revert copilot changes

Author: jgbradley1

docs/examples_notebooks/index_migration_to_v1.ipynb

@@ -202,11 +202,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from graphrag.index.flows.generate_text_embeddings import generate_text_embeddings\n",
-    "\n",
     "from graphrag.cache.factory import CacheFactory\n",
     "from graphrag.callbacks.noop_workflow_callbacks import NoopWorkflowCallbacks\n",
     "from graphrag.config.embeddings import get_embedded_fields, get_embedding_settings\n",
+    "from graphrag.index.flows.generate_text_embeddings import generate_text_embeddings\n",
     "\n",
     "# We only need to re-run the embeddings workflow, to ensure that embeddings for all required search fields are in place\n",
     "# We'll construct the context and run this function flow directly to avoid everything else\n",

examples_notebooks/community_contrib/yfiles-jupyter-graphs/graph-visualization.ipynb

@@ -29,9 +29,6 @@
     "\n",
     "import pandas as pd\n",
     "import tiktoken\n",
-    "from graphrag.query.llm.oai.chat_openai import ChatOpenAI\n",
-    "from graphrag.query.llm.oai.embedding import OpenAIEmbedding\n",
-    "from graphrag.query.llm.oai.typing import OpenaiApiType\n",
     "\n",
     "from graphrag.query.context_builder.entity_extraction import EntityVectorStoreKey\n",
     "from graphrag.query.indexer_adapters import (\n",
@@ -41,6 +38,9 @@
     "    read_indexer_reports,\n",
     "    read_indexer_text_units,\n",
     ")\n",
+    "from graphrag.query.llm.oai.chat_openai import ChatOpenAI\n",
+    "from graphrag.query.llm.oai.embedding import OpenAIEmbedding\n",
+    "from graphrag.query.llm.oai.typing import OpenaiApiType\n",
     "from graphrag.query.structured_search.local_search.mixed_context import (\n",
     "    LocalSearchMixedContext,\n",
     ")\n",

graphrag/storage/factory.py

@@ -44,9 +44,6 @@ def register(
         ------
             TypeError: If creator is a class type instead of a factory function.
         """
-        if isinstance(creator, type):
-            msg = "Registering classes directly is no longer supported. Please provide a factory function instead."
-            raise TypeError(msg)
         cls._registry[storage_type] = creator
 
     @classmethod
@@ -91,24 +88,7 @@ def is_supported_type(cls, storage_type: str) -> bool:
 
 
 # --- register built-in storage implementations ---
-StorageFactory.register(
-    StorageType.blob.value,
-    lambda **kwargs: BlobPipelineStorage(**{
-        k: v for k, v in kwargs.items() if k != "type"
-    }),
-)
-StorageFactory.register(
-    StorageType.cosmosdb.value,
-    lambda **kwargs: CosmosDBPipelineStorage(**{
-        k: v for k, v in kwargs.items() if k != "type"
-    }),
-)
-StorageFactory.register(
-    StorageType.file.value,
-    lambda **kwargs: FilePipelineStorage(**{
-        k: v for k, v in kwargs.items() if k != "type"
-    }),
-)
-StorageFactory.register(
-    StorageType.memory.value, lambda **_kwargs: MemoryPipelineStorage()
-)
+StorageFactory.register(StorageType.blob.value, BlobPipelineStorage)
+StorageFactory.register(StorageType.cosmosdb.value, CosmosDBPipelineStorage)
+StorageFactory.register(StorageType.file.value, FilePipelineStorage)
+StorageFactory.register(StorageType.memory.value, MemoryPipelineStorage)

graphrag/vector_stores/factory.py

@@ -51,9 +51,6 @@ def register(
         ------
             TypeError: If creator is a class type instead of a factory function.
         """
-        if isinstance(creator, type):
-            msg = "Registering classes directly is no longer supported. Please provide a factory function instead."
-            raise TypeError(msg)
         cls._registry[vector_store_type] = creator
 
     @classmethod
@@ -98,13 +95,8 @@ def is_supported_type(cls, vector_store_type: str) -> bool:
 
 
 # --- register built-in vector store implementations ---
+VectorStoreFactory.register(VectorStoreType.LanceDB.value, LanceDBVectorStore)
 VectorStoreFactory.register(
-    VectorStoreType.LanceDB.value, lambda **kwargs: LanceDBVectorStore(**kwargs)
-)
-VectorStoreFactory.register(
-    VectorStoreType.AzureAISearch.value,
-    lambda **kwargs: AzureAISearchVectorStore(**kwargs),
-)
-VectorStoreFactory.register(
-    VectorStoreType.CosmosDB.value, lambda **kwargs: CosmosDBVectorStore(**kwargs)
+    VectorStoreType.AzureAISearch.value, AzureAISearchVectorStore
 )
+VectorStoreFactory.register(VectorStoreType.CosmosDB.value, CosmosDBVectorStore)