# Copyright (c) 2024 Microsoft Corporation. # Licensed under the MIT License from graphrag.data_model.schemas import COVARIATES_FINAL_COLUMNS from graphrag.index.workflows.extract_covariates import ( run_workflow, ) from graphrag_llm.config import LLMProviderType from pandas.testing import assert_series_equal from tests.unit.config.utils import get_default_graphrag_config from .util import ( create_test_context, load_test_table, ) MOCK_LLM_RESPONSES = [ """ (COMPANY A<|>GOVERNMENT AGENCY B<|>ANTI-COMPETITIVE PRACTICES<|>TRUE<|>2022-01-10T00:00:00<|>2022-01-10T00:00:00<|>Company A was found to engage in anti-competitive practices because it was fined for bid rigging in multiple public tenders published by Government Agency B according to an article published on 2022/01/10<|>According to an article published on 2022/01/10, Company A was fined for bid rigging while participating in multiple public tenders published by Government Agency B.) """.strip() ] async def test_extract_covariates(): input = load_test_table("text_units") context = await create_test_context( storage=["text_units"], ) config = get_default_graphrag_config() config.extract_claims.enabled = True config.extract_claims.description = "description" llm_settings = config.get_completion_model_config( config.extract_claims.completion_model_id ) llm_settings.type = LLMProviderType.MockLLM llm_settings.mock_responses = MOCK_LLM_RESPONSES # type: ignore await run_workflow(config, context) actual = await context.output_table_provider.read_dataframe("covariates") for column in COVARIATES_FINAL_COLUMNS: assert column in actual.columns # our mock only returns one covariate per text unit, so that's a 1:1 mapping versus the LLM-extracted content in the test data assert len(actual) == len(input) # assert all of the columns that covariates copied from the input assert_series_equal(actual["text_unit_id"], input["id"], check_names=False) # make sure the human ids are incrementing assert actual["human_readable_id"][0] == 0 assert actual["human_readable_id"][1] == 1 # check that the mock data is parsed and inserted into the correct columns assert actual["covariate_type"][0] == "claim" assert actual["subject_id"][0] == "COMPANY A" assert actual["object_id"][0] == "GOVERNMENT AGENCY B" assert actual["type"][0] == "ANTI-COMPETITIVE PRACTICES" assert actual["status"][0] == "TRUE" assert actual["start_date"][0] == "2022-01-10T00:00:00" assert actual["end_date"][0] == "2022-01-10T00:00:00" assert ( actual["description"][0] == "Company A was found to engage in anti-competitive practices because it was fined for bid rigging in multiple public tenders published by Government Agency B according to an article published on 2022/01/10" ) assert ( actual["source_text"][0] == "According to an article published on 2022/01/10, Company A was fined for bid rigging while participating in multiple public tenders published by Government Agency B." )