chore: Delete unused test, fix formatting.

cognee/infrastructure/databases/vector/vector_db_interface.py

@@ -106,7 +106,11 @@ class VectorDBInterface(Protocol):
 
     @abstractmethod
     async def batch_search(
-        self, collection_name: str, query_texts: List[str], limit: Optional[int], with_vectors: bool = False
+        self,
+        collection_name: str,
+        query_texts: List[str],
+        limit: Optional[int],
+        with_vectors: bool = False,
     ):
         """
         Perform a batch search using multiple text queries against a collection.

cognee/tests/test_chromadb.py

@@ -66,8 +66,14 @@ async def test_getting_of_documents(dataset_name_1):
         f"Number of expected documents doesn't match {len(document_ids)} != 2"
     )
 
+
 async def test_vector_engine_search_none_limit():
-    file_path = os.path.join(pathlib.Path(__file__).resolve().parent.parent.parent, "examples", "data", "alice_in_wonderland.txt")
+    file_path = os.path.join(
+        pathlib.Path(__file__).resolve().parent.parent.parent,
+        "examples",
+        "data",
+        "alice_in_wonderland.txt",
+    )
 
     await cognee.prune.prune_data()
     await cognee.prune.prune_system(metadata=True)
@@ -93,6 +99,7 @@ async def test_vector_engine_search_none_limit():
     # Check that we did not accidentally use any default value for limit in vector search along the way (like 5, 10, or 15)
     assert len(result) > 15
 
+
 async def main():
     cognee.config.set_vector_db_config(
         {

cognee/tests/test_lancedb.py

@@ -66,8 +66,14 @@ async def test_getting_of_documents(dataset_name_1):
         f"Number of expected documents doesn't match {len(document_ids)} != 2"
     )
 
+
 async def test_vector_engine_search_none_limit():
-    file_path = os.path.join(pathlib.Path(__file__).resolve().parent.parent.parent, "examples", "data", "alice_in_wonderland.txt")
+    file_path = os.path.join(
+        pathlib.Path(__file__).resolve().parent.parent.parent,
+        "examples",
+        "data",
+        "alice_in_wonderland.txt",
+    )
 
     await cognee.prune.prune_data()
     await cognee.prune.prune_system(metadata=True)
@@ -93,6 +99,7 @@ async def test_vector_engine_search_none_limit():
     # Check that we did not accidentally use any default value for limit in vector search along the way (like 5, 10, or 15)
     assert len(result) > 15
 
+
 async def main():
     cognee.config.set_vector_db_config(
         {

cognee/tests/test_pgvector.py

@@ -67,8 +67,14 @@ async def test_getting_of_documents(dataset_name_1):
         f"Number of expected documents doesn't match {len(document_ids)} != 2"
     )
 
+
 async def test_vector_engine_search_none_limit():
-    file_path = os.path.join(pathlib.Path(__file__).resolve().parent.parent.parent, "examples", "data", "alice_in_wonderland.txt")
+    file_path = os.path.join(
+        pathlib.Path(__file__).resolve().parent.parent.parent,
+        "examples",
+        "data",
+        "alice_in_wonderland.txt",
+    )
 
     await cognee.prune.prune_data()
     await cognee.prune.prune_system(metadata=True)

cognee/tests/unit/infrastructure/databases/vector/test_vector_engine.py

@@ -1,46 +0,0 @@
-import os
-import pathlib
-import pytest
-
-import cognee
-
-
-class TestVectorEngine:
-    # Test that vector engine search works well with limit=None.
-    # Search should return all entities that exist in a collection. Used Alice for a bit larger test.
-    @pytest.mark.asyncio
-    async def test_vector_engine_search_none_limit(self):
-        system_directory_path = os.path.join(
-            pathlib.Path(__file__).parent, ".cognee_system/test_vector_engine_search_none_limit"
-        )
-        cognee.config.system_root_directory(system_directory_path)
-        data_directory_path = os.path.join(
-            pathlib.Path(__file__).parent, ".data_storage/test_vector_engine_search_none_limit"
-        )
-        cognee.config.data_root_directory(data_directory_path)
-
-        file_path = os.path.join(pathlib.Path(__file__).resolve().parent, "data", "alice_in_wonderland.txt")
-
-        await cognee.prune.prune_data()
-        await cognee.prune.prune_system(metadata=True)
-
-        await cognee.add(file_path)
-
-        await cognee.cognify()
-
-        query_text = "List me all the important characters in Alice in Wonderland."
-
-        from cognee.infrastructure.databases.vector import get_vector_engine
-
-        vector_engine = get_vector_engine()
-
-        collection_name = "Entity_name"
-
-        query_vector = (await vector_engine.embedding_engine.embed_text([query_text]))[0]
-
-        result = await vector_engine.search(
-            collection_name=collection_name, query_vector=query_vector, limit=None
-        )
-
-        # Check that we did not accidentally use any default value for limit in vector search along the way (like 5, 10, or 15)
-        assert len(result) > 15