Graph
Enable graph storage via the graph
parameter. This component requires the graph extras package.
When enabled, a graph network is built using the embeddings index. Graph nodes are synced with each embeddings index operation (index/upsert/delete). Graph edges are created using the embeddings index upon completion of each index/upsert/delete embeddings index call.
backend
backend: networkx|rdbms|custom
Sets the graph backend. Defaults to networkx
.
Add custom graph storage engines via setting this parameter to the fully resolvable class string.
The rdbms
backend has the following additional settings.
rdbms
url: database url connection string, alternatively can be set via the
GRAPH_URL environment variable
schema: database schema to store graph - defaults to being
determined by the database
nodes: table to store node data, defaults to `nodes`
edges: table to store edge data, defaults to `edges`
batchsize
batchsize: int
Batch query size, used to query embeddings index - defaults to 256.
limit
limit: int
Maximum number of results to return per embeddings query - defaults to 15.
minscore
minscore: float
Minimum score required to consider embeddings query matches - defaults to 0.1.
approximate
approximate: boolean
When true, queries only run for nodes without edges - defaults to true.
topics
topics:
algorithm: community detection algorithm (string), options are
louvain (default), greedy, lpa
level: controls number of topics (string), options are best (default) or first
resolution: controls number of topics (int), larger values create more
topics (int), defaults to 100
labels: scoring index method used to build topic labels (string)
options are bm25 (default), tfidf, sif
terms: number of frequent terms to use for topic labels (int), defaults to 4
stopwords: optional list of stop words to exclude from topic labels
categories: optional list of categories used to group topics, allows
granular topics with broad categories grouping topics
Enables topic modeling. Defaults are tuned so that in most cases these values don't need to be changed (except for categories). These parameters are available for advanced use cases where one wants full control over the community detection process.