c889a57b6b
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288 lines
12 KiB
Python
288 lines
12 KiB
Python
import os
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import pytest
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import pathlib
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from uuid import NAMESPACE_OID, uuid5
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from unittest.mock import AsyncMock, patch
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import cognee
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from cognee.api.v1.datasets import datasets
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from cognee.context_global_variables import set_database_global_context_variables
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from cognee.infrastructure.databases.vector import get_vector_engine_async
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from cognee.infrastructure.llm import LLMGateway
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from cognee.modules.chunking.models.DocumentChunk import DocumentChunk
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from cognee.modules.data.processing.document_types.TextDocument import TextDocument
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from cognee.modules.engine.models import Entity
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from cognee.modules.engine.operations.setup import setup
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from cognee.modules.users.methods import get_default_user
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from cognee.shared.data_models import KnowledgeGraph, Node, Edge, SummarizedContent
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from cognee.shared.logging_utils import get_logger
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from cognee.tests.utils.assert_edges_vector_index_not_present import (
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assert_edges_vector_index_not_present,
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)
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from cognee.tests.utils.assert_edges_vector_index_present import assert_edges_vector_index_present
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from cognee.tests.utils.assert_graph_edges_not_present import assert_graph_edges_not_present
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from cognee.tests.utils.assert_graph_edges_present import assert_graph_edges_present
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from cognee.tests.utils.assert_graph_nodes_not_present import assert_graph_nodes_not_present
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from cognee.tests.utils.assert_graph_nodes_present import assert_graph_nodes_present
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from cognee.tests.utils.assert_nodes_vector_index_not_present import (
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assert_nodes_vector_index_not_present,
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)
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from cognee.tests.utils.assert_nodes_vector_index_present import assert_nodes_vector_index_present
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from cognee.tests.utils.extract_entities import extract_entities
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from cognee.tests.utils.extract_relationships import extract_relationships
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from cognee.tests.utils.extract_summary import extract_summary
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from cognee.tests.utils.filter_overlapping_entities import filter_overlapping_entities
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from cognee.tests.utils.filter_overlapping_relationships import filter_overlapping_relationships
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from cognee.tests.utils.get_contains_edge_text import get_contains_edge_text
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logger = get_logger()
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@pytest.mark.asyncio
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@patch.object(LLMGateway, "acreate_structured_output", new_callable=AsyncMock)
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async def main(mock_create_structured_output: AsyncMock):
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data_directory_path = os.path.join(
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pathlib.Path(__file__).parent, ".data_storage/test_delete_default_graph"
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)
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cognee.config.data_root_directory(data_directory_path)
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cognee_directory_path = os.path.join(
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pathlib.Path(__file__).parent, ".cognee_system/test_delete_default_graph"
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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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await setup()
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def mock_llm_output(text_input: str, system_prompt: str, response_model):
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if text_input == "test": # LLM connection test
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return "test"
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if "John" in text_input and response_model == SummarizedContent:
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return SummarizedContent(
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summary="Summary of John's work.", description="Summary of John's work."
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)
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if "Marie" in text_input and response_model == SummarizedContent:
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return SummarizedContent(
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summary="Summary of Marie's work.", description="Summary of Marie's work."
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)
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if "Marie" in text_input and response_model == KnowledgeGraph:
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return KnowledgeGraph(
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nodes=[
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Node(id="Marie", name="Marie", type="Person", description="Marie is a person"),
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Node(
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id="Apple",
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name="Apple",
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type="Company",
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description="Apple is a company",
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),
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Node(
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id="MacOS",
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name="MacOS",
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type="Product",
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description="MacOS is Apple's operating system",
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),
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],
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edges=[
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Edge(
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source_node_id="Marie",
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target_node_id="Apple",
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relationship_name="works_for",
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),
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Edge(
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source_node_id="Marie", target_node_id="MacOS", relationship_name="works_on"
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),
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],
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)
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if "John" in text_input and response_model == KnowledgeGraph:
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return KnowledgeGraph(
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nodes=[
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Node(id="John", name="John", type="Person", description="John is a person"),
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Node(
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id="Apple",
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name="Apple",
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type="Company",
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description="Apple is a company",
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),
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Node(
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id="Food for Hungry",
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name="Food for Hungry",
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type="Non-profit organization",
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description="Food for Hungry is a non-profit organization",
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),
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],
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edges=[
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Edge(
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source_node_id="John", target_node_id="Apple", relationship_name="works_for"
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),
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Edge(
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source_node_id="John",
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target_node_id="Food for Hungry",
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relationship_name="works_for",
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),
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],
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)
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mock_create_structured_output.side_effect = mock_llm_output
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user = await get_default_user()
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await set_database_global_context_variables("main_dataset", user.id)
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vector_engine = await get_vector_engine_async()
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assert not await vector_engine.has_collection("Entity_name")
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assert not await vector_engine.has_collection("DocumentChunk_text")
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assert not await vector_engine.has_collection("TextSummary_text")
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assert not await vector_engine.has_collection("TextDocument_text")
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assert not await vector_engine.has_collection("EdgeType_relationship_name")
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johns_text = "John works for Apple. He is also affiliated with a non-profit organization called 'Food for Hungry'"
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add_john_result = await cognee.add(johns_text)
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johns_data_id = add_john_result.data_ingestion_info[0]["data_id"]
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maries_text = "Marie works for Apple as well. She is a software engineer on MacOS project."
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add_marie_result = await cognee.add(maries_text)
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maries_data_id = add_marie_result.data_ingestion_info[0]["data_id"]
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cognify_result: dict = await cognee.cognify()
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dataset_id = list(cognify_result.keys())[0]
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johns_document = TextDocument(
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id=johns_data_id,
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name="John's Work",
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raw_data_location="johns_data_location",
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external_metadata="",
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)
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johns_chunk = DocumentChunk(
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id=uuid5(NAMESPACE_OID, f"{str(johns_data_id)}-0"),
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text=johns_text,
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chunk_size=14,
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chunk_index=0,
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cut_type="sentence_end",
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is_part_of=johns_document,
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)
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johns_summary = extract_summary(johns_chunk, mock_llm_output("John", "", SummarizedContent)) # type: ignore
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maries_document = TextDocument(
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id=maries_data_id,
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name="Maries's Work",
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raw_data_location="maries_data_location",
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external_metadata="",
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)
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maries_chunk = DocumentChunk(
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id=uuid5(NAMESPACE_OID, f"{str(maries_data_id)}-0"),
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text=maries_text,
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chunk_size=14,
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chunk_index=0,
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cut_type="sentence_end",
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is_part_of=maries_document,
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)
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maries_summary = extract_summary(maries_chunk, mock_llm_output("Marie", "", SummarizedContent)) # type: ignore
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johns_entities = extract_entities(mock_llm_output("John", "", KnowledgeGraph)) # type: ignore
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maries_entities = extract_entities(mock_llm_output("Marie", "", KnowledgeGraph)) # type: ignore
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(overlapping_entities, johns_entities, maries_entities) = filter_overlapping_entities(
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johns_entities, maries_entities
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)
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johns_data = [
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johns_document,
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johns_chunk,
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johns_summary,
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*johns_entities,
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]
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maries_data = [
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maries_document,
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maries_chunk,
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maries_summary,
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*maries_entities,
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]
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# Assert data points presence in the graph, vector collections and nodes table
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await assert_graph_nodes_present(johns_data + maries_data + overlapping_entities)
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await assert_nodes_vector_index_present(johns_data + maries_data + overlapping_entities)
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johns_relationships = extract_relationships(
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johns_chunk,
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mock_llm_output("John", "", KnowledgeGraph), # type: ignore
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)
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maries_relationships = extract_relationships(
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maries_chunk,
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mock_llm_output("Marie", "", KnowledgeGraph), # type: ignore
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)
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(overlapping_relationships, johns_relationships, maries_relationships) = (
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filter_overlapping_relationships(johns_relationships, maries_relationships)
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)
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johns_relationships = [
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(johns_chunk.id, johns_document.id, "is_part_of"),
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(johns_summary.id, johns_chunk.id, "made_from"),
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*johns_relationships,
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]
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maries_relationships = [
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(maries_chunk.id, maries_document.id, "is_part_of"),
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(maries_summary.id, maries_chunk.id, "made_from"),
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*maries_relationships,
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]
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expected_relationships = johns_relationships + maries_relationships + overlapping_relationships
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await assert_graph_edges_present(expected_relationships)
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await assert_edges_vector_index_present(expected_relationships)
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# Delete John's data from cognee
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await datasets.delete_data(dataset_id, johns_data_id, user) # type: ignore
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# Assert data points presence in the graph, vector collections and nodes table
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await assert_graph_nodes_present(maries_data + overlapping_entities)
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await assert_nodes_vector_index_present(maries_data + overlapping_entities)
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await assert_graph_nodes_not_present(johns_data)
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await assert_nodes_vector_index_not_present(johns_data)
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# Assert relationships presence in the graph, vector collections and nodes table
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await assert_graph_edges_present(maries_relationships + overlapping_relationships)
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await assert_edges_vector_index_present(maries_relationships)
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await assert_graph_edges_not_present(johns_relationships)
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johns_contains_relationships = [
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(
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johns_chunk.id,
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entity.id,
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get_contains_edge_text(entity.name, entity.description),
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{
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"relationship_name": get_contains_edge_text(entity.name, entity.description),
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},
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)
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for entity in johns_entities
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if isinstance(entity, Entity)
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]
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# We check only by relationship name and we need edges that are created by John's data and no other.
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await assert_edges_vector_index_not_present(johns_contains_relationships)
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# Delete Marie's data from cognee
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await datasets.delete_data(dataset_id, maries_data_id, user) # type: ignore
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await assert_graph_nodes_not_present(johns_data + maries_data + overlapping_entities)
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await assert_nodes_vector_index_not_present(johns_data + maries_data + overlapping_entities)
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# Assert relationships presence in the graph, vector collections and nodes table
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await assert_graph_edges_not_present(
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johns_relationships + maries_relationships + overlapping_relationships
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)
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await assert_edges_vector_index_not_present(maries_relationships)
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if __name__ == "__main__":
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import asyncio
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asyncio.run(main())
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