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* Remove genid * Move snapshot_rows * Move snapshot * Delete spread_json * Delete unzip * Delete zip * Move unpack_graph * Move compute_edge_combined_degree * Delete create_graph * Delete concat * Delete text replace * Delete text_translate * Move text_split * Inline aggregate override * Move cluster_graph * Move merge_graphs * Semver * Move text_chunk * Move layout_graph and fix some __init__s * Move extract_covariates * Rename text_split -> split_text * Move extract_entities * Move summarize_descriptions * Rename text_chunk -> chunk_text * Move community report creation * Remove verb-level packing operators * Streamline some naming * Streamline param name/order * Move mock LLM data to tests * Fixed missed rename * Update some strategy refs * Rename run_gi * Inject mock responses into integ test config
97 lines
3.8 KiB
Python
97 lines
3.8 KiB
Python
# Copyright (c) 2024 Microsoft Corporation.
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# Licensed under the MIT License
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import pytest
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from datashaper.errors import VerbParallelizationError
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from pandas.testing import assert_series_equal
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from graphrag.config.enums import LLMType
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from graphrag.index.workflows.v1.create_final_covariates import (
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build_steps,
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workflow_name,
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)
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from .util import (
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get_config_for_workflow,
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get_workflow_output,
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load_expected,
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load_input_tables,
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)
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MOCK_LLM_RESPONSES = [
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"""
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(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.)
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""".strip()
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]
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MOCK_LLM_CONFIG = {"type": LLMType.StaticResponse, "responses": MOCK_LLM_RESPONSES}
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async def test_create_final_covariates():
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input_tables = load_input_tables(["workflow:create_base_text_units"])
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expected = load_expected(workflow_name)
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config = get_config_for_workflow(workflow_name)
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config["claim_extract"]["strategy"]["llm"] = MOCK_LLM_CONFIG
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steps = build_steps(config)
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actual = await get_workflow_output(
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input_tables,
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{
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"steps": steps,
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},
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)
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input = input_tables["workflow:create_base_text_units"]
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# we removed the subject_type and object_type columns so expect two less columns than the pre-refactor outputs
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assert len(actual.columns) == (len(expected.columns) - 2)
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# 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
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assert len(actual) == len(input)
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# assert all of the columns that covariates copied from the input
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assert_series_equal(actual["text_unit_id"], input["id"], check_names=False)
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assert_series_equal(actual["text_unit_id"], input["chunk_id"], check_names=False)
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assert_series_equal(actual["document_ids"], input["document_ids"])
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assert_series_equal(actual["n_tokens"], input["n_tokens"])
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# make sure the human ids are incrementing and cast to strings
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assert actual["human_readable_id"][0] == "1"
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assert actual["human_readable_id"][1] == "2"
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# check that the mock data is parsed and inserted into the correct columns
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assert actual["covariate_type"][0] == "claim"
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assert actual["subject_id"][0] == "COMPANY A"
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assert actual["object_id"][0] == "GOVERNMENT AGENCY B"
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assert actual["type"][0] == "ANTI-COMPETITIVE PRACTICES"
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assert actual["status"][0] == "TRUE"
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assert actual["start_date"][0] == "2022-01-10T00:00:00"
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assert actual["end_date"][0] == "2022-01-10T00:00:00"
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assert (
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actual["description"][0]
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== "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"
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)
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assert (
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actual["source_text"][0]
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== "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."
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)
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async def test_create_final_covariates_missing_llm_throws():
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input_tables = load_input_tables(["workflow:create_base_text_units"])
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config = get_config_for_workflow(workflow_name)
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del config["claim_extract"]["strategy"]["llm"]
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steps = build_steps(config)
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with pytest.raises(VerbParallelizationError):
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await get_workflow_output(
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input_tables,
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{
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"steps": steps,
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},
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)
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