test_neo4j.py•4.98 kB
import os
import pathlib
import cognee
from cognee.infrastructure.files.storage import get_storage_config
from cognee.modules.retrieval.graph_completion_retriever import GraphCompletionRetriever
from cognee.modules.search.operations import get_history
from cognee.modules.users.methods import get_default_user
from cognee.shared.logging_utils import get_logger
from cognee.modules.search.types import SearchType
from cognee.modules.engine.models import NodeSet
logger = get_logger()
async def main():
cognee.config.set_graph_database_provider("neo4j")
data_directory_path = str(
pathlib.Path(
os.path.join(pathlib.Path(__file__).parent, ".data_storage/test_neo4j")
).resolve()
)
cognee.config.data_root_directory(data_directory_path)
cognee_directory_path = str(
pathlib.Path(
os.path.join(pathlib.Path(__file__).parent, ".cognee_system/test_neo4j")
).resolve()
)
cognee.config.system_root_directory(cognee_directory_path)
await cognee.prune.prune_data()
await cognee.prune.prune_system(metadata=True)
dataset_name = "cs_explanations"
explanation_file_path_nlp = os.path.join(
pathlib.Path(__file__).parent, "test_data/Natural_language_processing.txt"
)
from cognee.infrastructure.databases.graph import get_graph_engine
graph_engine = await get_graph_engine()
is_empty = await graph_engine.is_empty()
assert is_empty, "Graph has to be empty"
await cognee.add([explanation_file_path_nlp], dataset_name)
explanation_file_path_quantum = os.path.join(
pathlib.Path(__file__).parent, "test_data/Quantum_computers.txt"
)
await cognee.add([explanation_file_path_quantum], dataset_name)
is_empty = await graph_engine.is_empty()
assert is_empty, "Graph has to be empty before cognify"
await cognee.cognify([dataset_name])
is_empty = await graph_engine.is_empty()
assert not is_empty, "Graph shouldn't be empty"
from cognee.infrastructure.databases.vector import get_vector_engine
vector_engine = get_vector_engine()
random_node = (await vector_engine.search("Entity_name", "Quantum computer"))[0]
random_node_name = random_node.payload["text"]
search_results = await cognee.search(
query_type=SearchType.GRAPH_COMPLETION, query_text=random_node_name
)
assert len(search_results) != 0, "The search results list is empty."
print("\n\nExtracted sentences are:\n")
for result in search_results:
print(f"{result}\n")
search_results = await cognee.search(query_type=SearchType.CHUNKS, query_text=random_node_name)
assert len(search_results) != 0, "The search results list is empty."
print("\n\nExtracted chunks are:\n")
for result in search_results:
print(f"{result}\n")
search_results = await cognee.search(
query_type=SearchType.SUMMARIES, query_text=random_node_name
)
assert len(search_results) != 0, "Query related summaries don't exist."
print("\nExtracted results are:\n")
for result in search_results:
print(f"{result}\n")
# NOTE: Due to the test failing often on weak LLM models we've removed this test for now
# search_results = await cognee.search(
# query_type=SearchType.NATURAL_LANGUAGE,
# query_text=f"Find nodes connected to node with name {random_node_name}",
# )
# assert len(search_results) != 0, "Query related natural language don't exist."
# print("\nExtracted results are:\n")
# for result in search_results:
# print(f"{result}\n")
user = await get_default_user()
history = await get_history(user.id)
assert len(history) == 6, "Search history is not correct."
nodeset_text = "Neo4j is a graph database that supports cypher."
await cognee.add([nodeset_text], dataset_name, node_set=["first"])
await cognee.cognify([dataset_name])
context_nonempty = await GraphCompletionRetriever(
node_type=NodeSet,
node_name=["first"],
).get_context("What is in the context?")
context_empty = await GraphCompletionRetriever(
node_type=NodeSet,
node_name=["nonexistent"],
).get_context("What is in the context?")
assert isinstance(context_nonempty, list) and context_nonempty != [], (
f"Nodeset_search_test:Expected non-empty string for context_nonempty, got: {context_nonempty!r}"
)
assert context_empty == [], (
f"Nodeset_search_test:Expected empty string for context_empty, got: {context_empty!r}"
)
await cognee.prune.prune_data()
data_root_directory = get_storage_config()["data_root_directory"]
assert not os.path.isdir(data_root_directory), "Local data files are not deleted"
await cognee.prune.prune_system(metadata=True)
is_empty = await graph_engine.is_empty()
assert is_empty, "Neo4j graph database is not empty"
if __name__ == "__main__":
import asyncio
asyncio.run(main())