You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
After I executed the graphrag.index and graphrag.query in command line, I didn't find any embedding vector saved in the parquet file. And the lance db seems only stores the entity description text embedding.
I checked the entity.py and there is description_embedding/name_embedding/graph_embedding fields. In the graphrag/query/context_builder/entity_extraction.py it is calling the vector store to search to use the above embeddings.
Can anyone kindly help to point out where name_embedding/graph_embedding vector data are saved?
PS: in the settings.yaml file I already set the embed_graph "enabed" to true.
reacted with thumbs up emoji reacted with thumbs down emoji reacted with laugh emoji reacted with hooray emoji reacted with confused emoji reacted with heart emoji reacted with rocket emoji reacted with eyes emoji
-
After I executed the graphrag.index and graphrag.query in command line, I didn't find any embedding vector saved in the parquet file. And the lance db seems only stores the entity description text embedding.
I checked the entity.py and there is description_embedding/name_embedding/graph_embedding fields. In the graphrag/query/context_builder/entity_extraction.py it is calling the vector store to search to use the above embeddings.
Can anyone kindly help to point out where name_embedding/graph_embedding vector data are saved?
PS: in the settings.yaml file I already set the embed_graph "enabed" to true.
Beta Was this translation helpful? Give feedback.
All reactions