Selective embeddings loading (#2035)

* Invert embedding table loading logic

* Semver

Author: natoverse

.semversioner/next-release/patch-20250827003854793879.json

@@ -0,0 +1,4 @@
+{
+  "type": "patch",
+  "description": "generate_text_embeddings only loads tables if embedding field is specified."
+}

graphrag/index/workflows/generate_text_embeddings.py

@@ -26,7 +26,6 @@
 from graphrag.index.typing.workflow import WorkflowFunctionOutput
 from graphrag.utils.storage import (
     load_table_from_storage,
-    storage_has_table,
     write_table_to_storage,
 )
 
@@ -39,27 +38,35 @@ async def run_workflow(
 ) -> WorkflowFunctionOutput:
     """All the steps to transform community reports."""
     logger.info("Workflow started: generate_text_embeddings")
+    embedded_fields = config.embed_text.names
+    logger.info("Embedding the following fields: %s", embedded_fields)
     documents = None
     relationships = None
     text_units = None
     entities = None
     community_reports = None
-    if await storage_has_table("documents", context.output_storage):
+    if document_text_embedding in embedded_fields:
         documents = await load_table_from_storage("documents", context.output_storage)
-    if await storage_has_table("relationships", context.output_storage):
+    if relationship_description_embedding in embedded_fields:
         relationships = await load_table_from_storage(
             "relationships", context.output_storage
         )
-    if await storage_has_table("text_units", context.output_storage):
+    if text_unit_text_embedding in embedded_fields:
         text_units = await load_table_from_storage("text_units", context.output_storage)
-    if await storage_has_table("entities", context.output_storage):
+    if (
+        entity_title_embedding in embedded_fields
+        or entity_description_embedding in embedded_fields
+    ):
         entities = await load_table_from_storage("entities", context.output_storage)
-    if await storage_has_table("community_reports", context.output_storage):
+    if (
+        community_title_embedding in embedded_fields
+        or community_summary_embedding in embedded_fields
+        or community_full_content_embedding in embedded_fields
+    ):
         community_reports = await load_table_from_storage(
             "community_reports", context.output_storage
         )
 
-    embedded_fields = config.embed_text.names
     text_embed = get_embedding_settings(config)
 
     output = await generate_text_embeddings(