VectorSelection

Bases: object

add_edges(edges)

Add all the documents associated with the edges to the current selection

Documents added by this call are assumed to have a score of 0.

Parameters:

Name	Type	Description	Default
edges	list	a list of the edge ids or edges to add	required

Returns:

Type	Description
None

add_nodes(nodes)

Add all the documents associated with the nodes to the current selection

Documents added by this call are assumed to have a score of 0.

Parameters:

Name	Type	Description	Default
nodes	list	a list of the node ids or nodes to add	required

Returns:

Type	Description
None

append(selection)

Add all the documents in selection to the current selection

Parameters:

Name	Type	Description	Default
selection	VectorSelection	a selection to be added	required

Returns:

Type	Description
VectorSelection	The selection with the new documents

edges()

Return the edges present in the current selection

Returns:

Type	Description
list[Edge]	list of edges in the current selection

expand(hops, window=None)

Add all the documents hops hops away to the selection

Two documents A and B are considered to be 1 hop away of each other if they are on the same entity or if they are on the same node/edge pair. Provided that, two nodes A and C are n hops away of each other if there is a document B such that A is n - 1 hops away of B and B is 1 hop away of C.

Parameters:

Name	Type	Description	Default
hops	int	the number of hops to carry out the expansion	required
window	Tuple[int | str, int | str]	the window where documents need to belong to in order to be considered	None

Returns:

Type	Description
None

expand_edges_by_similarity(query, limit, window=None)

Add the top limit adjacent edges with higher score for query to the selection

This function has the same behavior as expand_entities_by_similarity but it only considers edges.

Parameters:

Name	Type	Description	Default
query	str | list	the text or the embedding to score against	required
limit	int	the maximum number of new edges to add	required
window	Tuple[int | str, int | str]	the window where documents need to belong to in order to be considered	None

Returns:

Type	Description
None

expand_entities_by_similarity(query, limit, window=None)

Add the top limit adjacent entities with higher score for query to the selection

The expansion algorithm is a loop with two steps on each iteration

1. All the entities 1 hop away of some of the entities included on the selection (and not already selected) are marked as candidates.
2. Those candidates are added to the selection in descending order according to the similarity score obtained against the query.

This loops goes on until the number of new entities reaches a total of limit entities or until no more documents are available

Parameters:

Name	Type	Description	Default
query	str | list	the text or the embedding to score against	required
limit	int	the number of documents to add	required
window	Tuple[int | str, int | str]	the window where documents need to belong to in order to be considered	None

Returns:

Type	Description
None

expand_nodes_by_similarity(query, limit, window=None)

Add the top limit adjacent nodes with higher score for query to the selection

This function has the same behavior as expand_entities_by_similarity but it only considers nodes.

Parameters:

Name	Type	Description	Default
query	str | list	the text or the embedding to score against	required
limit	int	the maximum number of new nodes to add	required
window	Tuple[int | str, int | str]	the window where documents need to belong to in order to be considered	None

Returns:

Type	Description
None

get_documents()

Return the documents present in the current selection

Returns:

Type	Description
list[Document]	list of documents in the current selection

get_documents_with_scores()

Return the documents alongside their scores present in the current selection

Returns:

Type	Description
list[Tuple[Document, float]]	list of documents and scores

nodes()

Return the nodes present in the current selection

Returns:

Type	Description
list[Node]	list of nodes in the current selection