fails.

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upsert

Adds new data or updates existing data in the Qdrant collection. This method transforms the framework-native data lists into Qdrant’s PointStruct format and uses the high-performance upsert API. It respects the write consistency and batching parameters defined in the config. Parameters:
  • vectors (List[List[float]]): A list of dense vector embeddings.
  • payloads (List[Dict[str, Any]]): A list of corresponding metadata objects.
  • ids (List[Union[str, int]]): A list of unique identifiers for each record.
  • chunks (Optional[List[str]]): A list of text chunks.
  • **kwargs: Provider-specific options.
Raises:
  • VectorDBConnectionError: If not connected to upsert data.
  • ValueError: If the lengths of vectors, payloads, and ids lists are not identical.
  • UpsertError: If the data ingestion fails.

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delete

Removes data from the collection by their unique identifiers. Parameters:
  • ids (List[Union[str, int]]): A list of specific IDs to remove.
  • **kwargs: Provider-specific options.
Raises:
  • VectorDBConnectionError: If not connected to delete data.
  • VectorDBError: If the deletion fails.

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fetch

Retrieves full records (payload and vector) by their unique IDs. Parameters:
  • ids (List[Union[str, int]]): A list of IDs to retrieve the full records for.
  • **kwargs: Provider-specific options.
Returns:
  • List[VectorSearchResult]: A list of VectorSearchResult objects containing the fetched data.
Raises:
  • VectorDBConnectionError: If not connected to fetch data.
  • VectorDBError: If the fetch operation fails.
A master search method that dispatches to the appropriate specialized search function. Parameters:
  • top_k (Optional[int]): The number of results to return. If None, falls back to the default in the Config.
  • query_vector (Optional[List[float]]): The vector for dense or hybrid search.
  • query_text (Optional[str]): The text for full-text or hybrid search.
  • filter (Optional[Dict[str, Any]]): An optional metadata filter.
  • alpha (Optional[float]): The weighting factor for hybrid search. If None, falls back to the default in the Config.
  • fusion_method (Optional[Literal[‘rrf’, ‘weighted’]]): The algorithm to use for hybrid search (‘rrf’ or ‘weighted’).
  • similarity_threshold (Optional[float]): The minimum similarity score for results. If None, falls back to the default in the Config.
  • **kwargs: Additional provider-specific options.
Returns:
  • List[VectorSearchResult]: A list of VectorSearchResult objects.
Raises:
  • ConfigurationError: If the requested search is disabled or the wrong combination of arguments is provided.
  • SearchError: If any underlying search operation fails.
Performs a pure vector similarity search. Parameters:
  • query_vector (List[float]): The vector embedding to search for.
  • top_k (int): The number of top results to return.
  • filter (Optional[Dict[str, Any]]): A metadata filter to apply. Defaults to None.
  • similarity_threshold (Optional[float]): The minimum similarity score for results. Defaults to None.
  • **kwargs: Additional provider-specific options.
Returns:
  • List[VectorSearchResult]: A list of the most similar results.
Raises:
  • SearchError: If the search operation fails.

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full_text_search

Performs a full-text search using Qdrant’s payload filtering. For this to be performant, a payload index should be created on the target text field in Qdrant beforehand. Parameters:
  • query_text (str): The text string to search for.
  • top_k (int): The number of top results to return.
  • filter (Optional[Dict[str, Any]]): A metadata filter to apply. Defaults to None.
  • similarity_threshold (Optional[float]): The minimum similarity score for results. Defaults to None.
  • **kwargs: Additional provider-specific options.
Returns:
  • List[VectorSearchResult]: A list of matching results.
Raises:
  • VectorDBConnectionError: If not connected to perform a full-text search.
  • SearchError: If the search operation fails.
Combines dense and full-text search results using a specified fusion method. Parameters:
  • query_vector (List[float]): The dense vector for the semantic part of the search.
  • query_text (str): The raw text for the keyword/sparse part of the search.
  • top_k (int): The number of final results to return.
  • filter (Optional[Dict[str, Any]]): An optional metadata filter.
  • alpha (Optional[float]): The weight for combining scores. If None, falls back to the default in the Config.
  • fusion_method (Optional[Literal[‘rrf’, ‘weighted’]]): The algorithm to use for fusing results (‘rrf’ or ‘weighted’).
  • similarity_threshold (Optional[float]): The minimum similarity score for results. If None, falls back to the default in the Config.
  • **kwargs: Additional provider-specific options.
Returns:
  • List[VectorSearchResult]: A list of VectorSearchResult objects, ordered by the combined hybrid score.
Raises:
  • ConfigurationError: If the fusion method is unsupported.
  • SearchError: If the search operation fails.
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