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